Prof. Dr. habil. Matthias Dehmer

Akademischer Werdegang

• 1994 – 1998 Studium der Mathematik und Informatik an der Universität Siegen. Abschluss: Diplom-Mathematiker
• 2002 – 2005 Promotion in Informatik an der TU Darmstadt im Fachgebiet Telekooperation (Prof. Dr. M. Mühlhäuser). Note: “magna cum laude”; Abschluss: Dr. rer. nat.
• 2005 – 2006 Postdoc-Position an der Universität Rostock und an der Universität Wien (Max F. Perutz Laboratories), Austria
• 2006 – 2007 Postdoc-Position an der TU Wien (Diskrete Mathematik) im Bereich Graphen- und Informationstheorie
• 2007 – 2008 Research Assistant Professor an der University of Coimbra in Portugal, Department of Probability Theory
• 2008 Habilitation in Angewandter Diskreter Mathematik an der TU Wien, Austria
• 2009 – 2015 Universitätsprofessor an der UMIT, Hall, Austria in Bioinformatik
• Seit 2015 Dozent an der FFHS, Schweiz
• Seit 2024 Professor für Informatik an der AKAD University

Verantwortliche Tätigkeiten außerhalb der Lehre

• 1998 – 2000 Diplom-Mathematiker bei der Alten-Leipziger Versicherung
• 2000 – 2002 Business Trainer im Bereich Datenbanken bei der Sybase GmbH in Frankfurt
• 2002 Informationsmanager bei Siemens, Frankfurt

Mitgliedschaften und Funktionen in wissenschaftlichen Vereinigungen und Gremien

• Editor of Applied Mathematics and Computation, Elsevier
• Editor of Information Sciences, Elsevier

Drittmittel

• 09/2017 Approved FFG Grant (350.000 EUR), ’ADAPT’, Key Researcher, University of Applied Sciences Upper Austria, Campus Steyr
• 05/2017 Approved FWF Grant (350.000 EUR), ’Measures based on Graph Automorphism’, Principal Investigator, UMIT, Austria
• 10/2016 – 10/2019 (ca. 290.000 EUR) Starter fund of the ’Thousand Talents Program’ of the Nankai University, Tianjin, China
• 04/2014 – 10/2016 Scientific leader of the BMBF project ’Risiken und Kosten der terroristischen Bedrohungen des schienengebundenen ÖPV’ (Risk and costs of threat in the public train sector), UNIBW, Germany
• 02/2014 Approved TWF Grant (20.000 EUR), ’Structural Analysis of Treatment Cycles in Nursing’, Principal Investigator, UMIT, Austria
• 10/2013 Approved FWF Grant (200.000 EUR), ’Characteristics and Interrelations between Methods for Comparing Relational Structures’, Principal Investigator, UMIT, Austria
• 10/2010 Approved Grant from the Tiroler Zukunftsstiftung (ca. 350.000 EUR), ’Stiftungsprofessur für Bioinformatik’, Principal Investigator, UMIT, Austria
• 11/2009 Approved FWF Grant (308.000 EUR), ’Information Measures to Characterize Complex Networks’, Principal Investigator, UMIT, Austria
• 09/2011 Approved Grant from ONCOTYROL (ca. 300.000 EUR), ’Secondary Malignoma – Prospective Evaluation of Radiotherapeutic dose distribution as a cause for induction’, Co-Principal Investigator, UMIT, Austria

Theses

•  Dehmer M.: Analysis of Complex Networks: Graph and Information-theoretic Methods, Cumulative Habilitation Thesis, TU-Wien, 2008
• Dehmer M.: Strukturelle Analyse web-basierter Dokumente, PhD Thesis, TU-Darmstadt, 2005
• Dehmer M.: Schrankensätze in der analytischen Theorie der Polynome, Diploma Thesis, UGHSiegen, 1998
• Dehmer M.: Strukturelle AnalyseWeb-basierter Dokumente, Gabler Edition Wissenschaft, DeutscherUniversitätsverlag, Editors: Lehner F., Bodendorf F., Series: Multimedia und Telekooperation, 2006
• Dehmer M.: Die analytische Theorie der Polynome. Nullstellenschranken für komplexwertige Polynome, Weissensee-Verlag, Berlin, 2004

Books (Authored, Edited and Co-edited)

• Emmert-Streib F., Moutari S., Dehmer M.: Elements of Data Science, Machine Learning, and Artificial Intelligence Using R, Springer Publishing, Cham, Switzerland, 2023
• Emmert-Streib F., Moutari S., Dehmer M.: Mathematical Foundations of Data Science Using R, De Gruyter Oldenbourg, 2020
• Dehmer M., Emmert-Streib F., Jodlbauer H.: Entrepreneurial Complexity, CRC, 2019
• Chen Z., Dehmer M., Emmert-Streib F., Shi Y.: Modern and Interdisciplinary Problems in Network Science: A Translational Research Perspective, CRC, 2018
• Dehmer M., Emmert-Streib F.: Frontiers in Data Science, CRC, 2017
• Shi Y., Dehmer M., Li X., Gutman I.: Graph Polynomials (Discrete Mathematics and Its Applications), CRC, 2016
• Dehmer M., Shi Y., Emmert-Streib F.: Computational Network Analysis with R: Applications in Biology, Medicine and Chemistry, Wiley-Blackwell, 2016
• Dehmer M., Chen Z., Li X., Shi Y.: Mathematical Foundations and Applications of Graph Entropy, Wiley-Blackwell, 2016
• Dehmer M., Emmert-Streib F., Holzinger A., Pickl S.: Big Data of Complex Networks, CRC, 2016
• Dehmer M., Emmert-Streib F., Pickl S.: Computational Network Theory, Wiley-Blackwell, 2015
• Dehmer M., Emmert-Streib F.: Quantitative Graph Theory: Mathematical Foundations and Applications, CRC Press, 2014
• Dehmer M., Mowshowitz A., Emmert-Streib F.: Advances in Network Complexity, Wiley-Blackwell, 2013
• Emmert-Streib F., Dehmer M.: Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data, Wiley-Blackwell, 2013
• Dehmer M., Varmuza K., Bonchev D.: Statistical Modelling of Molecular Descriptors in QSAR/QSPR, Wiley-Blackwell, 2012
• Dehmer M., Basak S. C.: Statistical and Machine Learning Approaches for Network Analysis, Wiley Series in Computational Statistics, Wiley, 2012
• Dehmer M., Emmert-Streib F., Mehler A.: Towards an Information Theory of Complex Networks: Statistical Methods and Applications, Birkhäuser Publishing, 2011
• Dehmer M., Emmert-Streib F., Graber A., Salvador A.: Applied Statistics for Network Biology: Methods in Systems Biology, Wiley-VCH, 2011
• Dehmer M.: Structural Analysis of Complex Networks, Birkhäuser Publishing, 2010
• Dehmer M., Emmert-Streib F.: Analysis of Complex Networks: From Biology to Linguistics, Wiley-VCH Publishing, 2009
• Dehmer M., Drmota M., Emmert-Streib F.: Proceedings of the 2008 International Conference on Information Theory and Statistical Learning (ITSL’08), CSREA Press, 2008
• Emmert-Streib F., Dehmer M.: Medical Biostatistics for Complex Diseases, Wiley-VCH Publishing, 2010
• Emmert-Streib F., Dehmer M.: Analysis of Microarray Data: A Network-based Approach, Wiley-VCH Publishing, 2008
• Emmert-Streib F., Dehmer M.: Information Theory and Statistical Learning, Springer, 2008
• Arabnia H. R., Dehmer M., Emmert-Streib F., Yang Q. U.: Proceedings of the 2007 International Conference on Machine Learning: Models, Technologies and Applications (MLMTA’07), CSREA Press, 2007

Books (Associate Editor)

• Arabnia H. R. et al.: Proceedings of the 2007 International Conference on Bioinformatics and Computational Biology (BIOCOMP’07), Dehmer M., (Associate Editor), CSREA Press, 2007
• Arabnia H. R. et al.: Proceedings of the 2007 International Conference on Artificial Intelligence (ICAI’07), Dehmer M., (Associate Editor), CSREA Press, 2007
• Arabnia H. R. et al.: Proceedings of the 2007 International Conference on Scientific Computing (CSC’07), Dehmer M., (Associate Editor), CSREA Press, 2007
• Arabnia H. R. et al.: Proceedings of the 2007 International Conference on Genetic and Evolutionary Methods (GEM’07). Dehmer M., (Associate Editor), CSREA Press, 2007
• Arabnia H. R., Valafar H.: Proceedings of the 2006 International Conference on Bioinformatics & Computational Biology, Dehmer M., (Associate Editor), Las Vegas, Nevada, USA, 2006, CSREA Press

Books (Series Editor)

• Meller J., NowakW.: Machine Learning Approaches in Bioinformatics. Emmert-Streib F., Dehmer M., (Series Editors). Peter Lang Publishing, 2007

