Mark Gerstein

257.5k citations
558 papers · 61.8k indexed · 19 hit papers · h-index 123
    • Genomics and Phylogenetic Studies 128
    • RNA and protein synthesis mechanisms 113
    • Bioinformatics and Genomic Networks 106
    • Genomics and Chromatin Dynamics 89
    • Protein Structure and Dynamics 79
    • Gene expression and cancer classification 73
    • RNA Research and Splicing 63
    • Machine Learning in Bioinformatics 45
  • Cancer Research top 0.05%
  • Aging top 0.2%
  • Genetics top 0.05%
  • Plant Science top 0.1%

Mark Gerstein

548 papers receiving 60.5k citations

Hit Papers

Dermal Adipocy...19619932026200420152.5k5.0k7.5k

Peers

Mark Gerstein
Comparison fields: 5 of 229
  • Molecular Biology 48.2k
  • Cancer Research 7.8k
  • Aging 748
  • Genetics 8.6k
  • Plant Science 6.9k
Replace Trey Ideker with:
Trey Ideker United States
Christian von Mering Switzerland
Gavin Sherlock United States
M Snyder United States
Lars Juhl Jensen Denmark
Damian Szklarczyk Switzerland
Susumu Goto Japan
J. Michael Cherry United States
Nitin S. Baliga United States
Brad T. Sherman United States
Mark Gerstein relative to Trey Ideker United States Trey Ideker's profile →
Citations per field
00.5×1.5×
Trey Ideker · 1×
Citations per year

Countries citing papers authored by Mark Gerstein

Since Specialization
Citations

This map shows the geographic impact of Mark Gerstein's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mark Gerstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Gerstein more than expected).

Fields of papers citing papers by Mark Gerstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Gerstein. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mark Gerstein. The network helps show where Mark Gerstein may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Mark Gerstein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Gerstein Line = papers co-authored together Mark Gerstein links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20246
2 202310
3 202234
4 202225
5 20215
6 20217
7 202110
8 20218
9 202011
10 202018
11 20204
12 2012144
13 2010150
14 2009139
15 2007292
16 2007291
17 200760
18 2006177
19
A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Databreakdown →
2003916
20 2002136

About Mark Gerstein

Mark Gerstein is a scholar working on Molecular Biology, Cancer Research and Aging, having authored 558 papers that have together received 61.8k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (128 papers), RNA and protein synthesis mechanisms (113 papers), Bioinformatics and Genomic Networks (106 papers), Genomics and Chromatin Dynamics (89 papers), Protein Structure and Dynamics (79 papers), Gene expression and cancer classification (73 papers), RNA Research and Splicing (63 papers) and Machine Learning in Bioinformatics (45 papers). The work is most often cited by research in Molecular Biology (48.2k citations), Cancer Research (7.8k citations) and Aging (748 citations). Mark Gerstein has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include M Snyder, Zhong Wang, Haiyuan Yu, Dov Greenbaum, Joel Rozowsky, Nicholas M. Luscombe, Ronald Jansen, Alexej Abyzov, Cyrus Chothia and Philip M. Kim. Their work appears in journals such as Bioinformatics, Genome biology, Genome Research, Journal of Molecular Biology and PLoS Computational Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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