Full Publication List of Matthias Dehmer

Theses

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

Books (Authored, Edited and Co-edited)

  1. Emmert-Streib F., Moutari S., Dehmer M.: Elements of Data Science, Machine Learning, and
    Artificial Intelligence Using R, Springer Publishing, Cham, Switzerland, 2023
  2. Emmert-Streib F., Moutari S., Dehmer M.: Mathematical Foundations of Data Science Using R,
    De Gruyter Oldenbourg, 2020
  3. Dehmer M., Emmert-Streib F., Jodlbauer H.: Entrepreneurial Complexity, CRC, 2019
  4. Chen Z., Dehmer M., Emmert-Streib F., Shi Y.: Modern and Interdisciplinary Problems in Network Science: A Translational Research Perspective, CRC, 2018
  5. Dehmer M., Emmert-Streib F.: Frontiers in Data Science, CRC, 2017
  6. Shi Y., Dehmer M., Li X., Gutman I.: Graph Polynomials (Discrete Mathematics and Its Applications), CRC, 2016
  7. Dehmer M., Shi Y., Emmert-Streib F.: Computational Network Analysis with R: Applications in
    Biology, Medicine and Chemistry, Wiley-Blackwell, 2016
  8. Dehmer M., Chen Z., Li X., Shi Y.: Mathematical Foundations and Applications of Graph Entropy,
    Wiley-Blackwell, 2016
  9. Dehmer M., Emmert-Streib F., Holzinger A., Pickl S.: Big Data of Complex Networks, CRC, 2016
  10. Dehmer M., Emmert-Streib F., Pickl S.: Computational Network Theory, Wiley-Blackwell, 2015
  11. Dehmer M., Emmert-Streib F.: Quantitative Graph Theory: Mathematical Foundations and Applications, CRC Press, 2014
  12. Dehmer M., Mowshowitz A., Emmert-Streib F.: Advances in Network Complexity, Wiley-Blackwell,
    2013
  13. Emmert-Streib F., Dehmer M.: Statistical Diagnostics for Cancer: Analyzing High-Dimensional
    Data, Wiley-Blackwell, 2013
  14. Dehmer M., Varmuza K., Bonchev D.: Statistical Modelling of Molecular Descriptors in QSAR/QSPR,
    Wiley-Blackwell, 2012
  15. Dehmer M., Basak S. C.: Statistical and Machine Learning Approaches for Network Analysis,
    Wiley Series in Computational Statistics, Wiley, 2012
  16. Dehmer M., Emmert-Streib F., Mehler A.: Towards an Information Theory of Complex Networks:
    Statistical Methods and Applications, Birkhäuser Publishing, 2011
  17. Dehmer M., Emmert-Streib F., Graber A., Salvador A.: Applied Statistics for Network Biology:
    Methods in Systems Biology, Wiley-VCH, 2011
  18. Dehmer M.: Structural Analysis of Complex Networks, Birkhäuser Publishing, 2010
  19. Dehmer M., Emmert-Streib F.: Analysis of Complex Networks: From Biology to Linguistics,
    Wiley-VCH Publishing, 2009
  20. Dehmer M., Drmota M., Emmert-Streib F.: Proceedings of the 2008 International Conference
    on Information Theory and Statistical Learning (ITSL’08), CSREA Press, 2008
  21. Emmert-Streib F., Dehmer M.: Medical Biostatistics for Complex Diseases, Wiley-VCH Publishing, 2010
  22. Emmert-Streib F., Dehmer M.: Analysis of Microarray Data: A Network-based Approach, WileyVCH Publishing, 2008
  23. Emmert-Streib F., Dehmer M.: Information Theory and Statistical Learning, Springer, 2008
  24. 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)

  1. 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
  2. Arabnia H. R. et al.: Proceedings of the 2007 International Conference on Artificial Intelligence
    (ICAI’07), Dehmer M., (Associate Editor), CSREA Press, 2007
  3. Arabnia H. R. et al.: Proceedings of the 2007 International Conference on Scientific Computing
    (CSC’07), Dehmer M., (Associate Editor), CSREA Press, 2007
  4. 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
  5. 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)

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

Book Chapter

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. Holzinger, A., Ofner B, Stocker, C., Valdez A. C., Schaar A. K., Ziefle M., Dehmer, M.: On Graph Entropy 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 (Lecture Notes in Computer Science), Springer, Vol. 8127, 2013, 354-362
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. Gutman I., Zhang Y., Dehmer M., Ilic A.: Altenburg, Wiener, and Hosoya Polynomials. In: Gutman I., Furtula B. (Editors): Distance in Molecular Graphs – Theory, Mathematical Chemistry Monographs, 2011, 49-70
  16. 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
  17. 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
  18. 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