Book Chapter

• Dehmer M., Kraus V., Emmert-Streib F., Pickl S.: What is Quantitative Graph Theory? In: Dehmer M., Emmert-Streib F. (Editors): Quantitative Graph Theory: Theoretical Foundations and Applications, CRC Press, 2014, 1-33
• Dehmer M., Dobrynin A. A.: The Uniqueness of Graph Invariants: Classical and Recent Results.In: Gutman I. et al. (Editors): Topics in Chemical Graph Theory, Mathematical Chemistry Monographs, 2014
• Holzinger, A., Stocker, C., Dehmer, M.: Big complex biomedical data: Towards a taxonomy of data. In: Obaidat M. S., Filipe J. (Editors): Springer Communications in Computer and Information Science CCIS 455, 2014, 3-18
• Holzinger, A., Ofner, B., Dehmer, M.: Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges. In: Holzinger, A., Jurisica, I. (Editors): Interactive Knowledge Discovery and Data Mining: State-of-the-Art and Future Challenges in Biomedical Informatics, Springer Lecture Notes in Computer Science LNCS 8401, Berlin, Heidelberg: Springer, 2014, 241-254
• Preuß M., Dehmer M., Pickl S., Holzinger H.: On Terrain Coverage Optimization by Using a Network Approach for Universal Graph-Based Data Mining and Knowledge Discovery, In: Slezak D., Tan A. H., Peters J. F., Schwabe L. (Editors): Brain Informatics and Health – International Conference, BIH 2014, Warsaw, Poland, Springer Lecture Notes in Computer Science, 2014, 564-573
• Dehmer M., Sivakumar L.: On Comparability Graphs. In: Basak S. C., Restrepo G., Villaveces J. L. (Editors): Advances in Mathematical Chemistry, Bentham Publishing, 2014, in press
• Emmert-Streib F., De Matos Simoes R., Tripathi S., Dehmer M.: Overview of Public Cancer Databases, Resources, and Visualization Tools. In: Emmert-Streib F., Dehmer M. (Editors): Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data, Wiley-Blackwell, 2013, 27-40
• Holzinger, A., Ofner B, Stocker, C., Valdez A. C., Schaar A. K., Ziefle M., Dehmer, M.: On GraphEntropy Measures for Knowledge Discovery from Publication Network Data. In: Cuzzocrea A., Kittl C., Simos D. E.,Weippl E., Xu L. (Editors): Availability, Reliability, and Security in Information Systems and HCI (Lectures Notes in Computer Science), Springer, Vol. 8127, 2013, 354-362
• Müller L., Dehmer M., Emmert-Streib F.: Comparing Biological Networks: A Survey on Graph Classifying Techniques. In: Csukás, B., Prokop A.: Systems Biology: Integrative Biology and Simulation Tools, Springer, Vol. 1, 2013, 43-63
• Müller L., Dehmer M., Emmert-Streib F.: Network-based Methods for Computational Diagnostics by Means of R. In: Trajanoski Z. (Editor): Computational Medicine, Springer, 2012, 185-197
• Dehmer M., Varmuza K.: On Aspects of the Degeneracy of Topological Indices. In: Enachescu F., Filip F. G., Iantovics B. (Editors): Advanced Computational Technologies, Romanian Academy Press, 2012, 99-107
• Dehmer M., Mowshowitz A.: On Measuring the Complexity of Sets of Graphs Using Graph Entropy. In: Enachescu F., Filip F. G., Iantovics B. (Editors): Advanced Computational Technologies, Romanian Academy Press, 2012, 176-184
• Dehmer M., Sivakumar L., Varmuza K.: On Distance-Based Entropy Measures. In: Gutman I., Furtula B. (Editors): Distance in Molecular Graphs – Theory, Mathematical Chemistry Monographs, 2011, 123-138
• Dehmer M., Emmert-Streib F., Tsoy R. Y., Varmuza K.: Quantifying Structural Complexity of Graphs: Information Measures in Mathematical Chemistry. In: Putz M. (Editor): Quantum Frontiers of Atoms and Molecules in Physics, Chemistry, and Biology, Nova Publishing, 2011, 479-497
• Gutman I., Zhang Y., Dehmer M., Ili´c A.: Altenburg, Wiener, and Hosoya Polynomials. In: Gutman I., Furtula B. (Editors): Distance in Molecular Graphs – Theory, Mathematical Chemistry Monographs, 2011, 49-70
• Dehmer M., Graber A.: Recent Developments on Information-theoretic Descriptors to Analyze Networks. In: Gutman I., Furtula B. (Editors): Novel Topological Indices in Mathematical Chemistry, Mathematical Chemistry Monographs, 2010, 21-38
• Dehmer M., Emmert-Streib F.: Mining Graph Patterns in Web-based Systems: A Conceptual View. In: Mehler A., Sharoff S., Rehm G., Santini M. (Editors): Genres on the Web: Computational Models and Empirical Studies, Springer, 2010, 237-253
• Dehmer M., Emmert-Streib F.: Detecting Pathological Pathways of a Complex Disease by a Comparative Analysis of Networks. In: Emmert-Streib F., Dehmer M. (Editors): Analysis of Microarray Data: A Network-based Approach, Wiley-VCH Publishing, 2008, 285-303

