World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
11104
World Ranking
5580
National Ranking
2549

Mathematics

D-Index
43
Citations
8631
World Ranking
1683
National Ranking
727

Overview

Matthias Dehmer is affiliated with the University of Miami in the United States. Their research spans across multiple domains within computer science and mathematics, with a particular focus on graph theory and computational approaches in these fields.

The main fields of study in Dehmer's research include:

  • Computer Science
  • Mathematics

Within these domains, their work concentrates on several subfields such as:

  • Geometry and Topology
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Statistical and Nonlinear Physics
  • Molecular Biology

Dehmer's research topics reflect an interdisciplinary approach, combining elements from graph theory and computational modeling. The key topics include:

  • Graph theory and applications
  • Complex Network Analysis Techniques
  • Computational Drug Discovery Methods
  • Synthesis and Properties of Aromatic Compounds
  • Graph Labeling and Dimension Problems
  • Advanced Graph Theory Research
  • Bioinformatics and Genomic Networks

The scientist has published extensively, with frequent contributions to several key journals and publication venues. These include:

  • Applied Mathematics and Computation
  • Symmetry
  • IEEE Access
  • Information Sciences
  • arXiv (Cornell University)

Among their recent papers are:

  • "An Introductory Review of Deep Learning for Prediction Models With Big Data", 2020, Frontiers in Artificial Intelligence
  • "Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence", 2021, Information Fusion
  • "Named Entity Recognition and Relation Detection for Biomedical Information Extraction", 2020, Frontiers in Cell and Developmental Biology
  • "Combining deep learning with token selection for patient phenotyping from electronic health records", 2020, Scientific Reports
  • "Impact of information diffusion on epidemic spreading in partially mapping two-layered time-varying networks", 2021, Nonlinear Dynamics

Dehmer has collaborated frequently with a number of coauthors, including:

  • Frank Emmert-Streib
  • Modjtaba Ghorbani
  • Zengqiang Chen
  • Shailesh Tripathi
  • Jin Tao

Best Publications

  • A history of graph entropy measures

    Matthias Dehmer;Abbe Mowshowitz

  • An Introductory Review of Deep Learning for Prediction Models With Big Data

    Frank Emmert-Streib;Zhen Yang;Han Feng;Shailesh Tripathi

  • Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks

    Frank Emmert-Streib;Matthias Dehmer;Benjamin Haibe-Kains

  • Information processing in complex networks: Graph entropy and information functionals

    Matthias Dehmer

  • A review of connectivity map and computational approaches in pharmacogenomics.

    Aliyu Musa;Laleh Soltan Ghoraie;Shu-Dong Zhang;Galina V. Glazko

  • Knowledge Discovery and interactive Data Mining in Bioinformatics - State-of-the-Art, future challenges and research directions

    Andreas Holzinger;Andreas Holzinger;Matthias Dehmer;Igor Jurisica;Igor Jurisica

  • Fifty years of graph matching, network alignment and network comparison

    Frank Emmert-Streib;Matthias Dehmer;Yongtang Shi

  • On structure-sensitivity of degree-based topological indices

    Boris Furtula;Ivan Gutman;Ivan Gutman;Matthias Dehmer

  • Entropy and the Complexity of Graphs Revisited

    Abbe Mowshowitz;Matthias Dehmer

  • A new coupled disease-awareness spreading model with mass media on multiplex networks

    Chengyi Xia;Zhishuang Wang;Chunyuan Zheng;Quantong Guo

  • Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

    Andreas Holzinger;Andreas Holzinger;Matthias Dehmer;Frank Emmert-Streib;Rita Cucchiara

  • Extremality of degree-based graph entropies

    Shujuan Cao;Matthias Dehmer;Yongtang Shi

  • High-Dimensional LASSO-Based Computational Regression Models: Regularization, Shrinkage, and Selection

    Frank Emmert-Streib;Matthias Dehmer

  • A Note on Distance-based Graph Entropies

    Zengqiang Chen;Matthias Dehmer;Yongtang Shi

  • Named Entity Recognition and Relation Detection for Biomedical Information Extraction

    Nadeesha Perera;Matthias Dehmer;Frank Emmert-Streib

  • Networks for systems biology: conceptual connection of data and function

    Frank Emmert-Streib;M. Dehmer

  • Statistical modelling of molecular descriptors in QSAR/QSPR

    Matthias Dehmer;Kurt Varmuza;Danail Bonchev

  • Interplay between SIR-based disease spreading and awareness diffusion on multiplex networks

    Chunyuan Zheng;Chengyi Xia;Quantong Guo;Quantong Guo;Matthias Dehmer

  • Structural Analysis of Complex Networks

    Matthias Dehmer

  • On Entropy-Based Molecular Descriptors: Statistical Analysis of Real and Synthetic Chemical Structures

    Matthias Dehmer;Kurt Varmuza;Stephan Borgert;Frank Emmert-Streib

  • Analysis of Microarray Data: A Network-Based Approach

    Frank Emmert-Streib;Matthias Dehmer

  • Analysis of Complex Networks: From Biology to Linguistics

    Matthias Dehmer;Frank Emmert-Streib

  • A review of connectivity map and computational approaches in pharmacogenomics

    Unknown

Frequent Co-Authors

Frank Emmert-Streib
Frank Emmert-Streib Tampere University
Zengqiang Chen
Zengqiang Chen Nankai University
Andreas Holzinger
Andreas Holzinger BOKU University
Ivan Gutman
Ivan Gutman University of Kragujevac
Max Mühlhäuser
Max Mühlhäuser Technical University of Darmstadt
Guangming Xie
Guangming Xie Peking University
Chengyi Xia
Chengyi Xia Tianjin Polytechnic University
Benjamin Haibe-Kains
Benjamin Haibe-Kains Princess Margaret Cancer Centre
Igor Jurisica
Igor Jurisica University Health Network
Boris Furtula
Boris Furtula University of Kragujevac

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