  1. Emmert-Streib F., Tripathi S., Dehmer M.: Human team behavior and predictability in the mas-sively multiplayer online game WOT Blitz, ACM Transactions on the Web, Vol. 18 (1), 2023, 1-27
  2. 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
  3. Emmert-Streib F., Tripathi S., Dehmer M.: Analyzing the scholarly literature of digital twin re-search: Trends, topics and structure, IEEE Access, Vol. 11, 2023
  4. 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
  5. Lotfi A., Mowshowitz A., Dehmer M., A Note on Eigenvalues and Asymmetric Graphs, Axioms, Vol. 12 (6), 510, 2023
  6. Brezovnik S., Dehmer M., Tratnik N., Žigert-Pleteršek P.: Szeged and Mostar root-indices of graphs, Applied Mathematics and Computation, Vol. 442, 127736, 2023
  7. Cai J., Li W., Cai W., Dehmer M.: List injective coloring of planar graphs, Applied Mathematics and Computation, Vol. 439, 127631, 2023
  8. 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
  9. Brezovnik S., Dehmer M., Tratnik N., Žigert-Pleteršek P.: Szeged-like entropies of graphs, Ap-plied Mathematics and Computation, Vol. 431, 127325, 2022
  10. Emmert-Streib M., Dehmer M.: Taxonomy of machine learning paradigms: A data-centric per-spective, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery Vol. 12 (5), 2022
  11. Ma Y., Dehmer M., Künzi U. M., Tripathi S., Ghorbani M., Tao J., Emmert-Streib F.: The useful-ness of topological indices, Information Sciences, Vol. 606, 143-151, 2022
  12. 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
  13. 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
  14. 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
  15. 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, 528, 2022
  16. 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
  17. 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
  18. 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
  19. 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
  20. Maddah S., Ghorbani M., Dehmer M.: New results of identifying codes in product graphs, Ap-plied Mathematics and Computation, Vol. 410, 126438, 2021
  21. Ghorbani M., Dehmer M., Lotfi A., Amraei N., Mowshowitz A., Emmert-Streib F.: On the rela-tionship between PageRank and automorphisms of a graph, Information Sciences, Vol. 579, 401-417, 2021
  22. 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
  23. 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
  24. 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
  25. Zhu H., Sun Q., Tao J., Tan P., Chen Z., Dehmer M., Xie G.: Fluid-Structure Interaction Simu-lation and Accurate Dynamic Modeling of Parachute Warhead System Based on Impact Point Prediction, IEEE Access, Vol. 9, 104418-104428, 2021
  26. 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
  27. Zhuang H., Sun Q., Chen Z., Dehmer M.: Sliding Mode Robust Control for Maximum Allow-able Vertical Tail Damage to Aircraft Based on Linear Matrix Inequality, Journal of Aerospace Engineering, Vol. 34 (4), 05021001, 2021
  28. Tripathi S., Muhr D., Brunner M., Jodlbauer H., Dehmer M., Emmert-Streib F.: Ensuring the Ro-bustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manu-facturing, Frontiers in Artificial Intelligence, Vol. 22 (3), 2021
  29. Ghorbani M., Dehmer M.: On the Roots of the Modified Orbit Polynomial of a Graph, Symmetry, Vol. 13 (6), 972, 2021
  30. Ghorbani M., Dehmer M.: Network Analyzing by the Aid of Orbit Polynomial, Symmetry, Vol. 13 (5), 801, 2021
  31. 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
  32. Ghorbani M., Jalali-Rad M., Dehmer M.: Orbit polynomial of graphs versus polynomial with integer coefficients, Symmetry, Vol. 13 (4), 710, 2021
  33. 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
  34. Emmert-Streib F., Manjang K., Dehmer M., Yli-Harja O., Auvinen A.: Are There Limits in Ex-plainability of Prognostic Biomarkers? Scrutinizing Biological Utility of Established Signatures, Cancers, Vol. 13 (20), 5087, 2021
  35. Zheng Y., Tao J., Sun H., Sun Q., Chen Z., Dehmer M., Zhou Q.: Load frequency active distur-bance rejection control for multi-source power system based on soft actor-critic, Energies, Vol. 14 (16), 4804, 2021
  36. Manjang K., Yli-Harja O., Dehmer M., Emmert-Streib F.: Limitations of explainability for estab-lished prognostic biomarkers of prostate cancer, Frontiers in Genetics, Vol. 12, 649429, 2021
  37. 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
  38. 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
  39. Cheng T., Dehmer M., Emmert-Streib F., Li Y., Liu W., Properties of Commuting Graphs over Semidihedral Groups, Symmetry, Vol. 13 (1), 2021
  40. 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
  41. Dehmer M., Emmert-Streib F., Mowshowitz M., Ilic´ 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
  42. 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
  43. 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
  44. Ghorbani M., Dehmer M., Emmert-Streib F.: On the Degeneracy of the Orbit Polynomial and Related Graph Polynomials Symmetry, Vol. 12 (10), 2020