Journal Publications

• Emmert-Streib F., Tripathi S., Dehmer M.: Human team behavior and predictability in the massively multiplayer online game WOT Blitz, ACM Transactions on the Web, Vol. 18 (1), 2023, 1-27
• Ghorbani M., Alidehi-Ravandi R., Dehmer M., Emmert-Streib F.: A Study of Roots of a Certain Class of Counting Polynomials, Mathematics, Vol. 11 (13), 2876, 2023
• Emmert-Streib F., Tripathi S., Dehmer M.: Analyzing the scholarly literature of digital twin research: Trends, topics and structure, IEEE Access, Vol. 11, 2023
• Ghorbani M., Alidehi-Ravandi R., Dehmer M., Emmert-Streib F.: A Study of Roots of a Certain Class of Counting Polynomials, Mathematics, Vol. 11 (13), 2876, 2023
• Lotfi A., Mowshowitz A., Dehmer M., A Note on Eigenvalues and Asymmetric Graphs, Axioms, Vol. 12 (6), 510, 2023
• Brezovnik S., Dehmer M., Tratnik N., Žigert-Pleteršek P.: Szeged and Mostar root-indices of graphs, Applied Mathematics and Computation, Vol. 442, 127736, 2023
• Cai J., Li W., Cai W., Dehmer M.: List injective coloring of planar graphs, Applied Mathematics and Computation, Vol. 439, 127631, 2023
• Ghorbani M., Hakimi-Nezhaad M., Dehmer M.: Novel results on partial hosoya polynomials: An application in chemistry, Applied Mathematics and Computation, Vol. 433, 127379, 2022
• Brezovnik S., Dehmer M., Tratnik N., Žigert-Pleteršek P.: Szeged-like entropies of graphs, Applied Mathematics and Computation, Vol. 431, 127325, 2022
• Emmert-Streib M., Dehmer M.: Taxonomy of machine learning paradigms: A data-centric perspective, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery Vol. 12 (5), 2022
• Ma Y., Dehmer M., Künzi U. M., Tripathi S., Ghorbani M., Tao J., Emmert-Streib F.: The usefulness of topological indices, Information Sciences, Vol. 606, 143-151, 2022
• Zhu H., Sun Q., Tao J., Chen Z., Dehmer M., Xie G.: Flexible modeling of parafoil delivery system in wind environments, Communications in Nonlinear Science and Numerical Simulation, Vol. 108, 106210, 2022
• Perera N., Nguyen TTL., Dehmer M., Emmert-Streib F.: Comparison of text mining models for food and dietary constituent named-entity recognition, Machine Learning and Knowledge Extraction, Vol. 4 (1), 2022, 254-275
• Sun Q., Yu L., Zheng Y., Tao J., Sun H., Sun M., Dehmer M., Chen Z.: Trajectory tracking control of powered parafoil system based on sliding mode control in a complex environment, Aerospace Science and Technology, Vol. 122, 107406, 2022
• Bashath S., Perera N., Tripathi S., Manjang K., Dehmer M., Emmert-Streib.: A data-centric review of deep transfer learning with applications to text data, Information Sciences, Vol. 585, 498-528, 2022
• Holzinger A., Dehmer M., Emmert-Streib F., Cucchiara R., Augenstein I., Del Ser J., Samek W., Jurisica I., Diaz-Rodriguez N.: Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence, Information Fusion, Vol. 79, 263-278, 2022
• Li J., Dang J., Zhang J., Chen Z., Dehmer M.: Degree of satisfaction-based adaptive interaction in spatial Prisoner’s dilemma, Nonlinear Dynamics, Vol. 107 (3), 3143-3154, 2022
• Zhou Y., Zheng Y., Tao J., Sun M., Sun Q., Dehmer M., Chen Z.: Servo Health Monitoring Based on Feature Learning via Deep Neural Network, IEEE Access, Vol. 9, 160887-160896, 2021
• Ma Y., Dehmer M., Künzi U. M., Mowshowitz A., Tripathi S., Ghorbani M., Emmert-Streib F.: Relationships between symmetry-based graph measures, Information Sciences, Vol. 581, 291-303, 2021
• Maddah S., Ghorbani M., Dehmer M.: New results of identifying codes in product graphs, Applied Mathematics and Computation, Vol. 410, 126438, 2021
• Ghorbani M., Dehmer M., Lotfi A., Amraei N., Mowshowitz A., Emmert-Streib F.: On the relationship between PageRank and automorphisms of a graph, Information Sciences, Vol. 579, 401-417, 2021
• Ilic A., Ghorbani M., Azizi S., Dehmer M.: On conjectures of network distance measures by using graph spectra, Discrete Applied Mathematics, Vol. 302, 248-255, 2021
• Guo H., Yin Q., Xia C., Dehmer M.: Impact of information diffusion on epidemic spreading in partially mapping two-layered time-varying networks, Nonlinear Dynamics, Vol. 105 (4), 3819-3833, 2021
• Zheng Y., Huang Z., Tao J., Sun H., Sun Q., Sun M., Dehmer M., Chen Z.: A novel chaotic fractional-order beetle swarm optimization algorithm and its application for load-frequency active disturbance rejection control, IEEE Transactions on Circuits and Systems II: Express Briefs, 2021
• Zhu H., Sun Q., Tao J., Tan P., Chen Z., Dehmer M., Xie G.: Fluid-Structure Interaction Simulation and Accurate Dynamic Modeling of Parachute Warhead System Based on Impact Point Prediction, IEEE Access, Vol. 9, 104418-104428, 2021
• Zheng Y., Huang Z., Tao J., Sun H., Sun Q., Dehmer M., Sun M., Chen Z.: Power system load frequency active disturbance rejection control via reinforcement learning-based memetic particle swarm optimization, IEEE Access, Vol. 9, 116194-116206, 2021
• Zhuang H., Sun Q., Chen Z., Dehmer M.: Sliding Mode Robust Control for Maximum Allowable Vertical Tail Damage to Aircraft Based on Linear Matrix Inequality, Journal of Aerospace Engineering, Vol. 34 (4), 05021001, 2021
• Tripathi S., Muhr D., Brunner M., Jodlbauer H., Dehmer M., Emmert-Streib F.: Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing, Frontiers in Artificial Intelligence, Vol. 22 (3), 2021
• Ghorbani M., Dehmer M.: On the Roots of the Modified Orbit Polynomial of a Graph, Symmetry, Vol. 13 (6), 972, 2021
• Ghorbani M., Dehmer M.: Network Analyzing by the Aid of Orbit Polynomial, Symmetry, Vol. 13 (5), 801, 2021
• Emmert-Streib F., Dehmer M.: Data-driven computational social network science: Predictive and inferential models for Web-enabled scientific discoveries, Frontiers in big Data, Vol. 4, 591749, 2021
• Ghorbani M., Jalali-Rad M., Dehmer M.: Orbit polynomial of graphs versus polynomial with integer coefficients, Symmetry, Vol. 13 (4), 710, 2021
• Manjang K., Tripathi S., Yli-Harja O., Dehmer M., Glazko G., Emmert-Streib F.: Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning, Scientific reports, Vol. 11, 156, 1-18, 2021
• Emmert-Streib F., Manjang K., Dehmer M., Yli-Harja O., Auvinen A.: Are There Limits in Explainability of Prognostic Biomarkers? Scrutinizing Biological Utility of Established Signatures, Cancers, Vol. 13 (20), 5087, 2021
• Zheng Y., Tao J., Sun H., Sun Q., Chen Z., Dehmer M., Zhou Q.: Load frequency active disturbance rejection control for multi-source power system based on soft actor-critic, Energies, Vol. 14 (16), 4804, 2021
• Manjang K., Yli-Harja O., Dehmer M., Emmert-Streib F.: Limitations of explainability for established prognostic biomarkers of prostate cancer, Frontiers in Genetics, Vol. 12, 649429, 2021
• Zhang Q., Tao J., Sun Q., Zeng X., Dehmer M., Zhou Q.: A Fall Posture Classification and Recognition Method Based on Wavelet Packet Transform and Support Vector Machine, Applied Sciences, Vol. 11 (11), 5030, 2021
• Hu B., Dehmer M., Emmert-Streib F., Zhang B.: Analysis of the real number of infected people by COVID-19: A system dynamics approach, PLOS One, Vol. 16 (3), 2021, e0245728
• Cheng T., Dehmer M., Emmert-Streib F., Li Y., Liu W., Properties of Commuting Graphs over Semidihedral Groups, Symmetry, Vol. 13 (1), 2021
• Dehmer M., Chen Z., Emmert-Streib F., Mowshowitz A., Varmuza K., Feng L., Jodlbauer H., Shi Y., Tao J.: The Orbit-Polynomial: A Novel Measure of Symmetry in Networks, Vol. 8, 2020, 47619-47639
• Dehmer M., Emmert-Streib F., Mowshowitz M., Ilić A., Chen Z., Yu G., Feng L., Ghorbani M., Varmuza K., Tao J.: Relations and bounds for the zeros of graph polynomials using vertex orbits, Applied Mathematics and Computation Vol. 380, 125239, 2020
• Nadjafi-Arani M.J., Mirzargar M., Emmert-Streib F., Dehmer M.: Partition and Colored Distances in Graphs Induced to Subsets of Vertices and Some of Its Applications, Symmetry, Vol. 12 (12), 2020
• Manjang K., Tripathi S., Yli-Harja O., Dehmer M., Emmert-Streib F.: Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance Scientific reports, Vol. 10 (1), 1-16, 2020
• Ghorbani M., Dehmer M., Emmert-Streib F.: On the Degeneracy of the Orbit Polynomial and Related Graph Polynomials Symmetry, Vol. 12 (10), 2020
• Ghorbani M., Hakimi-Nezhaad M., Dehmer M., Li X.: Analysis of the Graovac-Pisanski Index of Some Polyhedral Graphs Based on Their Symmetry Group Symmetry, Vol. 12 (9), 2020
• Azemati H., Jam F., Ghorbani M., Dehmer M., Ebrahimpour R., Ghanbaran A., Emmert-Streib F.: The Role of Symmetry in the Aesthetics of Residential Building Facades Using Cognitive Science Methods Symmetry, Vol. 12 (9), 2020
• Ghorbani M., Dehmer M., Emmert-Streib F.: Properties of Entropy-Based Topological Measures of Fullerenes, Mathematics Vol. 8 (5), 740, 2020
• Wan P., Chen X., Tu J., Dehmer M., Zhang S., Emmert-Streib F.: On graph entropy measures based on the number of independent sets and matchings, Information Sciences Vol. 516, 491-504, 2020
• Ghorbani M., Dehmer M., Cao S., Feng L., Tao J., Emmert-Streib F.: On the Zeros of the Partial Hosoya Polynomial of Graphs, Information Sciences, Vol. 524, 199-215, 2020
• Li J., Park J.H., Zhang J., Chen Z., Dehmer M.: The networked cooperative dynamics of adjusting signal strength based on information quantity, Nonlinear Dynamics, 1=17, 2020
• Ghorbani M., Dehmer M., Rahmani S., Rajabi-Parsa M.: A Survey on Symmetry Group of Polyhedral Graphs, Symmetry, Vol. 12 (3), 2020
• Emmert-Streib F., Yang Z., Feng L., Tripathi S., Dehmer M.: An Introductory Review of Deep Learning for Prediction Models With Big Data, Frontiers in Artificial Intelligence, Vol. 3 (4), 2020
• Kong M., Zhang Y., Xu D., Chen Z., Dehmer M., FCTP-WSRC: Protein-Protein Interactions Prediction via Weighted Sparse Representation Based Classification, Frontiers in genetics, Vol. 11, 2020
• Yang Z., Dehmer M., Yli-Harja O., Emmert-Streib F.: Combining deep learning with token selection for patient phenotyping from electronic health records, Scientific Reports, Vol. 10 (1), 1-18, 2020
• Gao H., Tao J., Dehmer M., Emmert-Streib F., Sun Q., Chen Z., Xie G., Zhou Q.: In-flight Wind Field Identification and Prediction of Parafoil Systems, Applied Sciences, Vol. 10 (6), 2020
• Dehmer M., Chen Z., Emmert-Streib F., Tripathi S., Mowshowitz A., Levitchi A., Feng L., Shi Y., Tao J.: Measuring the complexity of directed graphs: A polynomial-based approach, PLoS ONE, Vol. 14 (11), 2019, e0223745
• Azam F., Musa A., Dehmer M., Yli-Harja O. P., Emmert-Streib F.: Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach, Frontiers in Genetics, Vol. 10 (70), 2019
• Dehmer M., Chen Z., Emmert-Streib F., Mowshowitz A., Shi Y., Shailesh T., Zhang Y.: Towards Detecting Structural Branching and Cyclicity in Graphs: A Polynomial-based Approach, Information Science, Vol. 471, 19-28, 2019
• Dehmer. M., Chen Z., Mowshowitz A., Jodlbauer H., Emmert-Streib F., Shi Y., Tripathi S., Xia C.: On the Degeneracy of the Randi´c Entropy and Related Graph Measures, Information Sciences, Vol. 501, 2019, 680-687
• Dehmer M., Chen Z., Shi Y., Zhang Y., Tripathi S., Ghorbani M., Mowshowitz A., Emmert-Streib F.: On efficient network similarity measures, Applied Mathematics and Computation, Vol. 362, 2019, 124521
• Emmert-Streib F., Dehmer M.: Evaluation of Regression Models: Model Assessment, Model Selection and Generalization Error, Machine Learning and Knowledge Extraction Vol. 1 (1), 2019, 521-551
• Emmert-Streib F., Yli-Harja O. P., Dehmer M.: Utilizing Social Media Data for Psychoanalysis to Study Human Personality, Frontiers in Psychology, Vol. 10 (2596), 2019
• Emmert-Streib F., Dehmer M.: Introduction to Survival Analysis in Practice, Machine Learning and Knowledge Extraction Vol. 1 (3), 2019, 1013-1038
• Emmert-Streib F., Dehmer M.: Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference, Machine Learning and Knowledge Extraction Vol. 1 (3), 2019, 945-961
• Liu W., Ban J., Feng F., Cheng T., Emmert-Streib F., Dehmer M.: The Maximum Hosoya Index of Unicyclic Graphs with Diameter at Most Four, Symmetry Vol. 11 (8), 2019, 1034
• Moore D., Simoes R. M., Dehmer M., Emmert-Streib F.: Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data, Current Genomics, Vol. 20(1), 2019, 38-48
• Tao J., Du L., Dehmer M., Wen Y. Q., Xie G. M., Zhou, Q.: Path following control for towing system of cylindrical drilling platform in presence of disturbances and uncertainties, ISA Transactions, 2019
