World's Best Scientists 2026 revealed!
Christian J. Stoeckert

Christian J. Stoeckert

D-Index & Metrics

Genetics

D-Index
71
Citations
33955
World Ranking
2150
National Ranking
977

Christian J. Stoeckert publication distribution in Genetics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Genetics in 2026. The highlighted bar marks where Christian J. Stoeckert sits on this spectrum.

45–54 publications: 6 scientists 55–64 publications: 10 scientists 65–74 publications: 35 scientists 75–84 publications: 84 scientists 85–94 publications: 102 scientists 95–104 publications: 151 scientists 105–114 publications: 175 scientists 115–124 publications: 203 scientists 125–134 publications: 217 scientists 135–144 publications: 205 scientists 145–154 publications: 193 scientists 155–164 publications: 188 scientists 165–174 publications: 170 scientists 175–184 publications: 178 scientists 185–194 publications: 164 scientists 195–204 publications: 173 scientists 205–214 publications: 159 scientists 215–224 publications: 134 scientists 225–234 publications: 143 scientists 235–244 publications: 105 scientists 245–254 publications: 114 scientists 255–264 publications: 92 scientists 265–274 publications: 88 scientists 275–284 publications: 87 scientists 285–294 publications: 80 scientists 295–304 publications: 62 scientists 305–314 publications: 75 scientists 315–324 publications: 67 scientists 325–334 publications: 60 scientists 335–344 publications: 52 scientists 345–354 publications: 40 scientists 355–364 publications: 48 scientists 365–374 publications: 47 scientists 375–384 publications: 46 scientists 385–394 publications: 31 scientists 395–404 publications: 27 scientists 405–414 publications: 40 scientists 415–424 publications: 30 scientists 425–434 publications: 43 scientists 435–444 publications: 29 scientists 445–454 publications: 14 scientists 455–464 publications: 28 scientists 465–474 publications: 21 scientists 475–484 publications: 21 scientists 485–494 publications: 22 scientists 495–504 publications: 17 scientists 505–514 publications: 12 scientists 515–524 publications: 11 scientists 525–534 publications: 8 scientists 535–544 publications: 8 scientists 545–554 publications: 14 scientists 555–564 publications: 4 scientists 565–574 publications: 11 scientists 575–584 publications: 5 scientists 585–594 publications: 11 scientists 595–604 publications: 12 scientists 605–614 publications: 7 scientists 615–624 publications: 6 scientists 625–634 publications: 10 scientists 635–644 publications: 9 scientists 645–654 publications: 10 scientists 655–664 publications: 6 scientists 665–674 publications: 6 scientists 675–684 publications: 6 scientists 685–694 publications: 4 scientists 695–702 publications: 6 scientists 703+ publications: 100 scientists
45 publications 703+

This scientist: 199 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 703 publications or more.

Christian J. Stoeckert D-index placement in Genetics in 2026

The chart shows the D-index (discipline H-index) distribution of Genetics scientists ranked by Research.com in 2026. The highlighted bar marks where Christian J. Stoeckert sits on this spectrum.

40–41 D-Index: 24 scientists 42–43 D-Index: 52 scientists 44–45 D-Index: 84 scientists 46–47 D-Index: 112 scientists 48–49 D-Index: 118 scientists 50–51 D-Index: 141 scientists 52–53 D-Index: 143 scientists 54–55 D-Index: 145 scientists 56–57 D-Index: 179 scientists 58–59 D-Index: 162 scientists 60–61 D-Index: 175 scientists 62–63 D-Index: 191 scientists 64–65 D-Index: 172 scientists 66–67 D-Index: 184 scientists 68–69 D-Index: 164 scientists 70–71 D-Index: 158 scientists 72–73 D-Index: 150 scientists 74–75 D-Index: 136 scientists 76–77 D-Index: 127 scientists 78–79 D-Index: 127 scientists 80–81 D-Index: 111 scientists 82–83 D-Index: 110 scientists 84–85 D-Index: 110 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 102 scientists 90–91 D-Index: 66 scientists 92–93 D-Index: 72 scientists 94–95 D-Index: 70 scientists 96–97 D-Index: 54 scientists 98–99 D-Index: 60 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 55 scientists 104–105 D-Index: 45 scientists 106–107 D-Index: 42 scientists 108–109 D-Index: 28 scientists 110–111 D-Index: 39 scientists 112–113 D-Index: 25 scientists 114–115 D-Index: 31 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 34 scientists 120–121 D-Index: 29 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 18 scientists 126–127 D-Index: 27 scientists 128–129 D-Index: 22 scientists 130–131 D-Index: 16 scientists 132–133 D-Index: 11 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 12 scientists 138–139 D-Index: 21 scientists 140–141 D-Index: 4 scientists 142–143 D-Index: 9 scientists 144–145 D-Index: 14 scientists 146–147 D-Index: 6 scientists 148–149 D-Index: 10 scientists 150–151 D-Index: 7 scientists 152–153 D-Index: 9 scientists 154–155 D-Index: 8 scientists 156–157 D-Index: 8 scientists 158–159 D-Index: 9 scientists 160+ D-Index: 96 scientists
40 D-Index 160+

This scientist: 71 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 160 D-Index or more.