  45. 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
  46. 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
  47. Ghorbani M., Dehmer M., Emmert-Streib F.: Properties of Entropy-Based Topological Measures of Fullerenes, Mathematics Vol. 8 (5), 740, 2020
  48. 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
  49. 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
  50. Li J., Park J.H., Zhang J., Chen Z., Dehmer M.: The networked cooperative dynamics of adjust-ing signal strength based on information quantity, Nonlinear Dynamics, 1=17, 2020
  51. Ghorbani M., Dehmer M., Rahmani S., Rajabi-Parsa M.: A Survey on Symmetry Group of Poly-hedral Graphs, Symmetry, Vol. 12 (3), 2020,
  52. 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
  53. 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
  54. Yang Z., Dehmer M., Yli-Harja O., Emmert-Streib F.: Combining deep learning with token selec-tion for patient phenotyping from electronic health records, Scientific Reports, Vol. 10 (1), 1-18, 2020
  55. 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
  56. 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
  57. 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
  58. 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, Infor-mation Science, Vol. 471, 19-28, 2019
  59. Dehmer. M., Chen Z., Mowshowitz A., Jodlbauer H., Emmert-Streib F., Shi Y., Tripathi S., Xia C.: On the Degeneracy of the Randic´ Entropy and Related Graph Measures, Information Sciences, Vol. 501, 2019, 680-687
  60. 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
  61. 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
  62. 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
  63. Emmert-Streib F., Dehmer M.: Introduction to Survival Analysis in Practice, Machine Learning and Knowledge Extraction Vol. 1 (3), 2019, 1013-1038
  64. Emmert-Streib F., Dehmer M.: Understanding Statistical Hypothesis Testing: The Logic of Sta-tistical Inference, Machine Learning and Knowledge Extraction Vol. 1 (3), 2019, 945-961
  65. 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
  66. 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
  67. 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 Trans-actions, 2019
  68. 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
  69. Yu G., Dehmer M., Emmert-Streib F., Jodlbauer H.: Hermitian Normalized Laplacian Matrix for Directed Networks, Information Sciences, Vol. 495, 175-184, 2019
  70. 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
  71. Mowshowitz A., Dehmer, M., Emmert-Streib F.: A Note on Graphs with Prescribed Orbit Struc-ture, Entropy, Vol. 21 (11), 2019, 1118
  72. Ghorbani M., Dehmer M., Mowshowitz A., Tao J., Emmert-Streib F.: The Hosoya entropy of graphs revisited, Symmetry, Vol. 11 (8), 2019, 1013
  73. Ghorbani M., Dehmer M., Zangi S., Mowshowitz A., Emmert-Streib F.: A Note on Distance-Based Entropy of Dendrimers, Axioms, Vol. 8 (3), 2019
  74. 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
  75. 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
  76. 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
  77. 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
  78. 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
  79. Emmert-Streib F., Moutari S., Dehmer M.: A comprehensive survey of error measures for evalu-ating binary decision making in data science, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1303, 2019
  80. Emmert-Streib F., Dehmer M.: A machine learning perspective on Personalized Medicine: An automized, comprehensive knowledge base with ontology for pattern recognition, Machine Learn-ing and Knowledge Extraction, Vol. 1 (1), 2019 149-156
  81. 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
  82. Emmert-Streib F., Shailesh Tripathi S., Dehmer M,: Constrained Covariance Matrices With a Bi-ologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaus-sian Graphical Models, Frontiers in Applied Mathematics and Statistics, Vol. 5 (17), 2019
  83. Emmert-Streib F., Dehmer M.: Network Science: From Chemistry to Digital Society. Frontiers for Young Minds, Vol. 7 (49), 2019
  84. 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
  85. Emmert-Streib F., Dehmer M.: Inference of Genome-Scale Gene Regulatory Networks: Are There Differences in Biological and Clinical Validations? Machine Learning & Knowledge Ex-traction, Vol. 1 (1), 2019, 138-148
  86. 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
  87. 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
  88. Ghorbani M., Taghvayi V., Dehmer M., Emmert-Streib F.: A graph-theoretic approach to con-struct desired cryptographic Boolean functions, Axioms, Vol. 8 (2), 2019
  89. 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
  90. 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
  91. 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
  92. 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