• Tao J., Dehmer M., Xie G. M., Zhou, Q.: A generalized predictive control-based path following method for parafoil systems in wind environments, IEEE Access, Vol. (7), 2019, 42586-42595
• Yu G., Dehmer M., Emmert-Streib F., Jodlbauer H.: Hermitian Normalized Laplacian Matrix for Directed Networks, Information Sciences, Vol. 495, 175-184, 2019
• Dehmer M., Pickl S., Shi Y., Yu G.: New inequalities for network distance measures by using graph spectra, Discrete Applied Mathematics, Vol. 252, 2019, 17-27
• Mowshowitz A., Dehmer, M., Emmert-Streib F.: A Note on Graphs with Prescribed Orbit Structure, Entropy, Vol. 21 (11), 2019, 1118
• Ghorbani M., Dehmer M., Mowshowitz A., Tao J., Emmert-Streib F.: The Hosoya entropy of graphs revisited, Symmetry, Vol. 11 (8), 2019, 1013
• Ghorbani M., Dehmer M., Zangi S., Mowshowitz A., Emmert-Streib F.: A Note on Distance-Based Entropy of Dendrimers, Axioms, Vol. 8 (3), 2019
• Ghorbani M., Rajabi-Parsa M., Dehmer M., Mowshowitz A., Emmert-Streib F.: On Properties of Distance-based Entropies on Fullerene Graphs, Entropy, Vol. 21 (482), 2019
• Smolander J., Stupnikov A., Glazko G., Dehmer M., Emmert-Streib F.: Comparing biological information contained in mRNA and non-coding RNAs for classification of lung cancer patients, BMC Cancer Vol. 19 (1), 2019, 1176
• Emmert-Streib F., Dehmer M.: High-Dimensional LASSO-Based Computational Regression Models: Regularization, Shrinkage, and Selection, Machine Learning & Knowledge Extraction, Vol. 1 (1), 2019, 359-383
• Emmert-Streib F., Dehmer M.: Defining Data Science by a Data-Driven Quantification of the Community, Machine Learning & Knowledge Extraction, Vol. 1 (1), 2019, 235-251
• Emmert-Streib F., Dehmer M.: Large-Scale Simultaneous Inference with Hypothesis Testing: Multiple Testing Procedures in Practice, Machine Learning and Knowledge Extraction, Vol. 1 (2), 2019, 653-683
• Emmert-Streib F., Moutari S., Dehmer M.: A comprehensive survey of error measures for evaluating binary decision making in data science, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1303, 2019
• Emmert-Streib F., Dehmer M.: A machine learning perspective on Personalized Medicine: An automized, comprehensive knowledge base with ontology for pattern recognition, Machine Learning and Knowledge Extraction, Vol. 1 (1), 2019 149-156
• Emmert-Streib F., Dehmer M., Yli-Harja O. P.: Ensuring Quality Standards and Reproducible Research for Data Analysis Services in Oncology: A Cooperative Service Model, Frontiers in Cell and Developmental Biology, Vol. 7 (349), 2019
• Emmert-Streib F., Shailesh Tripathi S., Dehmer M.: Constrained Covariance Matrices With a Biologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaussian Graphical Models, Frontiers in Applied Mathematics and Statistics, Vol. 5 (17), 2019
• Emmert-Streib F., Dehmer M.: Network Science: From Chemistry to Digital Society. Frontiers for Young Minds, Vol. 7 (49), 2019
• Emmert-Streib F., Dehmer M.: A Machine Learning Perspective on Personalized Medicine: An Automized, Comprehensive Knowledge Base with Ontology for Pattern Recognition, Machine Learning & Knowledge Extraction, Vol. 1(1), 2019, 149-156
• Emmert-Streib F., Dehmer M.: Inference of Genome-Scale Gene Regulatory Networks: Are There Differences in Biological and Clinical Validations? Machine Learning & Knowledge Extraction, Vol. 1 (1), 2019, 138-148
• Ge L., Liu J., Zhang Y., Dehmer M.: Identifying anticancer peptides by using a generalized chaos game representation, Journal of Mathematical Bioligy, Vol. 78 (1-2), 2019, 441-463
• Ghorbani M., Dehmer M., Rajabi-Parsa M., Emmert-Streib F., Mowshowitz A.: Hosoya entropy of fullerene graphs, Applied Mathematics and Computation, Vol. 352, 2019, 88-98
• Ghorbani M., Taghvayi V., Dehmer M., Emmert-Streib F.: A graph-theoretic approach to construct desired cryptographic Boolean functions, Axioms, Vol. 8 (2), 2019
• Ghorbani M., Dehmer M., Zangi S.: On certain aspects of graph entropies of fullerenes, MATCH Communications in Mathematical and in Computer Chemistry, Vol. 81 (1), 2019, 163-174
• Ma Y., Cao S., Shi Y., Dehmer M., Xia C.: Nordhaus-Gaddum type results for graph irregularities, Applied Mathematics and Computation, Vol. 343, 2019, 268-272
• Musa A., Dehmer M., Yli-Harja O., Emmert-Streib F.: Exploiting Genomic Relations in Big Data Repositories by Graph-Based Search Methods, Machine Learning & Knowledge Extraction, Vol. 1 (1), 2019, 205-210
• Musa A., Tripathi S., Dehmer M., Emmert-Streib F.: L1000 Viewer: A Search Engine and Web Interface for the LINCS Data Repository, Frontiers in Genetics, Vol. 10 (557), 2019
• Musa A., Tripathi S., Dehmer M., Yli-Harja O., Kauffman S. A, Emmert-Streib F.: Systems pharmacogenomic Landscape of Drug similarities from LINCs data: Drug Association Networks, Scientific Reports, Vol. 9 (1), 2019, 7849
• Smolander J., Dehmer M., Emmert-Streib F.: Comparing deep belief networks with support vector machines for classifying gene expression data from complex disorders, FEBS Open Bio, Vol. 9 (7), 2019, 1232-1248
• Stevanovi´c S., Stevanovi´c D., Dehmer M.: On optimal and near-optimal shapes of external shading of windows in apartment buildings, PLoS ONE, Vol. 14 (2), 2019, e0212710
• Wan P., Tu J., Dehmer M., Zhang S., Emmert-Streib F.: Graph entropy based on the number of spanning forests of c-cyclic graphs, Applied Mathematics and Computation, Vol. 363, 2019, 124616
• Wan P., Chen X., Tu J., Dehmer M., Emmert-Streib F.: On Graph Entropy Measures Based on the Number of Independent Sets and Matchings, Information Sciences, 2019, in press
• Wu W., Sun Q., Sun M., Dehmer M., Chen Z.: Modeling and control of parafoils based on computational fluid dynamics, Applied Mathematical Modelling, Vol. 70, 2019, 378-401
• Xia C., Wang Z., Zheng C., Guo Q., Shi Y., Dehmer M., Chen Z.: A new coupled diseaseawareness spreading model with mass media on multiplex networks, Information Sciences, Vol. 471, 2019, 185-200
• Ghorbani M., Dehmer M., Zangi S.: Graph Operations based on Using Distance-based Graph Entropies, Applied Mathematics and Computation, Vol. 333, 2018, 547-555
• Iantovics L. B., Dehmer M., Emmert-Streib F.: MetrIntSimil- An Accurate and Robust Metric for Comparison of Similarity in Intelligence of Any Number of Cooperative Multiagent Systems, Symmetry, Vol. 10 (48), 2018
• Jodlbauer H., Dehmer M., Strasser S.: A Hybrid Binomial Inverse Hypergeometric Probability Distribution: Theory and Applications, Applied Mathematics and Computation, Vol. 338, 2018, 44-54
• Emmert-Streib F., Musa A., Baltakys K., Kanniainen J., Tripathi S., Yli-Harja O., Jodlbauer H., Dehmer M.: Computational analysis of structural properties of economic and financial networks, Journal of Network Theory in Finance, Vol. 4 (3), 2018, 1-32
• Emmert-Streib F., Musa A., Tripathi S., Kandhavelu M., Dehmer M.: Harnessing the biological complexity of Big Data from LINCS Gene Expression Signatures, PLoS ONE, Vol. 13 (8), e0201937, 2018
• Emmert-Streib F., Yli-Harja O., Dehmer M.: Data analytics applications for streaming data from social media: What to predict?, Frontiers in Big Data-Data Mining and Management, Vol. 1, 2018
• Emmert-Streib F., Tripathi S., Yli-Harja O., Dehmer M.: Understanding the world economy in terms of networks: A survey of data-based network science approaches on economic networks, Frontiers in Applied Mathematics and Statistics-Mathematical Finance, Vol. 4, 2018
• Dehmer M., Emmert-Streib F.: Comments to ‘Quantification of network structural dissimilarities’ published by Schieber et al., Mathematical Methods in the Applied Sciences, Vol. 41 (14), 2018, 5711-5713
• Dehmer M., Chen Z., Emmert-Streib F., Shi Y., Shailesh T., Musa A., Mowshowitz A.: Properties of Graph Distance Measures by Means of Discrete Inequalities, Applied Mathematics Modelling, Vol. 59, 2018, 739-749
• Dehmer M., Chen Z., Emmert-Streib F., Shi Y., Shailesh T.: Graph measures with high discrimination power revisited: A random polynomial approach, Information Science, Vol. 467, 2018, 407-414
• Lui S., Xu C., Zhang Y., Liu Y., Yu B., Liu X., Dehmer M.: Feature selection of gene expression data for Cancer classification using double RBF-kernels, BMC Bioinformatics Vol. 19 (396), 2018
• Ma Y., Cao S., Shi Y., Gutman I., Dehmer M., Furtula B.: From the connectivity index to various Randi´c-type descriptors, MATCH Commun. Math. Comput. Chem., Vol. 80 (1) 2018, 85-106
• Zheng C., Xia C., Guo Q., Dehmer M.: Interplay between SIR-based disease spreading and awareness diffusion on multiplex networks, Journal of Parallel and Distributed Computing, Vol. 115, 2018, 20-28
• Tao J., Sun Q., Liang W., Chen Z., He Y., Dehmer M.: Computational fluid dynamics based dynamic modelling of parafoil system, Applied Mathematical Modelling, Vol. 54, 2018, 136-150
• Mowshowitz A., Dehmer M.: A Calculus for Measuring the Elegance of Abstract Graphs, Applied Mathematics and Computation, Vol. 320, 2018, 142-148
• Tao J., Sun Q., Sun H., Chen Z., Dehmer M.: Dynamic Modeling and Trajectory Tracking Control of Parafoil System in Wind Environments, IEEE/ASME Transactions on Mechatronics, Vol. 22 (6), 2017, 2736-2745
• Chen Z., Dehmer M., Emmert-Streib F., Mowshowitz A., Shi Y.: Toward Measuring Network Aesthetics Based on Symmetry, Axioms, Vol. 6 (12), 2017
• Cao S., Dehmer M., Kang Z.: Network Entropies Based on Independent Sets and Matchings, Applied Mathematics and Computation, Vol. 307, 2017, 265-270
• Dehmer M., Emmert-Streib F., Shi Y.: Quantitative Graph Theory: A new branch of graph theory and network science, Information Sciences, Vol. 418-419C, 2017, 575-580
• Dehmer M., Emmert-Streib F., Hu B., Shi Y., Stefu M., Tripathi S.: Highly unique network descriptors based on the roots of the permanental polynomial, Information Sciences, Vol. 408, 2017, 176-181
• Emmert-Streib F., Dehmer M., Yli-Harja O.: Lessons from the Human Genome Project: Modesty, honesty and realism, Frontiers in Genetics-Bioinformatics and Computational Biology, Vol. 8 (184), 2017
• Li T., Dong H., Shi Y., Dehmer M.: A Comparative Analysis of New Graph Distance Measures and Graph Edit Distance, Information Sciences, Vol. 403-404, 2017, 15-21
• Musa A., Ghoraie L. S., Zhang S. D., Glazko G., Yli-Harja O., Dehmer M., Haibe-Kains B., Emmert-Streib S.: A review of connectivity map and computational approaches in pharmacogenomics, Briefings in Bioinformatics, 2017, 1-18
• Tripathi S., Lloyd-Price J., Ribeiro A., Yli-Harja O., Dehmer M., Emmert-Streib F.: sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters, BMC Bioinformatics, Vol. 18 (325), 2017
• Yu G., Qu H., Dehmer M.: Principal minor version of Matrix-Tree theorem for mixed graphs, Applied Mathematics and Computation, Vol. 309, 2017, 27-30
• Xu C., Li. G., Zhang Y., Gutman I., Dehmer M.: Prediction of therapeutic peptides by incorporating q-Wiener index into Chou’s general PseAAC, Journal of Biomedical Informatics, Vol. 75, 2017, 63-69
• Yu L., Zhang Y., Gutman I., Shi Y., Dehmer M.: Protein Sequence Comparison Based on Physicochemical Properties and Position-Feature Energy Matrix, Scientific Reports, Vol. 7 (46237), 2017
• Chen Z., Dehmer M., Shi Y., Yang H.: Sharp Upper Bounds for the Balaban Index of Bicyclic Graphs, MATCH Commun. Math. Comput. Chem., Vol. 75 (1), 2016, 105-128
• Das K. Ch., Dehmer M., A Conjecture Regarding the Extremal Values of Graph Entropy Based on Degree Powers, Entropy, Vol. 18 (183), 2016
• Das K. Ch., Dehmer M., Comparison between the zeroth-order Randi´c index and the sumconnectivity index, Applied Mathematics and Computation, Vol. 266, 2016, 1027-1030
• Dehmer M., Mowshowitz A.: A Case Study of Cracks in the Scientific Enterprise: Reinvention of Information-Theoretic Measures for Graphs, Complexity, Vol. 21, 2016, 20-22
• Emmert-Streib M., Moutari S., Dehmer M.: The process of analyzing data is the emergent feature of data science, Frontiers in Genetics, 2016, Vol. 7 (12)
• Emmert-Streib F., Dehmer M., Shi Y.: Fifty Years of Graph Matching, Network Alignment and Network Comparison, Information Sciences, Vol. 346-347, 2016, 180-197
• Emmert-Streib M., Dehmer M., Yli-Harja O.: Against Dataism and for Data Sharing of Big Biomedical and Clinical Data with Research Parasites, Frontiers in Genetics, Vol. 7 (154), 2016

