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Computer Science
Netherlands
2025

D-Index & Metrics

Computer Science

D-Index
59
Citations
15210
World Ranking
3405
National Ranking
35

Marcel J. T. Reinders 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 Marcel J. T. Reinders 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: 316 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Marcel J. T. Reinders 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 Marcel J. T. Reinders 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: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Netherlands Leader Award
  • 2022 - Research.com Computer Science in Netherlands Leader Award

Overview

Marcel J. T. Reinders is affiliated with Delft University of Technology in the Netherlands. Their research spans multiple domains within biochemistry, genetics, molecular biology, and medicine.

The scientist has contributed to a variety of publication venues including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Alzheimer's & Dementia
  • Annals of the Rheumatic Diseases
  • Bioinformatics

Marcel J. T. Reinders' main fields of study include biochemistry, genetics and molecular biology, and medicine, with focus on several subfields such as molecular biology, genetics, physiology, immunology, and biophysics.

Their research encompasses a range of main topics, among which are:

  • Single-cell and spatial transcriptomics
  • Cell image analysis techniques
  • Cancer genomics and diagnostics
  • Alzheimer's disease research and treatments
  • Bioinformatics and genomic networks
  • Gene expression and cancer classification
  • Metabolomics and mass spectrometry studies

Among recent papers authored or co-authored by Marcel J. T. Reinders are:

  • "Eleven grand challenges in single-cell data science," published in 2020 in Genome Biology
  • "SpaGE: Spatial Gene Enhancement using scRNA-seq," published in 2020 in Nucleic Acids Research
  • "Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer's disease," published in 2022 in Nature Genetics
  • "Unsupervised protein embeddings outperform hand-crafted sequence and structure features at predicting molecular function," published in 2020 in Bioinformatics
  • "Heritability estimates for 361 blood metabolites across 40 genome-wide association studies," published in 2020 in Nature Communications

Frequent co-authors of Marcel J. T. Reinders include:

  • Ahmed Mahfouz
  • Henne Holstege
  • Erik B. van den Akker
  • Niccolò Tesi
  • Marc Hulsman

Best Publications

  • Eleven grand challenges in single-cell data science

    David Lähnemann;David Lähnemann;Johannes Köster;Johannes Köster;Ewa Szczurek;Davis J. McCarthy;Davis J. McCarthy

  • Unifying user-based and item-based collaborative filtering approaches by similarity fusion

    Jun Wang;Arjen P. de Vries;Marcel J. T. Reinders

  • TRIBLER: a social‐based peer‐to‐peer system

    JA Pouwelse;P Garbacki;J Jun Wang;Arthur Bakker

  • A comparison of automatic cell identification methods for single-cell RNA sequencing data

    Tamim Abdelaal;Tamim Abdelaal;Lieke C.M. Michielsen;Lieke C.M. Michielsen;Davy Cats;Dylan Hoogduin

  • Resolving motion correspondence for densely moving points

    C.J. Veenman;M.J.T. Reinders;E. Backer

  • A maximum variance cluster algorithm

    C.J. Veenman;M.J.T. Reinders;E. Backer

  • An algorithm-based topographical biomaterials library to instruct cell fate

    Hemant V. Unadkat;Marc Hulsman;Kamiel Cornelissen;Bernke J. Papenburg

  • Fewer permutations, more accurate P-values

    Theo A. Knijnenburg;Lodewyk F. A. Wessels;Marcel J. T. Reinders;Ilya Shmulevich

  • Genetic network modeling.

    E P van Someren;L F A Wessels;E Backer;M J T Reinders

  • Linear Modeling of Genetic Networks from Experimental Data

    Eugene P. van Someren;L. F. A. Wessels;Marcel J. T. Reinders

  • Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types

    Vincent van Unen;Thomas Höllt;Thomas Höllt;Nicola Pezzotti;Na Li

  • Sign Language Recognition by Combining Statistical DTW and Independent Classification

    J.F. Lichtenauer;E.A. Hendriks;M.J. Reinders

  • Random subspace method for multivariate feature selection

    Carmen Lai;Marcel J. T. Reinders;Lodewyk Wessels

  • A comparison of genetic network models.

    L. F. A. Wessels;E. P. Van Someren;M. J. T. Reinders

  • SpaGE: Spatial Gene Enhancement using scRNA-seq.

    Tamim Abdelaal;Tamim Abdelaal;Soufiane Mourragui;Soufiane Mourragui;Ahmed Mahfouz;Ahmed Mahfouz;Marcel J T Reinders;Marcel J T Reinders

  • Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data

    Walid M. Abdelmoula;Benjamin Balluff;Sonja Englert;Jouke Dijkstra

  • The nearest subclass classifier: a compromise between the nearest mean and nearest neighbor classifier

    C.J. Veenman;M.J.T. Reinders

  • Image sharpening by morphological filtering

    John G. M. Schavemaker;Marcel J. T. Reinders;Jan J. Gerbrands;Eric Backer

  • A protocol for building and evaluating predictors of disease state based on microarray data

    Lodewyk F. A. Wessels;Marcel J. T. Reinders;Augustinus A. M. Hart;Cor J. Veenman

  • RNA sequencing data integration reveals an miRNA interactome of osteoarthritis cartilage.

    Rodrigo Coutinho de Almeida;Yolande F M Ramos;Ahmed Mahfouz;Wouter den Hollander

  • A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets

    Carmen Lai;Marcel J. T. Reinders;Laura J. van't Veer;Lodewyk F. A. Wessels

  • WISECONDOR: detection of fetal aberrations from shallow sequencing maternal plasma based on a within-sample comparison scheme

    Roy Straver;Erik A. Sistermans;Henne Holstege;Allerdien Visser

Frequent Co-Authors

Lodewyk F. A. Wessels
Lodewyk F. A. Wessels Antoni van Leeuwenhoek Hospital
Boudewijn P. F. Lelieveldt
Boudewijn P. F. Lelieveldt Leiden University Medical Center
Philip Scheltens
Philip Scheltens Amsterdam UMC
Wiesje M. van der Flier
Wiesje M. van der Flier Vrije Universiteit Amsterdam
Martijn Huisman
Martijn Huisman Vrije Universiteit Amsterdam
Jan de Boer
Jan de Boer Antoni van Leeuwenhoek Hospital
Frank J.T. Staal
Frank J.T. Staal Leiden University Medical Center
Han A. B. Wösten
Han A. B. Wösten Utrecht University
P. Eline Slagboom
P. Eline Slagboom Leiden University Medical Center
Marian Beekman
Marian Beekman Leiden University Medical Center

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