  93. Musa A., Tripathi S., Dehmer M., Yli-Harja O., Kauffman S. A, Emmert-Streib F.: Systems phar-macogenomic Landscape of Drug similarities from LINCs data: Drug Association Networks, Scientific Reports, Vol. 9 (1), 2019, 7849
  94. 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
  95. Stevanovic´ S., Stevanovic´ D., Dehmer M.: On optimal and near-optimal shapes of external shading of windows in apartment buildings, PLoS ONE, Vol. 14 (2), 2019, e0212710
  96. 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
  97. 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
  98. 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
  99. Xia C., Wang Z., Zheng C., Guo Q., Shi Y., Dehmer M., Chen Z.: A new coupled disease-awareness spreading model with mass media on multiplex networks, Information Sciences, Vol. 471, 2019, 185-200
  100. Ghorbani M., Dehmer M., Zangi S.: Graph Operations based on Using Distance-based Graph Entropies, Applied Mathematics and Computation, Vol. 333, 2018, 547-555
  101. 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
  102. 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
  103. 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
  104. Emmert-Streib F., Musa A., Tripathi S., Kandhavelu M., Dehmer M.: Harnessing the biologi-cal complexity of Big Data from LINCS Gene Expression Signatures, PLoS ONE, Vol. 13 (8), e0201937, 2018
  105. 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
  106. 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
  107. 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
  108. 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
  109. Dehmer M., Chen Z., Emmert-Streib F., Shi Y., Shailesh T.: Graph measures with high discrim-ination power revisited: A random polynomial approach, Information Science, Vol. 467, 2018, 407-414
  110. 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
  111. 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
  112. 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
  113. 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
  114. Mowshowitz A., Dehmer M.: A Calculus for Measuring the Elegance of Abstract Graphs, Applied Mathematics and Computation, Vol. 320, 2018, 142-148
  115. 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
  116. Chen Z., Dehmer M., Emmert-Streib F., Mowshowitz A., Shi Y.: Toward Measuring Network Aesthetics Based on Symmetry, Axioms, Vol. 6 (12), 2017
  117. Cao S., Dehmer M., Kang Z.: Network Entropies Based on Independent Sets and Matchings, Applied Mathematics and Computation, Vol. 307, 2017, 265-270
  118. 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
  119. Dehmer M., Emmert-Streib F., Hu B., Shi Y., Stefu M., Tripathi S.: Highly unique network de-scriptors based on the roots of the permanental polynomial, Information Sciences, Vol. 408, 2017, 176-181
  120. 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
  121. 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
  122. 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 pharmacoge-nomics, Briefings in Bioinformatics, 2017, 1-18
  123. 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
  124. 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
  125. Xu C., Li. G., Zhang Y., Gutman I., Dehmer M.: Prediction of therapeutic peptides by incorpo-rating q-Wiener index into Chou’s general PseAAC, Journal of Biomedical Informatics, Vol. 75, 2017, 63-69
  126. Yu L., Zhang Y., Gutman I., Shi Y., Dehmer M.: Protein Sequence Comparison Based on Physic-ochemical Properties and Position-Feature Energy Matrix, Scientific Reports, Vol. 7 (46237), 2017
  127. 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
  128. Das K. Ch., Dehmer M., A Conjecture Regarding the Extremal Values of Graph Entropy Based on Degree Powers, Entropy, Vol. 18 (183), 2016
  129. Das K. Ch., Dehmer M., Comparison between the zeroth-order Randic´ index and the sum-connectivity index, Applied Mathematics and Computation, Vol. 266, 2016, 1027-1030
  130. 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
  131. 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)
  132. 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
  133. 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
  134. 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
  135. Tripathi S., Moutari S., Dehmer M., Emmert-Streib M.: Comparison of module detection algo-rithms in protein networks and investigation of the biological meaning of predicted modules, Bioinformatics, 2016, Vol. 17 (129)
  136. Cao S., Dehmer M.: Degree-Based Entropies of Networks Revisited, Applied Mathematics and Computation, Vol. 261, 2015, 141-147
  137. Chen Z., Dehmer M., Shi Y.: Bounds for degree-based Network Entropies, Applied Mathematics and Computation, Vol. 265, 2015, 983-993
  138. Chen Z., Dehmer M., Emmert-Streib F., Shi Y.: Entropy of Weighted Graphs with Randic´ Weights, Entropy, Vol. 17 (6), 2015, 3710-3723
  139. Dehmer M., Li X., Shi Y.: Connections Between Generalized Graph Entropies and Graph Energy, Complexity, Vol. 21, 2015, 35-41