• Stevanovi´c S., Stevanovi´c D., Dehmer M.: On optimal and near-optimal shapes of external shading of windows in apartment buildings, PLoS ONE, Vol. 14 (2), 2019, e0212710 
• Wan P., Tu J., Dehmer M., Zhang S., Emmert-Streib F.: Graph entropy based on the number of spanning forests of c-cyclic graphs, Applied Mathematics and Computation, Vol. 363, 2019, 124616 150. Wan P., Chen X., Tu J., Dehmer M., Emmert-Streib F.: On Graph Entropy Measures Based on the Number of Independent Sets and Matchings, Information Sciences, 2019, in press 151. Wu W., Sun Q., Sun M., Dehmer M., Chen Z.: Modeling and control of parafoils based on computational fluid dynamics, Applied Mathematical Modelling, Vol. 70, 2019, 378-401 

• Xia C., Wang Z., Zheng C., Guo Q., Shi Y., Dehmer M., Chen Z.: A new coupled diseaseawareness spreading model with mass media on multiplex networks, Information Sciences, Vol. 471, 2019, 185-200 153. Ghorbani M., Dehmer M., Zangi S.: Graph Operations based on Using Distance-based Graph Entropies, Applied Mathematics and Computation, Vol. 333, 2018, 547-555 
• Iantovics L. B., Dehmer M., Emmert-Streib F.: MetrIntSimil- An Accurate and Robust Metric for Comparison of Similarity in Intelligence of Any Number of Cooperative Multiagent Systems, Symmetry, Vol. 10 (48), 2018 
• Jodlbauer H., Dehmer M., Strasser S.: A Hybrid Binomial Inverse Hypergeometric Probability Distribution: Theory and Applications, Applied Mathematics and Computation, Vol. 338, 2018, 44-54 
• Emmert-Streib F., Musa A., Baltakys K., Kanniainen J., Tripathi S., Yli-Harja O., Jodlbauer H., Dehmer M.: Computational analysis of structural properties of economic and financial networks, Journal of Network Theory in Finance, Vol. 4 (3), 2018, 1-32 9 
• Emmert-Streib F., Musa A., Tripathi S., Kandhavelu M., Dehmer M.: Harnessing the biological complexity of Big Data from LINCS Gene Expression Signatures, PLoS ONE, Vol. 13 (8), e0201937, 2018 
• Emmert-Streib F., Yli-Harja O., Dehmer M.: Data analytics applications for streaming data from social media: What to predict?, Frontiers in Big Data-Data Mining and Management, Vol. 1, 2018 
• Emmert-Streib F., Tripathi S., Yli-Harja O., Dehmer M.: Understanding the world economy in terms of networks: A survey of data-based network science approaches on economic networks, Frontiers in Applied Mathematics and Statistics-Mathematical Finance, Vol. 4, 2018 
• Dehmer M., Emmert-Streib F.: Comments to ’Quantification of network structural dissimilarities’ published by Schieber et al., Mathematical Methods in the Applied Sciences, Vol. 41 (14), 2018, 5711-5713 
• Dehmer M., Chen Z., Emmert-Streib F., Shi Y., Shailesh T., Musa A., Mowshowitz A.: Properties of Graph Distance Measures by Means of Discrete Inequalities, Applied Mathematics Modelling, Vol. 59, 2018, 739-749 
• Dehmer M., Chen Z., Emmert-Streib F., Shi Y., Shailesh T.: Graph measures with high discrimination power revisited: A random polynomial approach, Information Science, Vol. 467, 2018, 407-414 
• Lui S., Xu C., Zhang Y., Liu Y., Yu B., Liu X., Dehmer M.: Feature selection of gene expression data for Cancer classification using double RBF-kernels, BMC Bioinformatics Vol. 19 (396), 2018 
• Ma Y., Cao S., Shi Y., Gutman I., Dehmer M., Furtula B.: From the connectivity index to various Randi´c-type descriptors, MATCH Commun. Math. Comput. Chem., Vol. 80 (1) 2018, 85-106 
• Zheng C., Xia C., Guo Q., Dehmer M.: Interplay between SIR-based disease spreading and awareness diffusion on multiplex networks, Journal of Parallel and Distributed Computing, Vol. 115, 2018, 20-28 
• Tao J., Sun Q., Liang W., Chen Z., He Y., Dehmer M.: Computational fluid dynamics based dynamic modelling of parafoil system, Applied Mathematical Modelling, Vol. 54, 2018, 136-150 
• Mowshowitz A., Dehmer M.: A Calculus for Measuring the Elegance of Abstract Graphs, Applied Mathematics and Computation, Vol. 320, 2018, 142-148 
• Tao J., Sun Q., Sun H., Chen Z., Dehmer M.: Dynamic Modeling and Trajectory Tracking Control of Parafoil System in Wind Environments, IEEE/ASME Transactions on Mechatronics, Vol. 22 (6), 2017, 2736-2745 
• Chen Z., Dehmer M., Emmert-Streib F., Mowshowitz A., Shi Y.: Toward Measuring Network Aesthetics Based on Symmetry, Axioms, Vol. 6 (12), 2017 
• Cao S., Dehmer M., Kang Z.: Network Entropies Based on Independent Sets and Matchings, Applied Mathematics and Computation, Vol. 307, 2017, 265-270 
• Dehmer M., Emmert-Streib F., Shi Y.: Quantitative Graph Theory: A new branch of graph theory and network science, Information Sciences, Vol. 418-419C, 2017, 575-580 
• Dehmer M., Emmert-Streib F., Hu B., Shi Y., Stefu M., Tripathi S.: Highly unique network descriptors based on the roots of the permanental polynomial, Information Sciences, Vol. 408, 2017, 176-181 
• Emmert-Streib F., Dehmer M., Yli-Harja O.: Lessons from the Human Genome Project: Modesty, honesty and realism, Frontiers in Genetics-Bioinformatics and Computational Biology, Vol. 8 (184), 2017 10 
• Li T., Dong H., Shi Y., Dehmer M.: A Comparative Analysis of New Graph Distance Measures and Graph Edit Distance, Information Sciences, Vol. 403-404, 2017, 15-21 
• Musa A., Ghoraie L. S., Zhang S. D., Glazko G., Yli-Harja O., Dehmer M., Haibe-Kains B., Emmert-Streib S.: A review of connectivity map and computational approaches in pharmacogenomics, Briefings in Bioinformatics, 2017, 1-18 
• Tripathi S., Lloyd-Price J., Ribeiro A., Yli-Harja O., Dehmer M., Emmert-Streib F.: sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters, BMC Bioinformatics, Vol. 18 (325), 2017 
• Yu G., Qu H., Dehmer M.: Principal minor version of Matrix-Tree theorem for mixed graphs, Applied Mathematics and Computation, Vol. 309, 2017, 27-30 
• Xu C., Li. G., Zhang Y., Gutman I., Dehmer M.: Prediction of therapeutic peptides by incorporating q-Wiener index into Chou’s general PseAAC, Journal of Biomedical Informatics, Vol. 75, 2017, 63-69 
• Yu L., Zhang Y., Gutman I., Shi Y., Dehmer M.: Protein Sequence Comparison Based on Physicochemical Properties and Position-Feature Energy Matrix, Scientific Reports, Vol. 7 (46237), 2017 
• Chen Z., Dehmer M., Shi Y., Yang H.: Sharp Upper Bounds for the Balaban Index of Bicyclic Graphs, MATCH Commun. Math. Comput. Chem., Vol. 75 (1), 2016, 105-128 Das K. Ch., Dehmer M., A Conjecture Regarding the Extremal Values of Graph Entropy Based on Degree Powers, Entropy, Vol. 18 (183), 2016 
• Das K. Ch., Dehmer M., Comparison between the zeroth-order Randi´c index and the sumconnectivity index, Applied Mathematics and Computation, Vol. 266, 2016, 1027-1030 
• Dehmer M., Mowshowitz A.: A Case Study of Cracks in the Scientific Enterprise: Reinvention of Information-Theoretic Measures for Graphs, Complexity, Vol. 21, 2016, 20-22 
• Emmert-Streib M., Moutari S., Dehmer M.: The process of analyzing data is the emergent feature of data science, Frontiers in Genetics, 2016, Vol. 7 (12) 
• Emmert-Streib F., Dehmer M., Shi Y.: Fifty Years of Graph Matching, Network Alignment and Network Comparison, Information Sciences, Vol. 346-347, 2016, 180-197 
• Emmert-Streib M., Dehmer M., Yli-Harja O.: Against Dataism and for Data Sharing of Big Biomedical and Clinical Data with Research Parasites, Frontiers in Genetics, Vol. 7 (154), 2016 
• Stupnikov A., Tripathi S., de Matos Simoes R., McArt D., Salto-Tellez M., Galina G., Dehmer M., Emmert-Streib M.: samExploreR: Exploring reproducibility and robustness of RNA-seq results based on SAM files, Bioinformatics, Vol. 32 (20), 2016 
• Tripathi S., Moutari S., Dehmer M., Emmert-Streib M.: Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules, Bioinformatics, 2016, Vol. 17 (129) 
• Cao S., Dehmer M.: Degree-Based Entropies of Networks Revisited, Applied Mathematics and Computation, Vol. 261, 2015, 141-147 
• Chen Z., Dehmer M., Shi Y.: Bounds for degree-based Network Entropies, Applied Mathematics and Computation, Vol. 265, 2015, 983-993 
• Chen Z., Dehmer M., Emmert-Streib F., Shi Y.: Entropy ofWeighted Graphs with Randi´cWeights, Entropy, Vol. 17 (6), 2015, 3710-3723 
• Dehmer M., Li X., Shi Y.: Connections Between Generalized Graph Entropies and Graph Energy, Complexity, Vol. 21, 2015, 35-41 11 
• Dehmer M., Emmert-Streib F., Shi Y., Stefu M., Tripathi S.: Discrimination Power of Polynomialbased Descriptors for Graphs by Using Functional Matrices, PLoS ONE, Vol. 10 (10), 2015, e0139265 
• Dehmer M., Shi Y.: A Method for Inferring Inequalities for Probability Values Applied to Complex Networks, Complexity, Vol. 21 (51), 2015, 113-115
• Dehmer M., Meyer-Nieberg S., Mihelcic G., Pickl S., Zsifkovits M.: Collaborative Risk Management for National Security and Strategic Foresight, EURO Journal on Decision Processes, Vol. 3 (3), 2015, 305-337 
• Dehmer M., Moosbrugger M., Shi Y.: Encoding Structural Information Uniquely With Polynomialbased Descriptors by Employing The Randi´c Matrix, Applied Mathematics and Computation, Vol. 268, 2015, 164-168 
• Dehmer M., Emmert-Streib F., Shi Y.: Graph Distance Measures Based on Topological Indices Revisited, Applied Mathematics and Computation, Vol. 266, 2015, 623-633 
• Dehmer M., Kurt Z., Emmert-Streib F., Them C., Schulc E., Hofer S.: Structural Analysis of Treatment Cycles Representing Transitions Between Nursing Organizational Units Inferred from Diabetes, PLoS ONE, Vol. 10 (6), 2015, e0127152 