Overview

Christian J. Stoeckert is affiliated with the University of Pennsylvania in the United States. Their research spans multiple disciplines within the biochemistry, genetics, molecular biology, and computer science domains. The scientist's work includes contributions to molecular biology, artificial intelligence, genetics, information systems, and ecology.

Their principal research topics cover a range of areas including biomedical text mining and ontologies, bioinformatics and genomic networks, semantic web and ontologies, genomics and phylogenetic studies, genomics and rare diseases, research data management practices, and pancreatic function and diabetes.

Recent scholarly publications include:

  • VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center (2021), published in Nucleic Acids Research
  • OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies (2021), published in Database
  • Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project (2020), published in Nature Reviews Nephrology
  • ClinEpiDB: an open-access clinical epidemiology database resource encouraging online exploration of complex studies (2020), published in Gates Open Research
  • NIAGADS Alzheimer's GenomicsDB: A resource for exploring Alzheimer's disease genetic and genomic knowledge (2023), published in Alzheimer's & Dementia

Frequent co-authors in their work include:

  • Emily Greenfest-Allen
  • Jie Zheng
  • Otto Valladares
  • Amanda B Kuzma
  • Yuk Yee Leung

The scientist often publishes in venues such as bioRxiv (Cold Spring Harbor Laboratory), Alzheimer's & Dementia, Database, Nucleic Acids Research, and Nature Reviews Nephrology. Their most frequent publication venue is bioRxiv, where they have six publications, followed by Alzheimer's & Dementia with five.

Best Publications

  • OrthoMCL: identification of ortholog groups for eukaryotic genomes.

    Li Li;Christian J. Stoeckert;David S. Roos

  • Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

    Alvis Brazma;Pascal Hingamp;John Quackenbush;Gavin Sherlock

  • PlasmoDB: a functional genomic database for malaria parasites

    Cristina Aurrecoechea;John Brestelli;Brian P. Brunk;Jennifer Dommer

  • TriTrypDB: a functional genomic resource for the Trypanosomatidae

    Martin Aslett;Cristina Aurrecoechea;Matthew Berriman;John Brestelli

  • Comparative genomics of the neglected human malaria parasite Plasmodium vivax

    Jane M. Carlton;Jane M. Carlton;John H. Adams;Joana C. Silva;Shelby L. Bidwell

  • OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups

    Feng Chen;Aaron J. Mackey;Christian J. Stoeckert;David S. Roos

  • PPARγ and C/EBP factors orchestrate adipocyte biology via adjacent binding on a genome-wide scale

    Martina I. Lefterova;Yong Zhang;David J. Steger;Michael Schupp

  • Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project

    Chris F. Taylor;Chris F. Taylor;Dawn Field;Susanna Assunta Sansone;Susanna Assunta Sansone;Jan Aerts

  • Design and implementation of microarray gene expression markup language (MAGE-ML)

    Paul T Spellman;Michael Miller;Jason Stewart;Charles Troup

  • Prevention of Islet Allograft Rejection with Engineered Myoblasts Expressing FasL in Mice

    Henry T. Lau;Ming Yu;Adriano Fontana;Christian J. Stoeckert

  • ToxoDB: an integrated Toxoplasma gondii database resource.

    Bindu Gajria;Amit Bahl;John Brestelli;Jennifer Dommer

  • Promoter features related to tissue specificity as measured by Shannon entropy

    Jonathan Schug;Winfried-Paul Schuller;Claudia Kappen;J Michael Salbaum

  • Using OrthoMCL to assign proteins to OrthoMCL-DB groups or to cluster proteomes into new ortholog groups.

    Steve Fischer;Brian P. Brunk;Feng Chen;Xin Gao

  • PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data

    Amit Bahl;Brian P. Brunk;Jonathan Crabtree;Martin J. Fraunholz

  • Coexisting proinflammatory and antioxidative endothelial transcription profiles in a disturbed flow region of the adult porcine aorta.

    Anthony G. Passerini;Denise C. Polacek;Congzhu Shi;Nadeene M. Francesco

  • Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM)

    Gregory R. Grant;Michael H. Farkas;Angel D. Pizarro;Nicholas F. Lahens

  • Defining the mammalian CArGome

    Qiang Sun;Guang Chen;Jeffrey W. Streb;Xiaochun Long

  • VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center.

    Beatrice Amos;Cristina Aurrecoechea;Matthieu Barba;Ana Barreto

  • FungiDB: an integrated functional genomics database for fungi

    Jason E. Stajich;Todd W. Harris;Brian P. Brunk;John Brestelli

  • A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB

    Tim F Rayner;Philippe Rocca-Serra;Paul T Spellman;Helen C Causton

Frequent Co-Authors

David S. Roos
David S. Roos University of Pennsylvania
Jessica C. Kissinger
Jessica C. Kissinger University of Georgia
Helen Parkinson
Helen Parkinson European Bioinformatics Institute
Jonathan Schug
Jonathan Schug University of Pennsylvania
Peter F. Davies
Peter F. Davies University of Pennsylvania
Alvis Brazma
Alvis Brazma European Bioinformatics Institute
John Quackenbush
John Quackenbush Harvard University
Li-San Wang
Li-San Wang University of Pennsylvania
Gavin Sherlock
Gavin Sherlock Stanford University
Philippe Rocca-Serra
Philippe Rocca-Serra University of Oxford

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