  140. Dehmer M., Emmert-Streib F., Shi Y., Stefu M., Tripathi S.: Discrimination Power of Polynomial-based Descriptors for Graphs by Using Functional Matrices, PLoS ONE, Vol. 10 (10), 2015, e0139265
  141. Dehmer M., Shi Y.: A Method for Inferring Inequalities for Probability Values Applied to Complex Networks, Complexity, Vol. 21 (51), 2015, 113-115
  142. Dehmer M., Meyer-Nieberg S., Mihelcic G., Pickl S., Zsifkovits M.: Collaborative Risk Manage-ment for National Security and Strategic Foresight, EURO Journal on Decision Processes, Vol. 3 (3), 2015, 305-337
  143. Dehmer M., Moosbrugger M., Shi Y.: Encoding Structural Information Uniquely With Polynomial-based Descriptors by Employing The Randic´ Matrix, Applied Mathematics and Computation, Vol. 268, 2015, 164-168
  144. Dehmer M., Emmert-Streib F., Shi Y.: Graph Distance Measures Based on Topological Indices Revisited, Applied Mathematics and Computation, Vol. 266, 2015, 623-633
  145. 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
  146. Dehmer M., Varmuza K.: A Comparative Analysis of the Tanimoto Index and Graph Edit Dis-tance for Measuring the Topological Similarity of Trees, Applied Mathematics and Computation, Vol. 259, 2015, 242-250
  147. 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
  148. Emmert-Streib F., Dehmer M.: Biological networks: The microscope of the 21st century, Fron-tiers in Genetics, Vol. 6 (307), 2015
  149. 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
  150. Ilic´ A., Dehmer M.: On the Distance Based Graph Entropies, Applied Mathematics and Compu-tation, Vol. 269, 2015, 647-650
  151. Mowshowitz A., Dehmer M.: The Hosoya entropy of a graph, Entropy, Vol. 17 (3), 2015, 1054-1062
  152. Nistor, M. S., Dehmer, M., Pickl, S., Network Exploratory Analysis on Subway Transportation Systems against Complex Threats Including a Human Factors Perspective. Procedia Manufac-turing, Vol. 3, 2015, 6593-6598
  153. 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
  154. Cao S., Dehmer M., Shi Y.: Extremality of Degree-Based Graph Entropies, Information Sci-ences, Vol. 278, 2014, 22-33
  155. Chen Z., Dehmer M., Emmert-Streib F., Shi Y.: Entropy Bounds for Dendrimers, Applied Mathe-matics and Computation, Vol. 242, 2014, 462-472
  156. Chen Z., Dehmer M., Shi Y.: A Note on Distance-based Graph Entropies, Entropy, Vol. 16 (10), 2014, 5416-5427
  157. Dehmer M., Tsoy Y. R.: Numerical Evaluation and Comparison of Kalantari’s Zero Bounds for Complex Polynomials, PLoS ONE, Vol. 9 (10), 2014, e110540.
  158. Dehmer M., Mowshowitz A., Shi Y.: Structural Differentiation of Graphs using Hosoya-based Indices, PLoS ONE, 2014, Vol. 9 (7), e102459
  159. Dehmer M., Emmert-Streib F., Grabner M.: A Computational Approach to Construct a Multivari-ate Complete Graph Invariant, Information Sciences, Vol. 260 (1), 2014, 200-208
  160. Dehmer M., Shi Y.: The Uniqueness of DMAX-Matrix Graph Invariants, PLoS ONE, Vol. 9 (1), 2014, e83868
  161. Dehmer M., Emmert-Streib F., Shi Y.: Interrelations of Graph Distance Measure Based on Topo-logical Indices, PLoS ONE, Vol. 9 (4), 2014, e94985
  162. Emmert-Streib F., Dehmer M., Haibe-Kains B.: Gene regulatory networks and their applica-tions: Understanding biological and medical problems in terms of networks, Frontiers in Cell and Developmental Biology, Vol. 2, Article 38, 2014
  163. 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
  164. Emmert-Streib F., de Matos Simoes R., Mullan P., Haibe-Kains B., Dehmer M.: The gene regu-latory network for breast cancer: Integrated regulatory landscape of cancer hallmarks, Frontiers in Genetics, Vol. 15 (5), 2014
  165. 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
  166. Holzinger A., Dehmer M., Jurisica I., Knowledge Discovery and Interactive Data Mining in Bioin-formatics – State-of-the-Art, Future challenges and Research Directions, BMC Bioinformatics, Vol. 15 (Suppl 6:I1), 2014
  167. Kraus V., Dehmer M., Emmert-Sreib F.: Probabilistic Inequalities for Evaluating Structural Net-work Measures, Information Sciences, Vol. 288, 2014, 220-245
  168. Schutte M., Dehmer M.: Large-Scale Analysis of Structural Branching Measures, Journal of Mathematical Chemistry, Vol. 52 (3), 2014, 805-819
  169. 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
  170. 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
  171. Dehmer M., Emmert-Streib F., Tripathi S.: Large-Scale Evaluation of Molecular Descriptors by Means of Clustering, PLoS ONE, Vol. 8 (12), 2013, e83956
  172. 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
  173. Dehmer M., Mowshowitz A.: The Discrimination Power of Structural SuperIndices, PLoS ONE, Vol. 8 (7), 2013, e70551
  174. 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
  175. 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
  176. Dehmer M., Grabner M.: The Discrimination Power of Molecular Identification Numbers Revis-ited, MATCH Commun. Math. Comput. Chem., Vol. 69 (3), 2013, 785-794