• Dehmer M., Varmuza K.: A Comparative Analysis of the Tanimoto Index and Graph Edit Distance for Measuring the Topological Similarity of Trees, Applied Mathematics and Computation, Vol. 259, 2015, 242-250 
• Dehmer M., Shi Y., Mowshowitz A.: Discrimination Power of Graph Measures based on Complex Zeros of The Partial Hosoya Polynomial, Applied Mathematics and Computation, Vol. 250 (1), 2015, 352-355 
• Emmert-Streib F., Dehmer M.: Biological networks: The microscope of the 21st century, Frontiers in Genetics, Vol. 6 (307), 2015 
• Li X., Qin Z., Wei M., Gutman I., Dehmer M.: Novel inequalities for generalized graph entropies – Graph energies and topological indices, Applied Mathematics and Computation, Vol. 259, 2015, 470-479 
• Ili´c A., Dehmer M.: On the Distance Based Graph Entropies, Applied Mathematics and Computation, Vol. 269, 2015, 647-650 
• Mowshowitz A., Dehmer M.: The Hosoya entropy of a graph, Entropy, Vol. 17 (3), 2015, 1054- 1062 
• Nistor, M. S., Dehmer, M., Pickl, S., Network Exploratory Analysis on Subway Transportation Systems against Complex Threats Including a Human Factors Perspective. Procedia Manufacturing, Vol. 3, 2015, 6593-6598 
• Altay G., Kurt Z., Dehmer M., Emmert-Streib F.: Netmes: Assessing gene network inference algorithms by ensemble network-based measures, Evolutionary Bioinformatics, Vol. 10, 2014, 1-9 
• Cao S., Dehmer M., Shi Y.: Extremality of Degree-Based Graph Entropies, Information Sciences, Vol. 278, 2014, 22-33 
• Chen Z., Dehmer M., Emmert-Streib F., Shi Y.: Entropy Bounds for Dendrimers, Applied Mathematics and Computation, Vol. 242, 2014, 462-472 
• Chen Z., Dehmer M., Shi Y.: A Note on Distance-based Graph Entropies, Entropy, Vol. 16 (10), 2014, 5416-5427 
• Dehmer M., Tsoy Y. R.: Numerical Evaluation and Comparison of Kalantari’s Zero Bounds for Complex Polynomials, PLoS ONE, Vol. 9 (10), 2014, e110540. 12 
• Dehmer M., Mowshowitz A., Shi Y.: Structural Differentiation of Graphs using Hosoya-based Indices, PLoS ONE, 2014, Vol. 9 (7), e102459 
• Dehmer M., Emmert-Streib F., Grabner M.: A Computational Approach to Construct a Multivariate Complete Graph Invariant, Information Sciences, Vol. 260 (1), 2014, 200-208 
• Dehmer M., Shi Y.: The Uniqueness of DMAX-Matrix Graph Invariants, PLoS ONE, Vol. 9 (1), 2014, e83868 214. Dehmer M., Emmert-Streib F., Shi Y.: Interrelations of Graph Distance Measure Based on Topological Indices, PLoS ONE, Vol. 9 (4), 2014, e94985 
• Emmert-Streib F., Dehmer M., Haibe-Kains B.: Gene regulatory networks and their applications: Understanding biological and medical problems in terms of networks, Frontiers in Cell and Developmental Biology, Vol. 2, Article 38, 2014 
• Emmert-Streib F., Dehmer M., Haibe-Kains B.: Untangling statistical and biological models to understand network inference: The need for a genomics network ontology, Frontiers in Genetics, Vol. 5, Article 299, 2014 
• Emmert-Streib F., de Matos Simoes R., Mullan P., Haibe-Kains B., Dehmer M.: The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks, Frontiers in Genetics, Vol. 15 (5), 2014 
• Emmert-Streib F., de Matos Simoes R., Glazko G., McDade S., Haibe-Kains B., Holzinger A., Dehmer M., Campbell F.: Functional and genetic analysis of the colon cancer network, BMC Bioinformatics, Vol. 15 (Suppl 6):S6, 2014 
• Holzinger A., Dehmer M., Jurisica I., Knowledge Discovery and Interactive Data Mining in Bioinformatics – State-of-the-Art, Future challenges and Research Directions, BMC Bioinformatics, Vol. 15 (Suppl 6:I1), 2014 
• Kraus V., Dehmer M., Emmert-Sreib F.: Probabilistic Inequalities for Evaluating Structural Network Measures, Information Sciences, Vol. 288, 2014, 220-245 
• Schutte M., Dehmer M.: Large-Scale Analysis of Structural Branching Measures, Journal of Mathematical Chemistry, Vol. 52 (3), 2014, 805-819 
• Tripathi S., Dehmer M., Emmert-Streib F.: NetBioV: An R package for visualizing large network data in biology and medicine, Bioinformatics, Vol. 30 (19), 2014, 2834-2836 
• Dander A., Müller L., Gallasch R., Pabinger S., Emmert-Streib F., Graber A., Dehmer M.: A Large-Scale Database of Molecular Descriptors using compounds from PubChem, Source Code for Biology and Medicine, Vol. 8 (22), 2013 
• Dehmer M., Emmert-Streib F., Tripathi S.: Large-Scale Evaluation of Molecular Descriptors by Means of Clustering, PLoS ONE, Vol. 8 (12), 2013, e83956 
• Dehmer M., Müller L., Emmert-Streib F.: Quantitative Network Measures as Biomarkers for Classifying Prostate Cancer Disease States: A Systems Approach to Diagnostic Biomarkers, PLoS ONE, Vol. 8 (11), 2013, e77602 
• Dehmer M., Mowshowitz A.: The Discrimination Power of Structural SuperIndices, PLoS ONE, Vol. 8 (7), 2013, e70551 
• Dehmer M., Grabner M., Mowshowitz A., Emmert-Streib F.: An Efficient Heuristic Approach to Detecting Graph Isomorphism Based on Combinations of Highly Discriminating Invariants, Advances in Computational Mathematics, Vol. 39 (2), 2013, 311-325 
• Dehmer M., Hackl W. O., Emmert-Streib F., Schulc E., Them C.: Network Nursing: Connections between Nursing and Complex Network Science, International Journal of Nursing Knowledge, Vol. 24 (3), 2013, 150-156 13 
• Dehmer M., Grabner M.: The Discrimination Power of Molecular Identification Numbers Revisited, MATCH Commun. Math. Comput. Chem., Vol. 69 (3), 2013, 785-794 
• de Matos Simoes R., Dehmer M., Emmert-Streib F.: B-cell lymphoma gene regulatory networks: Biological consistency among inference methods, Frontiers in Genetics, Vol. 4, Article 281, 2013 
• de Matos Simoes R., Dehmer M., Emmert-Streib F.: Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information, BMC Genomics, Vol. 14 (324), 2013 
• Emmert-Streib F., Dehmer M.: Enhancing systems medicine beyond genotype data by dynamic patient signatures: Having information and using it too, Frontiers in Bioinformatics and Computational Biology, Vol. 4, Article 241, 2013 
• Emmert-Streib F., Dehmer M., Lyardet F.: Learning Systems Biology: Conceptual Considerations Toward a Web-based Learning Platform, Education Sciences, Vol. 3 (2) 2013, 158-171 
• Emmert-Streib F., Tripathi S., de Matos Simoes R., Hawwa A. F., Dehmer M.: The human disease network. Opportunities for classification, diagnosis and prediction of disorders and disease genes, Systems Biomedicine, Vol. 1 (1), 2013, 1-8 
• Furtula B., Gutman I., Dehmer M.: On Structure-Sensitivity of Degree-Based Topological Indices, Applied Mathematics and Computation, Vol. 219, 2013, 8973-8978
• Kraus V., Dehmer M., Schutte M.: On Sphere-Regular Graphs and the Extremality of Information- Theoretic Network Measures, MATCH Commun. Math. Comput. Chem., Vol. 70 (3), 2013, 885-900 
• Varmuza K., Filzmoser P., Dehmer M.: Multivariate linear QSPR/QSAR models: Rigorous evaluation of variable selection for PLS, Computational and Structural Biotechnology Journal, Vol. 5 (6), e201302007, 2013, 1-10 
• Dehmer M., Kraus V.: On Extremal Properties of Graph Entropies, MATCH Commun. Math. Comput. Chem., Vol. 68 (3), 2012, 889-912 
• Dehmer M., Tsoy Y. R.: The Quality of Zero Bounds for Complex Polynomials, PLoS ONE, Vol. 7 (7), 2012, e39537 
• Dehmer M., Grabner M., Furtula B.: Structural Discrimination of Networks by Using Distance, Degree and Eigenvalue-Based Measures, PLoS ONE, Vol. 7 (7), 2012, e38564 
• Dehmer M., Grabner M., Varmuza K.: Information Indices with High Discriminative Power for Graphs, PLoS ONE, Vol. 7 (2), 2012, e31214 
• Dehmer M., Ili´c A.: Location of Zeros of Wiener and Distance Polynomials, PLoS ONE, Vol. 7 (3), 2012, e28328 
• Dehmer M., Sivakumar L.: Recent Developments in Quantitative Graph Theory: Information Inequalities for Networks, PLoS ONE, Vol. 7 (2), 2012, e31395 
• Dehmer M., Sivakumar L., Varmuza K.: Uniquely Discriminating Molecular Structures Using Novel Eigenvalue-based Descriptors, MATCH Commun. Math. Comput. Chem., Vol. 67 (1), 2012, 147-172 
• Emmert-Streib F., de Matos Simoes R., Tripathi S., Glazko G. V., Dehmer M.: A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data, Scientific Reports (Nature Publishing), Vol. 2, 2012
•  Emmert-Streib F., Dehmer M.: Exploring statistical and population aspects of network complexity, PLoS ONE 7(5), 2012, e34523 
• Grabner M., Dehmer M., Varmuza K.: RMol: A Toolset for Transforming SD/Molfile structure information into R Objects, Source Code for Biology and Medicine, Vol. 7 (12), 2012 14 
• Kusonmano K., Kugler K., Graber A., Emmert-Streib F., Dehmer M.: Effects of pooling samples on the performance of classification algorithms: A comparative study, The Scientific World Journal, Vol. 12, 2012 
• Mowshowitz A., Dehmer M.: Entropy and the Complexity of Graphs Revisited, Entropy, Vol. 14 (3), 2012, 559-570 250. Netzer M., Kugler K., Müller L., Weinberger K., Graber A., Baumgartner C., Dehmer M.: A Network-Based Feature Selection Approach to Identify Metabolic Signatures in Disease, Journal of Theoretical Biology, Volume 310, 2012, 216-222 
• Sivakumar L., Dehmer M.: Towards Information Inequalities for Generalized Graph Entropies, PLoS ONE, Vol. 7 (6), 2012, e38159 
• Varmuza K., Filzmoser P., Liebmann B., Dehmer M.: Redundancy analysis for characterizing the correlation between groups of variables – Applied to molecular descriptors, Chemometrics and Intelligent Laboratory Systems, Vol. 117, 31-41, 2012 
