World's Best Scientists 2026 revealed!
Francisco Azuaje

Francisco Azuaje

D-Index & Metrics

Computer Science

D-Index
38
Citations
6559
World Ranking
10186
National Ranking
637

Francisco Azuaje publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Francisco Azuaje sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 182 publications — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Francisco Azuaje D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Francisco Azuaje sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Francisco Azuaje is affiliated with Union Chimique Belge in Belgium. Their research spans the intersecting domains of Biochemistry, Genetics, and Molecular Biology, with a significant focus on Medicine. The scientist's work involves various subfields including Molecular Biology, Computational Theory and Mathematics, Genetics, Psychiatry and Mental Health, and Immunology.

The main research topics addressed by Azuaje include:

  • Bioinformatics and Genomic Networks
  • Computational Drug Discovery Methods
  • Immune Cells in Cancer
  • Glioma Diagnosis and Treatment
  • Cancer Research and Treatments
  • RNA Modifications and Cancer
  • Dementia and Cognitive Impairment Research

Francisco Azuaje has contributed to several scientific papers, some of which include:

  • Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology (2020) published in Acta Neuropathologica
  • Machine learning-assisted neurotoxicity prediction in human midbrain organoids (2020) published in Parkinsonism & Related Disorders
  • Extracellular ATP and CD39 Activate cAMP-Mediated Mitochondrial Stress Response to Promote Cytarabine Resistance in Acute Myeloid Leukemia (2020) published in Cancer Discovery
  • Fisetin protects against cardiac cell death through reduction of ROS production and caspases activity (2020) published in Scientific Reports
  • Oncolytic H-1 parvovirus binds to sialic acid on laminins for cell attachment and entry (2021) published in Nature Communications

Several venues have frequently published Azuaje's work, including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • BMC Medical Research Methodology
  • Zenodo (CERN European Organization for Nuclear Research)
  • Acta Neuropathologica
  • Parkinsonism & Related Disorders

Collaborations form a noteworthy part of Azuaje's research activities. The scientist has frequently co-authored papers with:

  • Simone P. Niclou
  • Arnaud Muller
  • Tony Kaoma
  • Petr V. Nazarov
  • Anna Golebiewska

Best Publications

  • Advanced Methods And Tools for ECG Data Analysis

    Gari D. Clifford;Francisco Azuaje;Patrick McSharry

  • Multiple SVM-RFE for gene selection in cancer classification with expression data

    Kai-Bo Duan;J.C. Rajapakse;Haiying Wang;F. Azuaje

  • Cluster validation techniques for genome expression data

    N. Bolshakova;F. Azuaje

  • An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors

    Peyman Jafari;Francisco Azuaje

  • Artificial intelligence for precision oncology: beyond patient stratification.

    Francisco Azuaje

  • Gene expression correlation and gene ontology-based similarity: an assessment of quantitative relationships

    H. Wang;F. Azuaje;O. Bodenreider;J. Dopazo

  • Solutions to Instability Problems with Sequential Wrapper-based Approaches to Feature Selection

    Kevin Dunne;Padraig Cunningham;Francisco Azuaje

  • Computational models for predicting drug responses in cancer research

    Francisco Azuaje

  • A cluster validity framework for genome expression data.

    Francisco Azuaje

  • Permutation – based statistical tests for multiple hypotheses

    Anyela Camargo;Francisco Azuaje;Haiying Wang;Huiru Zheng

  • Ontology-driven similarity approaches to supporting gene func- tional assessment

    Francisco Azuaje;Haiying Wang;Olivier Bodenreider

  • Databases for lncRNAs: a comparative evaluation of emerging tools

    Sabrina Fritah;Simone P. Niclou;Francisco Azuaje

  • An integrated tool for microarray data clustering and cluster validity assessment

    Nadia Bolshakova;Francisco Azuaje;Pádraig Cunningham

  • A knowledge-driven approach to cluster validity assessment

    Nadia Bolshakova;Francisco Azuaje;Pádraig Cunningham

  • Drug-target network in myocardial infarction reveals multiple side effects of unrelated drugs

    Francisco J. Azuaje;Lu Zhang;Yvan Devaux;Daniel R. Wagner

  • Selecting biologically informative genes in co-expression networks with a centrality score

    Francisco J Azuaje

  • A computational neural approach to support the discovery of gene function and classes of cancer

    F. Azuaje

  • Witten IH, Frank E: Data Mining: Practical Machine Learning Tools and Techniques 2nd edition

    Francisco Azuaje

  • Predicting coronary disease risk based on short-term RR interval measurements: a neural network approach

    Francisco Azuaje;Werner Dubitzky;Philippe Lopes;Norman D. Black

  • Machine learning-assisted neurotoxicity prediction in human midbrain organoids.

    Anna S. Monzel;Kathrin Hemmer;Tony Kaoma;Lisa M. Smits

  • Discovering relevance knowledge in data: a growing cell structures approach

    F. Azuaje;W. Dubitzky;N. Black;K. Adamson

Frequent Co-Authors

Gunnar Dittmar
Gunnar Dittmar Luxembourg Institute of Health
Ioannis Xenarios
Ioannis Xenarios University of Lausanne
Joaquín Dopazo
Joaquín Dopazo Institute of Biomedicine of Seville
Jagath C. Rajapakse
Jagath C. Rajapakse Nanyang Technological University
Christel Herold-Mende
Christel Herold-Mende Heidelberg University
Katherine W. Ferrara
Katherine W. Ferrara Stanford University
Olivier Bodenreider
Olivier Bodenreider National Institutes of Health
Pádraig Cunningham
Pádraig Cunningham University College Dublin
Andrei Zinovyev
Andrei Zinovyev Institute Curie
Zhongming Zhao
Zhongming Zhao The University of Texas Health Science Center at Houston

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