  177. 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
  178. 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
  179. 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 Compu-tational Biology, Vol. 4, Article 241, 2013
  180. Emmert-Streib F., Dehmer M., Lyardet F.: Learning Systems Biology: Conceptual Considera-tions Toward a Web-based Learning Platform, Education Sciences, Vol. 3 (2) 2013, 158-171
  181. Emmert-Streib F., Tripathi S., de Matos Simoes R., Hawwa A. F., Dehmer M.: The human dis-ease network. Opportunities for classification, diagnosis and prediction of disorders and disease genes, Systems Biomedicine, Vol. 1 (1), 2013, 1-8
  182. Furtula B., Gutman I., Dehmer M.: On Structure-Sensitivity of Degree-Based Topological In-dices, Applied Mathematics and Computation, Vol. 219, 2013, 8973-8978
  183. 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
  184. Varmuza K., Filzmoser P., Dehmer M.: Multivariate linear QSPR/QSAR models: Rigorous eval-uation of variable selection for PLS, Computational and Structural Biotechnology Journal, Vol. 5 (6), e201302007, 2013, 1-10
  185. Dehmer M., Kraus V.: On Extremal Properties of Graph Entropies, MATCH Commun. Math. Comput. Chem., Vol. 68 (3), 2012, 889-912
  186. Dehmer M., Tsoy Y. R.: The Quality of Zero Bounds for Complex Polynomials, PLoS ONE, Vol. 7 (7), 2012, e39537
  187. 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
  188. Dehmer M., Grabner M., Varmuza K.: Information Indices with High Discriminative Power for Graphs, PLoS ONE, Vol. 7 (2), 2012, e31214
  189. Dehmer M., Ilic´ A.: Location of Zeros of Wiener and Distance Polynomials, PLoS ONE, Vol. 7 (3), 2012, e28328
  190. Dehmer M., Sivakumar L.: Recent Developments in Quantitative Graph Theory: Information Inequalities for Networks, PLoS ONE, Vol. 7 (2), 2012, e31395
  191. 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
  192. Emmert-Streib F., de Matos Simoes R., Tripathi S., Glazko G. V., Dehmer M.: A Bayesian anal-ysis of the chromosome architecture of human disorders by integrating reductionist data, Scien-tific Reports (Nature Publishing), Vol. 2, 2012
  193. Emmert-Streib F., Dehmer M.: Exploring statistical and population aspects of network complex-ity, PLoS ONE 7(5), 2012, e34523
  194. 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
  195. Kusonmano K., Kugler K., Graber A., Emmert-Streib F., Dehmer M.: Effects of pooling sam-ples on the performance of classification algorithms: A comparative study, The Scientific World Journal, Vol. 12, 2012
  196. Mowshowitz A., Dehmer M.: Entropy and the Complexity of Graphs Revisited, Entropy, Vol. 14 (3), 2012, 559-570
  197. 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
  198. Sivakumar L., Dehmer M.: Towards Information Inequalities for Generalized Graph Entropies, PLoS ONE, Vol. 7 (6), 2012, e38159
  199. 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
  200. Dehmer M.: Information Theory of Networks, Symmetry, Vol. 3 (4), 2011, 767-779
  201. Dehmer M.: Inclusion Radii for the Zeros of Special Polynomials, Buletinul Academiei de Stiinte a Republicii Moldova. Matematica, Vol. 3 (67), 2011, 84-90
  202. Dehmer M., Mowshowitz A.: Bounds on the Moduli of Polynomial Zeros, Applied Mathematics and Computation, Vol. 218 (8), 2011, 4128-4137
  203. Dehmer M., Mowshowitz A.: Generalized Graph Entropies, Complexity, Vol. 17 (2), 2011, 45-50
  204. Dehmer M., Mowshowitz A., Emmert-Streib F.: Connections between Classical and Parametric Network Entropies, PLoS ONE, Vol. 6 (1), 2011, e15733
  205. Dehmer M., Mowshowitz A.: A History of Graph Entropy Measures, Information Sciences, Vol. 1 (1), 2011, 57-78
  206. Emmert-Streib F., Dehmer M.: Networks for Systems Biology: Conceptual Connection of Data and Function, IET Systems Biology, Vol. 5 (3), 2011, 185-207
  207. Kugler K., Müller L., Graber A., Dehmer M.: Graph Prototyping for Co-Expression Cancer Net-works, PLoS ONE Vol. 6 (7), 2011, e22843
  208. 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
  209. Müller L., Kugler K., Graber A., Emmert-Streib F., Dehmer M.: Structural Measures for Network Biology Using QuACN, BMC Bioinformatics, Vol. 12 (492), 2011
  210. Varmuza K., Dehmer M.: Classification of AMES mutagenicity from molecular descriptors – Ap-plying D-PLS regression and repeated double cross validation, Asian Chemistry Letters, 2011, accepted
  211. 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
  212. Dehmer M., Barbarini N., Varmuza K., Graber A.: Novel Topological Descriptors for Analyzing Biological Networks, BMC Structural Biology, Vol. 10 (18), 2010
  213. Dehmer M., Müller L., Graber A.: New Polynomial-based Molecular Descriptors With Low De-generacy, PLoS ONE, Vol. 5 (7), 2010, e11393
  214. Dehmer M., Emmert-Streib F., Tsoy Y. R., Varmuza K.: Novel Information Measure for the Anal-ysis of Chemical Graphs (in Russian), Bulletin of the Tomsk Polytechnic University, Vol. 316 (5), 2010, 5-11
