Mark Gerstein

1.6k citations
8 papers · 665 · h-index 7

Impact in

    • Genomics and Chromatin Dynamics
    • RNA and protein synthesis mechanisms
    • Machine Learning in Bioinformatics
    • Bioinformatics and Genomic Networks
    • Genomics and Phylogenetic Studies
    • Gene expression and cancer classification
    • Epigenetics and DNA Methylation
    • RNA Research and Splicing

Papers in

    • Genomics and Chromatin Dynamics 4
    • RNA and protein synthesis mechanisms 3
    • Machine Learning in Bioinformatics 2
    • Genomics and Phylogenetic Studies 2
    • Bioinformatics and Genomic Networks 2
    • RNA Research and Splicing 2
    • Advanced Proteomics Techniques and Applications 1

Mark Gerstein

8 papers receiving 642 citations

Peers

Mark Gerstein
Comparison fields: 5 of 73
  • Molecular Biology 561
  • Aging 5
  • Spectroscopy 44
  • Cancer Research 35
  • Genetics 48
Replace Gernot Stocker with:
Gernot Stocker Austria
Michaella J. Levy United States
Scott Rusin United States
Mădălina Giurgiu Germany
Robert Fragoza United States
Valentine Rech de Laval Switzerland
A Kahn United States
Matthias Haffke France
Gaurav Mishra India
Bi Zhao United States
Mark Gerstein relative to Gernot Stocker Austria Gernot Stocker's profile →
Citations per field
00.5×
Gernot Stocker · 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-authors

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

8 of 8 papers shown
#Work
1 2012194
2 2012139
3 2000122
4 200276
5 200057
6 200048
7 199727
8 20242

About Mark Gerstein

Mark Gerstein is a scholar working on Molecular Biology, Spectroscopy, Materials Chemistry, Infectious Diseases and Organic Chemistry, having authored 8 papers that have together received 665 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (4 papers), RNA and protein synthesis mechanisms (3 papers), Machine Learning in Bioinformatics (2 papers), Genomics and Phylogenetic Studies (2 papers), Bioinformatics and Genomic Networks (2 papers), RNA Research and Splicing (2 papers), Advanced Proteomics Techniques and Applications (1 paper) and Enzyme Structure and Function (1 paper). The work is most often cited by research in Molecular Biology (561 citations), Aging (5 citations), Spectroscopy (44 citations), Cancer Research (35 citations) and Genetics (48 citations). Mark Gerstein has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Amar Drawid, Ewan Birney, Xianjun Dong, Zhiping Weng, Chao Cheng, Roderic Guigó, Sarah Djebali, T Gingeras, Ronald Jansen and James Brown. Their work appears in journals such as Bioinformatics, Trends in Genetics, Blood, Genome Research and Genome 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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