World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
12724
World Ranking
5794
National Ranking
25

Jesper Tegnér 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 Jesper Tegnér 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: 224 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Jesper Tegnér 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 Jesper Tegnér 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: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Overview

Jesper Tegnér is affiliated with the King Abdullah University of Science and Technology in Saudi Arabia. Their research predominantly lies within the field of Biochemistry, Genetics and Molecular Biology, with a significant focus on Molecular Biology.

Their work spans several subfields of study including Immunology, Artificial Intelligence, Biophysics, and Computational Theory and Mathematics. Key research topics that Jesper Tegnér has contributed to are:

  • Single-cell and spatial transcriptomics
  • Bioinformatics and Genomic Networks
  • Gene expression and cancer classification
  • Immune cells in cancer
  • Cell Image Analysis Techniques
  • Machine Learning in Bioinformatics
  • Gene Regulatory Network Analysis

Jesper Tegnér has authored numerous papers, with some recent notable publications being:

  • "Harmonization of quality metrics and power calculation in multi-omic studies," published in 2020 in Nature Communications
  • "DeepViral: prediction of novel virus-host interactions from protein sequences and infectious disease phenotypes," published in 2021 in Bioinformatics
  • "Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder," published in 2020 in Nature Communications
  • "A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts," published in 2021 in GeroScience
  • "STATegra: Multi-Omics Data Integration - A Conceptual Scheme With a Bioinformatics Pipeline," published in 2021 in Frontiers in Genetics

Frequent collaborators include David Gómez-Cabrero, Narsis A. Kiani, Vincenzo Lagani, Robert Lehmann, and Felipe Prósper. Their publications appear often in venues such as bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Blood, Nature Machine Intelligence, and the SSRN Electronic Journal.

Jesper Tegnér's academic contributions also extend to book publications, including a work titled Algorithmic Information Dynamics published by Cambridge University Press in 2023.

Best Publications

  • A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

    Andrew E. Teschendorff;Francesco Marabita;Matthias Lechner;Thomas Bartlett

  • An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man

    Timothy Ravasi;Harukazu Suzuki;Carlo Vittorio Cannistraci;Shintaro Katayama

  • Reverse engineering gene networks using singular value decomposition and robust regression

    M. K. S. Yeung;J. Tegner;J. J. Collins

  • Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling

    Jesper Tegnér;M. K. Stephen Yeung;Jeff Hasty;James J. Collins

  • The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line

    Harukazu Suzuki;Alistair R.R. Forrest;Erik Van Nimwegen;Carsten O. Daub

  • Data integration in the era of omics: current and future challenges.

    David Gomez-Cabrero;Imad Abugessaisa;Dieter Maier;Andrew E. Teschendorff

  • Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory

    X.-J. Wang;Jesper Tegnér;Jesper Tegnér;C. Constantinidis;C. Constantinidis;P.S. Goldman-Rakic

  • Mechanism for top-down control of working memory capacity

    Fredrik Edin;Torkel Klingberg;Pär Johansson;Fiona McNab

  • Intrinsic function of a neuronal network - a vertebrate central pattern generator.

    Sten Grillner;Örjan Ekeberg;Abdeljabbar El Manira;Anders Lansner

  • An integrative analysis reveals coordinated reprogramming of the epigenome and the transcriptome in human skeletal muscle after training

    Maléne E Lindholm;Francesco Marabita;David Gomez-Cabrero;Helene Rundqvist

  • Normalization of circulating microRNA expression data obtained by quantitative real-time RT-PCR.

    Francesco Marabita;Paola de Candia;Anna Torri;Jesper Tegnér

  • Towards scalable and data efficient learning of Markov boundaries

    Jose M. Peòa;Roland Nilsson;Johan Björkegren;Jesper Tegnér

  • An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform.

    Francesco Marabita;Malin Almgren;Maléne E. Lindholm;Sabrina Ruhrmann

  • Consistent Feature Selection for Pattern Recognition in Polynomial Time

    Roland Nilsson;José M. Peña;Johan Björkegren;Jesper Tegnér

  • Calcium-dependent potassium channels play a critical role for burst termination in the locomotor network in lamprey.

    A. el Manira;J. Tegner;S. Grillner

  • The dynamical stability of reverberatory neural circuits.

    Jesper Tegnér;Albert Compte;Xiao Jing Wang

  • A vision and strategy for the virtual physiological human in 2010 and beyond.

    Peter Hunter;Peter Hunter;Peter V. Coveney;Bernard de Bono;Vanessa Diaz

  • Spike-timing-dependent plasticity: common themes and divergent vistas.

    Adam Kepecs;Mark C.W. van Rossum;Sen Song;Jesper Tegner

  • Transcriptional network dynamics in macrophage activation.

    Roland Nilsson;Vladimir B. Bajic;Vladimir B. Bajic;Harukazu Suzuki;Diego di Bernardo

  • A Decomposition Method for Global Evaluation of Shannon Entropy and Local Estimations of Algorithmic Complexity

    Hector Zenil;Hector Zenil;Santiago Hernández-Orozco;Santiago Hernández-Orozco;Narsis Aftab Kiani;Fernando Soler-Toscano

  • Towards scalable and data efficient learning of Markov boundaries

    Jose M. Pena;Roland Nilsson;Johan Björkegren;Jesper Tegner

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