  215. Dehmer M., Popovscaia M.: Towards Structural Network Analysis, Buletinul Academiei de Stiinte a Republicii Moldova. Matematica, Vol. 1, 2010, 3-22
  216. Dehmer M., Mowshowitz A.: Inequalities for Entropy-Based Measures of Network Information Content, Applied Mathematics and Computation, Vol. 215 (12), 2010, 4263-4271
  217. Diudea M. V., Ilic´ A., Varmuza K., Dehmer M.: Network Analysis Using a Novel Highly Discrimi-nating Topological Index, Complexity, Vol. 16 (6), 2010, 32-39
  218. Emmert-Streib F., Dehmer M.: Influence of the Time Scale on the Construction of Financial Networks, Complexity, PLoS ONE, Vol. 5 (9), 2010, e12884
  219. Emmert-Streib F., Dehmer M.: Identifying Critical Financial Networks of the DJIA: Towards a Network based Index, Complexity, Vol. 16 (1), 2010, 24-33
  220. Mowshowitz A., Dehmer M.: A Symmetry Index for Graphs, Symmetry: Culture and Science, Vol. 21 (4), 2010
  221. 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 Transplan-tation, Vol 25 (4), 2015, 1015-1018
  222. 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
  223. Borgert S., Dehmer M., Aitenbichler E.: On Quantitative Network Complexity Measures for Busi-ness Process Models, Acta Universitatis Apulensis, Vol. 18, 2009
  224. Dehmer M., Borgert S.: Information Measures to Characterize Weighted Chemical Structures, Acta Universitatis Apulensis, Vol. 18, 2009
  225. 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
  226. Dehmer M., Borgert S., Bonchev D.: Information Inequalities for Graphs, Symmetry: Culture and Science, Symmetry in Nanostructures, Vol. 19 (4), 2009
  227. Dehmer M., Varmuza K., Borgert S., Emmert-Streib F.: On Entropy-based Molecular Descrip-tors: Statistical Analysis of Real and Synthetic Chemical Structures, Journal of Chemical Infor-mation and Modelling, Vol. 49, 2009, 1655-1663
  228. Dehmer M., Borgert S.: Characterizing Classes of Structured Objects by Means of Information Inequalities, Cybernetics and Systems, Vol. 40 (3), 2009, 249-258
  229. Emmert-Streib F., Dehmer M.: Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae, BMC Systems Biology, Vol. 3 (76), 2009
  230. Emmert-Streib F., Dehmer M.: Predicting cell cycle regulated genes by causal interactions, PLoS ONE, Vol. 4 (8), e6633, 2009
  231. Emmert-Streib F., Dehmer M.: Information Processing in the Transcriptional Regulatory Network of Yeast: Functional Robustness, BMC Systems Biology, Vol. 3 (35), 2009
  232. Emmert-Streib F., Dehmer M.: Fault Tolerance of Information Processing in Gene Networks, Physica A, Vol. 338 (4), 2009, 541-548
  233. 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
  234. Dehmer M., Emmert-Streib F: The Structural Information Content of Chemical Networks, Zeitschrift für Naturforschung A, Vol. 63a, 2008, 155-158
  235. Dehmer M., Borgert S., Emmert-Streib F.: Entropy Bounds for Hierarchical Molecular Networks, PLoS ONE, Vol. 3 (8), 2008, e3079
  236. Dehmer M.: Information-theoretic Concepts for the Analysis of Complex Networks, Applied Arti-ficial Intelligence, Vol. 22, 2008, 684-706
  237. Dehmer M.: Information Processing in Complex Networks: Graph Entropy and Information Functionals, Applied Mathematics and Computation, Vol. 201 (1-2), 2008, 82-94
  238. Dehmer M.: A Novel Method for Measuring the Structural Information Content of Networks, Cybernetics and Systems, Vol. 39 (8), 2008, 825-842
  239. 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
  240. 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
  241. 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
  242. 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
  243. 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
  244. Dehmer M., Emmert-Streib F.: Comparing Large Graphs Efficiently by Margins of Feature Vec-tors, Applied Mathematics and Computation, Vol. 188 (2), 2007, 1699-1710
  245. 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
  246. Emmert-Streib F., Dehmer M.: Information Theoretic Measures of UHG Graphs with Low Com-putational Complexity, Applied Mathematics and Computation, Vol. 190 (2), 2007, 1783-1794
  247. Emmert-Streib F., Dehmer M.: Topological Mappings between Graphs, Trees and Generalized Trees, Applied Mathematics and Computation, Vol. 186 (2), 2007, 1326-1333
  248. 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
  249. Dehmer M., Emmert-Streib F., Wolkenhauer O.: Perspectives of Graph Mining Techniques, Ro-stocker Informatik Berichte, Vol. 30 (2), 2006, 47-57
  250. Dehmer M.: On the Location of Zeros for complex Polynomials, Journal of Inequalities in Pure and Applied Mathematics, Vol. 7 (1), 2006
  251. Dehmer M., Emmert-Streib F., Mehler A., Kilian J.: Measuring the Structural Similarity of Web-based Documents: A novel Approach, International Journal of Computational Intelligence, Vol. 3 (1), 2006, 1-7
  252. Dehmer M.: Data Mining-Konzepte und graphentheoretische Methoden zur Analyse web-basierter Daten, Journal of Computational Linguistics and Language Technology, 2005, 113-143
  253. 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