• Dehmer M.: Information Theory of Networks, Symmetry, Vol. 3 (4), 2011, 767-779 
• Dehmer M.: Inclusion Radii for the Zeros of Special Polynomials, Buletinul Academiei de Stiinte a Republicii Moldova. Matematica, Vol. 3 (67), 2011, 84-90 
• Dehmer M., Mowshowitz A.: Bounds on the Moduli of Polynomial Zeros, Applied Mathematics and Computation, Vol. 218 (8), 2011, 4128-4137 
• Dehmer M., Mowshowitz A.: Generalized Graph Entropies, Complexity, Vol. 17 (2), 2011, 45-50 
• Dehmer M., Mowshowitz A., Emmert-Streib F.: Connections between Classical and Parametric Network Entropies, PLoS ONE, Vol. 6 (1), 2011, e15733 
• Dehmer M., Mowshowitz A.: A History of Graph Entropy Measures, Information Sciences, Vol. 1 (1), 2011, 57-78 
• Emmert-Streib F., Dehmer M.: Networks for Systems Biology: Conceptual Connection of Data and Function, IET Systems Biology, Vol. 5 (3), 2011, 185-207 
• Kugler K., Müller L., Graber A., Dehmer M.: Graph Prototyping for Co-Expression Cancer Networks, PLoS ONE Vol. 6 (7), 2011, e22843 
• Müller L., Kugler K., Graber A., Dehmer M.: A Network-Based Approach to Classify the Three Domains of Life, Biology Direct, Vol. 6 (53), 2011 
• Müller L., Kugler K., Graber A., Emmert-Streib F., Dehmer M.: Structural Measures for Network Biology Using QuACN, BMC Bioinformatics, Vol. 12 (492), 2011 
• Varmuza K., Dehmer M.: Classification of AMES mutagenicity from molecular descriptors – Applying D-PLS regression and repeated double cross validation, Asian Chemistry Letters, 2011, accepted 
• Balasubramanian R., Müller L., Kugler K., Hackl W., Pleyer L., Dehmer M., Graber A.: The Impact of Storage Effects in Biobanks on Biomarker Discovery in Systems Biology Studies, Biomarkers, Vol. 15 (8), 2010, 677-683 
• Dehmer M., Barbarini N., Varmuza K., Graber A.: Novel Topological Descriptors for Analyzing Biological Networks, BMC Structural Biology, Vol. 10 (18), 2010 
• Dehmer M., Müller L., Graber A.: New Polynomial-based Molecular Descriptors With Low Degeneracy, PLoS ONE, Vol. 5 (7), 2010, e11393 
• Dehmer M., Emmert-Streib F., Tsoy Y. R., Varmuza K.: Novel Information Measure for the Analysis of Chemical Graphs (in Russian), Bulletin of the Tomsk Polytechnic University, Vol. 316 (5), 2010, 5-11 15 
• Dehmer M., Popovscaia M.: Towards Structural Network Analysis, Buletinul Academiei de Stiinte a Republicii Moldova. Matematica, Vol. 1, 2010, 3-22 
• Dehmer M., Mowshowitz A.: Inequalities for Entropy-Based Measures of Network Information Content, Applied Mathematics and Computation, Vol. 215 (12), 2010, 4263-4271 
• Diudea M. V., Ili´c A., Varmuza K., Dehmer M.: Network Analysis Using a Novel Highly Discriminating Topological Index, Complexity, Vol. 16 (6), 2010, 32-39 
• Emmert-Streib F., Dehmer M.: Influence of the Time Scale on the Construction of Financial Networks, Complexity, PLoS ONE, Vol. 5 (9), 2010, e12884 
• Emmert-Streib F., Dehmer M.: Identifying Critical Financial Networks of the DJIA: Towards a Network based Index, Complexity, Vol. 16 (1), 2010, 24-33 
• Mowshowitz A., Dehmer M.: A Symmetry Index for Graphs, Symmetry: Culture and Science, Vol. 21 (4), 2010 
• Molina F., Dehmer M., Perco P., Graber A., Girolami 
• M., Spasovski G., Schanstra J. P., Vlahou A.: Systems Biology: Opening new avenues in clinical research, Nephrology Dialysis Transplantation, Vol 25 (4), 2015, 1015-1018 
• Müller L., Kugler K., Dander A., Graber A., Dehmer M.: QuACN – An R Package for Analyzing Complex Biological Networks Quantitatively, Bioinformatics, Vol.27 (1), 2010, 140-141 
• Borgert S., Dehmer M., Aitenbichler E.: On Quantitative Network Complexity Measures for Business Process Models, Acta Universitatis Apulensis, Vol. 18, 2009
• Dehmer M., Borgert S.: Information Measures to Characterize Weighted Chemical Structures, Acta Universitatis Apulensis, Vol. 18, 2009 
• Dehmer M., Barbarini N., Varmuza K., Graber A.: A Large Scale Analysis of Information- Theoretic Network Complexity Measures Using Chemical Structures, PLoS ONE, Vol. 4 (12), 2009, e8057 
• Dehmer M., Borgert S., Bonchev D.: Information Inequalities for Graphs, Symmetry: Culture and Science, Symmetry in Nanostructures, Vol. 19 (4), 2009 
• Dehmer M., Varmuza K., Borgert S., Emmert-Streib F.: On Entropy-based Molecular Descriptors: Statistical Analysis of Real and Synthetic Chemical Structures, Journal of Chemical Information and Modelling, Vol. 49, 2009, 1655-1663 
• Dehmer M., Borgert S.: Characterizing Classes of Structured Objects by Means of Information Inequalities, Cybernetics and Systems, Vol. 40 (3), 2009, 249-258 
• Emmert-Streib F., Dehmer M.: Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae, BMC Systems Biology, Vol. 3 (76), 2009 
• Emmert-Streib F., Dehmer M.: Predicting cell cycle regulated genes by causal interactions, PLoS ONE, Vol. 4 (8), e6633, 2009 
• Emmert-Streib F., Dehmer M.: Information Processing in the Transcriptional Regulatory Network of Yeast: Functional Robustness, BMC Systems Biology, Vol. 3 (35), 2009 
• Emmert-Streib F., Dehmer M.: Fault Tolerance of Information Processing in Gene Networks, Physica A, Vol. 338 (4), 2009, 541-548 
• Dehmer M., Emmert-Streib F: Structural Information Content of Networks: Graph Entropy based on Local Vertex Functionals, Computational Biology and Chemistry, Vol. 32, 2008, 131-138 
• Dehmer M., Emmert-Streib F: The Structural Information Content of Chemical Networks, Zeitschrift für Naturforschung A, Vol. 63a, 2008, 155-158 16 
• Dehmer M., Borgert S., Emmert-Streib F.: Entropy Bounds for Hierarchical Molecular Networks, PLoS ONE, Vol. 3 (8), 2008, e3079 
• Dehmer M.: Information-theoretic Concepts for the Analysis of Complex Networks, Applied Artificial Intelligence, Vol. 22, 2008, 684-706 
• Dehmer M.: Information Processing in Complex Networks: Graph Entropy and Information Functionals, Applied Mathematics and Computation, Vol. 201 (1-2), 2008, 82-94 
• Dehmer M.: A Novel Method for Measuring the Structural Information Content of Networks, Cybernetics and Systems, Vol. 39 (8), 2008, 825-842 
• Dehmer M., Emmert-Streib F., Gesell T.: A Comparative Analysis of Multidimensional Features of Objects Resembling Sets of Graphs, Applied Mathematics and Computation, Vol. 196 (1), 2008, 221-235 
• Emmert-Streib F., Dehmer M.: Robustness in Scale-free Networks: Comparing Directed and Undirected Networks, International Journal of Modern Physics C, Vol. 19 (5), 2008, 717-726 
• Dehmer M., Kilian J.: On Bounds for the Zeros of Univariate Polynomials, International Journal of Applied Mathematics and Computer Science, Vol. 4 (2), 2007, 118-123 
• Dehmer M., Emmert-Streib F.: Structural Similarity of Directed Universal Hierarchical Graphs: A low Computational Complexity Approach, Applied Mathematics and Computation, Vol. 194 (1), 2007, 7-20 
• Dehmer M., Mehler A.: A new Method of Measuring Similarity for a Special Class of Directed Graphs, Tatra Mountains Mathematical Publications, 2007, Vol. 36, 39-59 
• Dehmer M., Emmert-Streib F.: Comparing Large Graphs Efficiently by Margins of Feature Vectors, Applied Mathematics and Computation, Vol. 188 (2), 2007, 1699-1710 
• Emmert-Streib F., Dehmer M.: Nonlinear Time Series Prediction based on a Power-Law Noise Model, International Journal of Modern Physics C, Vol. 18 (12), 1839-1852, 2007 
• Emmert-Streib F., Dehmer M.: Information Theoretic Measures of UHG Graphs with Low Computational Complexity, Applied Mathematics and Computation, Vol. 190 (2), 2007, 1783-1794 
• Emmert-Streib F., Dehmer M.: Topological Mappings between Graphs, Trees and Generalized Trees, Applied Mathematics and Computation, Vol. 186 (2), 2007, 1326-1333 
• Dehmer M., Emmert-Streib F., Kilian J.: A Similarity Measure for Graphs with low Computational Complexity, Applied Mathematics and Computation, Vol. 182 (1), 2006, 447-459 
• Dehmer M., Emmert-Streib F., Wolkenhauer O.: Perspectives of Graph Mining Techniques, Rostocker Informatik Berichte, Vol. 30 (2), 2006, 47-57 
• Dehmer M.: On the Location of Zeros for complex Polynomials, Journal of Inequalities in Pure and Applied Mathematics, Vol. 7 (1), 2006 
• Dehmer M., Emmert-Streib F., Mehler A., Kilian J.: Measuring the Structural Similarity of Webbased Documents: A novel Approach, International Journal of Computational Intelligence, Vol. 3 (1), 2006, 1-7 
• Dehmer M.: Data Mining-Konzepte und graphentheoretische Methoden zur Analyse web-basierter Daten, Journal of Computational Linguistics and Language Technology, 2005, 113-143 
• Emmert-Streib F., Dehmer M., Liu J., Mühlhäuser M.: Ranking Genes from DNA Microarray Data of Cervical Cancer by a local Tree Comparison, International Journal of Biomedical Science, Vol. 1 (1), 2005, 17-22 17 Peer-Reviewed Conference Publications 
• Tripathi S., Strasser S., Mittermayr C., Dehmer M., Jodlbauer H., Approaches to Identify Relevant Process Variables in Injection Moulding using Beta Regression and SVM, In: Proceedings of the 8-th International Conference on Data Science, Technology and Applications, Prague, Czech Republic, 2019, 233-242 
• Dehmer M., Pickl S., Wang Z.: A Survey on Statistical Network Analysis, In: Proceedings of the 2015 Conference on Foundations in Computer Science, Las Vegas, USA, Vol. 2, 2015 
