M Snyder

199.6k citations
861 papers · 81.0k · 30 hit papers · h-index 140

Impact in

    • Genomics and Chromatin Dynamics
    • RNA Research and Splicing
    • Fungal and yeast genetics research
    • RNA and protein synthesis mechanisms
    • RNA modifications and cancer
    • Genomics and Phylogenetic Studies
    • Bioinformatics and Genomic Networks
  • Aging top 0.1%

Papers in

    • Fungal and yeast genetics research 108
    • Genomics and Chromatin Dynamics 103
    • RNA Research and Splicing 75
    • RNA and protein synthesis mechanisms 74
    • Gene expression and cancer classification 68
    • Bioinformatics and Genomic Networks 61
    • Genomics and Phylogenetic Studies 55
    • RNA modifications and cancer 48

M Snyder

842 papers receiving 79.5k citations

M Snyder's Hit Papers

Short-chain fatty acid metabolites propionate and butyrate are unique epigenetic regulatory elements linking diet, metabolism and gene expression 2025 · 60 citations
600+4+9Years since publication50010001.5k

Peers

M Snyder
Comparison fields: 5 of 230
  • Molecular Biology 53.6k
  • Aging 1.1k
  • Cancer Research 7.8k
  • Genetics 9.8k
  • Cell Biology 5.3k
Replace Mark Gerstein with:
Mark Gerstein United States
Patrick O. Brown United States
Ruedi Aebersold Switzerland
Minoru Kanehisa Japan
Ronald W. Davis United States
Wolfgang Huber Germany
Lars Juhl Jensen Denmark
Gordon K. Smyth Australia
George M. Church United States
Stephen J. Elledge United States
M Snyder relative to Mark Gerstein United States Mark Gerstein's profile →
Citations per field
00.5×1.5×2.3×
Mark Gerstein · 1×
Citations per year

Countries citing papers authored by M Snyder

Since Specialization
Citations

This map shows the geographic impact of M Snyder'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 M Snyder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M Snyder more than expected).

Fields of papers citing papers by M Snyder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M Snyder. 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 M Snyder. The network helps show where M Snyder may publish in the future.

Co-authors

The 25 scholars most cited alongside M Snyder, 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 M Snyder Line = papers co-authored together M Snyder links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 861 papers — load more, or switch the sort, to bring in the rest.

#Work
1
RNA-Seq: a revolutionary tool for transcriptomics
Hit paper breakdown →
20089128
2
The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing
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20081826
3
Annotation of functional variation in personal genomes using RegulomeDB
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20121735
4
Single-cell chromatin accessibility reveals principles of regulatory variation
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20151505
5
Global Analysis of Protein Activities Using Proteome Chips
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20011502
6
CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing
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20111080
7
Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing
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20071024
8
A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data
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2003918
9
High-Throughput Sequencing Technologies
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2015874
10
Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF
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2001841
11
Global Identification of Human Transcribed Sequences with Genome Tiling Arrays
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2004805
12
Protein chip technology
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2003696
13
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
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2016692
14
Integrative omics for health and disease
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2018691
15
Genomic analysis of regulatory network dynamics reveals large topological changes
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2004687
16
HTRA1 Promoter Polymorphism in Wet Age-Related Macular Degeneration
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2006673
17
Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution
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2016671
18
Analysis of yeast protein kinases using protein chips
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2000612
19
Unlocking the secrets of the genome
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2009610
20
Subcellular localization of the yeast proteome
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2002598

About M Snyder

M Snyder is a scholar working on Molecular Biology, Genetics, Plant Science, Cancer Research and Cell Biology, having authored 861 papers that have together received 81.0k indexed citations. Recurring topics across this work include Fungal and yeast genetics research (108 papers), Genomics and Chromatin Dynamics (103 papers), RNA Research and Splicing (75 papers), RNA and protein synthesis mechanisms (74 papers), Gene expression and cancer classification (68 papers), Bioinformatics and Genomic Networks (61 papers), Genomics and Phylogenetic Studies (55 papers) and RNA modifications and cancer (48 papers). The work is most often cited by research in Molecular Biology (53.6k citations), Aging (1.1k citations), Cancer Research (7.8k citations), Genetics (9.8k citations) and Cell Biology (5.3k citations). M Snyder has collaborated with scholars based in United States, China and France. Frequent co-authors include Mark Gerstein, Zhong Wang, Heng Zhu, Konrad J. Karczewski, Joel Rozowsky, Alexander E. Urban, Ghia Euskirchen, Sherman M. Weissman, Paul Bertone and Debasish Raha. Their work appears in journals such as Proceedings of the National Academy of Sciences, Genome Research, Genes & Development, Nature Communications and PLoS Genetics.

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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