Peer-Reviewed Conference Publications

  1. Tripathi S., Strasser S., Mittermayr C., Dehmer M., Jodlbauer H., Approaches to Identify Rele-vant 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
  2. 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
  3. Dehmer M., Lechleuthner A., Mudimu O. A., Pickl S.: Exploring Data Analysis Techniques for Threat Estimation, In: Proceedings of Future Security, Berlin, Germany, 2015
  4. 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
  5. 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
  6. Dehmer M., Holzinger A., Emmert-Streib F.: Personalized Medicine by Means of Complex Net-works – A Big Data Challenge, In: Proceedings of Big Data, Editors: Weber R. H., Thouvenin F., Zürich 2014, Switzerland
  7. Müller L. A. J., Kugler K. G., Dehmer M.: Structural Analysis of Molecular Networks: AMES Mu-tagenicity, In: Proceedings of the 2011 Conference on Bioinformatics & Computational Biology (BIOCOMP’11), Las Vegas, USA, Vol. 1, 2011, 196-201
  8. 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
  9. 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
  10. 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: Pro-ceedings of the 2010 Conference on Bioinformatics & Computational Biology (BIOCOMP’10), Las Vegas, USA, 2010, 55-61
  11. Borgert S., Dehmer M., Aitenbichler E.: A Comparative Study of Complexity Measure to Ana-lyze Business Process Models, In: Proceedings of UICS’2009, International Symposium Under-standing Intelligent and Complex Systems, 2009
  12. Dehmer M., Borgert S.: On the Information Content of Weighted Chemical Structures, In: Pro-ceedings of UICS’2009, International Symposium Understanding Intelligent and Complex Sys-tems, 2009
  13. 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
  14. 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
  15. Emmert-Streib F., Dehmer M.: Organizational Structure of the Transcriptional Regulatory Net-work 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
  16. 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 Nat-ural Systems, IEEE Computer Society Press, Targu Mures, Romania, 2008
  17. 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 Artifi-cial and Natural Systems, Petru Maior University Press, Targu Mures, Romania, 2008
  18. Dehmer M.: Relations Between the Topological Complexities of Complex Networks, In: Pro-ceedings of the 2008 International Conference on Machine Learning: Models, Technologies & Applications (MLMTA’08), Las Vegas, USA, 2008
  19. 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 Artifi-cial and Natural Complex Systems, Medical Applications of the Complex Systems, Biomedical Computing, IEEE Computer Society Press, Targu Mures, Romania, 2008
  20. Emmert-Streib F., Dehmer M.: Quantifying Communication Capabilities of Networks. In: Pro-ceedings of the first International Conference on Complexity and Intelligence of the Artificial and Natural Complex Systems, Medical Applications of the Complex Systems, Biomedical Comput-ing, IEEE Computer Society Press, Targu Mures, Romania, 2008
  21. Dehmer M., Mehler A., Emmert-Streib F.: Graph-theoretical Characterizations of Generalized Trees, Proceedings of the 2007 International Conference on Machine Learning: Models, Tech-nologies & Applications (MLMTA’07), Las Vegas, USA, 2007
  22. Dehmer M., Emmert-Streib F., Zulauf A.: A Graph Mining Technique for Automatic Classification of Web Genre Data, In: Proceedings of the 2007 International Conference on Machine Learning: Models, Technologies & Applications (MLMTA’07), Las Vegas, USA, 2007
  23. 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
  24. 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
  25. 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
  26. 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 & Com-putational Biology, Gene Networks: Theory and Application, Workshop at BIOCOMP’06, Las Vegas, USA, 2006, 472-476
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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 Sci-ences and Engineering, Krakow, Poland, Enformatika 10, 2005, 65-69
  32. 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 En-formatika, Systems Sciences and Engineering, Krakow, Poland, Enformatika 10, 2005, 70-74
  33. 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, Sci-ences and Engineering, Budapest, Hungary, Enformatika 8, 2005, 82-87
  34. Emmert-Streib F., Dehmer M.: A Systems Biology approach for the classification of DNA Mi-croarray Data, Applications of Statistical and Machine Learning. Methods in Bioinformatics, Proceedings of BIT 2005 – Bioinformatics Workshop,Torun, Poland, September 15-16, 2005
  35. Emmert-Streib F., Dehmer M., Kilian J.: Classification of large Graphs by a local Graph De-composition, Proceedings of the 2005 International Conference on Data Mining (DMIN’05), Las Vegas, USA, Editors: Arabnia H. R., Scime A., 2005, 200-207
  36. 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
  37. 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
  38. Mehler A., Dehmer M., Gleim R.: Towards logical Hypertext Structure. A graph-theoretic Per-spective, Proceedings of I2CS’04, Lecture Notes, Berlin, New York: Springer, 2005, 136-150
  39. 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

Prof. Dr. habil. Matthias Dehmer

UMIT – The Health and Lifesciences University, Eduard Wallnoefer Zentrum 1, A-6060 Hall in Tyrol, Austria Swiss Distance University of Applied Sciences, Department of Computer Science, Brig, Switzerland, Nankai University, China, College of Artificial Intelligence, Tianjin, China.

matthias.dehmer@ffhs.ch

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