• Dehmer M., Lechleuthner A., Mudimu O. A., Pickl S.: Exploring Data Analysis Techniques for Threat Estimation, In: Proceedings of Future Security, Berlin, Germany, 2015 
• Dehmer M., Nistor M. S., Schmitz W., Neubecker K. A.: Aspects of Quantitative Analysis of Transportation Networks, In: Proceedings of Future Security, Berlin, Germany, 2015 
• Nistor M. S., Bein D., Bein W., Dehmer M., Pickl S.: Time-based estimation of vulnerable points in the munich subway network, In: Operations Research Proceedings, Springer, 2015, 355-360 
• Dehmer M., Holzinger A., Emmert-Streib F.: Personalized Medicine by Means of Complex Networks – A Big Data Challenge, In: Proceedings of Big Data, Editors: Weber R. H., Thouvenin F., Zürich 2014, Switzerland 
• Müller L. A. J., Kugler K. G., Dehmer M.: Structural Analysis of Molecular Networks: AMES Mutagenicity, In: Proceedings of the 2011 Conference on Bioinformatics & Computational Biology (BIOCOMP’11), Las Vegas, USA, Vol. 1, 2011, 196-201 
• Kugler K. G., Müller L. A. J., Dehmer M.: Analysis of Metabolic Networks: On the Similarity of the Three Domains of Life, In: Proceedings of the 2011 Conference on Bioinformatics & Computational Biology (BIOCOMP’11), Las Vegas, USA, Vol. 2, 2011, 361-366 
• Kugler G. G., Müller L. A. J., Gallasch R. K., Graber A., Dehmer M.: A Novel Majority Vote Count Algorithm for Integrative Analysis of Association Networks, In: Proceedings of the 2010 Conference on Bioinformatics & Computational Biology (BIOCOMP’10), Las Vegas, USA, 2010, 62-67 
• Müller L. A. J., Kugler G. G., Dander A., Graber A., Dehmer M.: A Network-based Approach to Classify Disease Stages of Prostate Cancer Using Quantitative Network Measures, In: Proceedings of the 2010 Conference on Bioinformatics & Computational Biology (BIOCOMP’10), Las Vegas, USA, 2010, 55-61 
• Borgert S., Dehmer M., Aitenbichler E.: A Comparative Study of Complexity Measure to Analyze Business Process Models, In: Proceedings of UICS’2009, International Symposium Understanding Intelligent and Complex Systems, 2009 
• Dehmer M., Borgert S.: On the Information Content of Weighted Chemical Structures, In: Proceedings of UICS’2009, International Symposium Understanding Intelligent and Complex Systems, 2009 
• Dehmer M., Emmert-Streib F.: Towards Network Complexity. In: Proceedings of COMPLEX’2009 – The First International Conference on Complex Sciences: Theory and Applications, Springer, Lecture Notes, Vol. 4, 2009, 707-714 
• Emmert-Streib F., Dehmer M.: Towards a Partitioning of the Input Space of Boolean Networks: Variable Selection using Bagging. In: Proceedings of COMPLEX’2009 – The First International Conference on Complex Sciences: Theory and Applications, Springer, Lecture Notes, Vol. 4, 2009, 715-723 
• Emmert-Streib F., Dehmer M.: Organizational Structure of the Transcriptional Regulatory Network of Yeast: Periodic Genes. In: Proceedings of COMPLEX’2009 – The First International Conference on Complex Sciences: Theory and Applications, Springer, Lecture Notes, Vol. 4 2009, 140-148 18 
• Dehmer M., Borgert S., Emmert-Streib F.: Network Classes and Graph Complexity Measures. In: Proceedings of CANS’2008 – Workshop on Complexity and Intelligence of Artificial and Natural Systems, IEEE Computer Society Press, Targu Mures, Romania, 2008 
• Dehmer M., Borgert S., Emmert-Streib F.: Investigating Network Classes by Measuring Their Complexity. In: Proceedings of CANS’2008 – Workshop on Complexity and Intelligence of Artificial and Natural Systems, Petru Maior University Press, Targu Mures, Romania, 2008 
• Dehmer M.: Relations Between the Topological Complexities of Complex Networks, In: Proceedings of the 2008 International Conference on Machine Learning: Models, Technologies & Applications (MLMTA’08), Las Vegas, USA, 2008 
• Emmert-Streib F., Dehmer M.: Towards a channel capacity of communication networks. In: Proceedings of the first International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems, Medical Applications of the Complex Systems, Biomedical Computing, IEEE Computer Society Press, Targu Mures, Romania, 2008 
• Emmert-Streib F., Dehmer M.: Quantifying Communication Capabilities of Networks. In: Proceedings of the first International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems, Medical Applications of the Complex Systems, Biomedical Computing, IEEE Computer Society Press, Targu Mures, Romania, 2008 
• Dehmer M., Mehler A., Emmert-Streib F.: Graph-theoretical Characterizations of Generalized Trees, Proceedings of the 2007 International Conference on Machine Learning: Models, Technologies & Applications (MLMTA’07), Las Vegas, USA, 2007 
• Dehmer M., Emmert-Streib F., Zulauf A.: A Graph Mining Technique for Automatic Classification ofWeb Genre Data, In: Proceedings of the 2007 International Conference on Machine Learning: Models, Technologies & Applications (MLMTA’07), Las Vegas, USA, 2007 
• Emmert-Streib F., Dehmer M.: Global information processing in gene networks: Fault Tolerance, In: Proceedings of the bio-inspired models of network, information, and computing systems, Bionetics 2007, 326-329 
• Emmert-Streib F., Dehmer M.: Optimization Procedure for Predicting Nonlinear Time Series based on a non-Gaussian Noise Model, MICAI 2007: Advances in Artificial Intelligence, Lecture Notes in Computes Science (LNCS), Lecture Notes in Artificial Intelligence, Vol. 4827, 2007, 540-549 
• Gleim R., Mehler A., Dehmer M., Pustylnikov O.: Aisles through the Category Forest – Utilising the Wikipedia Category System for Corpus Building in Machine Learning, Proceedings of the 3rd International Conference on Web Information Systems and Technologies (WEBIST ’07), 2007, 142-149 
• Emmert-Streib F., Dehmer M.: Theoretical Bounds for the Number of inferable Edges in sparse Random Networks, Proceedings of the 2006 International Conference on Bioinformatics & Computational Biology, Gene Networks: Theory and Application, Workshop at BIOCOMP’06, Las Vegas, USA, 2006, 472-476 
• Emmert-Streib F., Dehmer M., Seidel C.: Influence of Prior Information on the Reconstruction of the Yeast Cell Cycle from Microarray Data, Proceedings of the 2006 International Conference on Bioinformatics & Computational Biology, Gene Networks: Theory and Application, Workshop at BIOCOMP’06, Las Vegas, USA, 2006, 477-482 
• Gleim R., Mehler A., Dehmer M.: Web Corpus Mining by Instance of Wikipedia, Proceedings of the EACL 2006 Workshop on Web as Corpus, Trento, Italy, 2006, 67-74 
• Dehmer M., Emmert-Streib F., Kilian J., Zulauf A.: Towards Clustering of web-based Document Structures, VIII. International Conference on Enformatika, Systems Sciences and Engineering, Krakow, Poland, Enformatika 10, 2005, 304-310 19 
• Dehmer M., Emmert-Streib F., Mehler A., Kilian J., Mühlhäuser M.: Application of a Similarity Measure for Graphs to web-based Documents, VI. International Conference on Enformatika, Systems Sciences and Engineering, Budapest, Hungary, Enformatika 8, 2005, 77-81 
• Emmert-Streib F., Dehmer M.: First Studies of the Influence of Single Gene Perturbations on the Inference of Genetic Networks, VIII. International Conference on Enformatika, Systems Sciences and Engineering, Krakow, Poland, Enformatika 10, 2005, 65-69 
• Emmert-Streib F., Dehmer M., Bakir H.G., Mühlhäuser M.: Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series, VIII. International Conference on Enformatika, Systems Sciences and Engineering, Krakow, Poland, Enformatika 10, 2005, 70-74 
• Emmert-Streib F., Dehmer M., Liu J., Mühlhäuser M.: A Systems Approach to Gene Ranking for DNA Microarray Data for Cervical Cancer, VI. International Conference on Enformatika, Sciences and Engineering, Budapest, Hungary, Enformatika 8, 2005, 82-87 
• Emmert-Streib F., Dehmer M.: A Systems Biology approach for the classification of DNA Microarray Data, Applications of Statistical and Machine Learning. Methods in Bioinformatics, Proceedings of BIT 2005 – Bioinformatics Workshop,Torun, Poland, September 15-16, 2005 
• Emmert-Streib F., Dehmer M., Kilian J.: Classification of large Graphs by a local Graph Decomposition, Proceedings of the 2005 International Conference on Data Mining (DMIN’05), Las Vegas, USA, Editors: Arabnia H. R., Scime A., 2005, 200-207 
• Mehler A., Gleim R., Dehmer M.: Towards Structure-Sensitive Hypertext Categorization. In: Spiliopoulou M., Kruse R., Borgelt C., Nürnberger A., Gaul W. (Editors): Proceedings of the 29th Annual Conference of the German Classification Society, Universität Magdeburg, 2005, Berlin, New York: Springer, 406-413 
• Mehler A., Dehmer M., Gleim R.: Zur automatischen Klassifikation von Webgenres, In: Fisseni B., Schmitz H. C., Schröder B., Wagner P. (Editors): Sprachtechnologie, mobile Kommunikation und linguistische Ressourcen. Beiträge zur GLDV-Tagung 2005, Universität Bonn, Peter Lang Publishing, 158-174 
• Mehler A., Dehmer M., Gleim R.: Towards logical Hypertext Structure. A graph-theoretic Perspective, Proceedings of I2CS’04, Lecture Notes, Berlin, New York: Springer, 2005, 136-150 
• Dehmer M., Mehler A., Gleim R.: Aspekte der Kategorisierung von Webseiten, Lecture Notes in Computer Science, Springer, Jahrestagung der Gesellschaft für Informatik, Ulm, Germany, 2004, 39-43