Mark Gerstein
Impact in
- Molecular Biology top 0.01%
- RNA and protein synthesis mechanisms
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
- RNA Research and Splicing
- Genomics and Chromatin Dynamics
- RNA modifications and cancer
- Gene expression and cancer classification
- Cancer Research top 0.05%
Papers in
-
- Genomics and Phylogenetic Studies 106
- RNA and protein synthesis mechanisms 104
- Bioinformatics and Genomic Networks 91
- Genomics and Chromatin Dynamics 81
- Protein Structure and Dynamics 75
- RNA Research and Splicing 58
- Gene expression and cancer classification 56
- Machine Learning in Bioinformatics 35
- Genetics 77
- Co-authors
- M Snyder (108 shared papers)Zhong Wang (3 shared papers)Haiyuan Yu (30 shared papers)Dov Greenbaum (26 shared papers)Joel Rozowsky (61 shared papers)Nicholas M. Luscombe (19 shared papers)Ronald Jansen (17 shared papers)Alexej Abyzov (22 shared papers)
- Journals
- Bioinformatics (38 papers)Genome biology (36 papers)Genome Research (34 papers)Journal of Molecular Biology (26 papers)PLoS Computational Biology (26 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Mark Gerstein
563 papers receiving 64.3k citations
Mark Gerstein's Hit Papers
Peers
Comparison fields: 5 of 233
- Molecular Biology 47.2k
- Cancer Research 7.2k
- Aging 739
- Genetics 8.3k
- Plant Science 6.8k
Countries citing papers authored by Mark Gerstein
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
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.
All Works
Showing the 20 most-cited of 576 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | RNA-Seq: a revolutionary tool for transcriptomics Hit paper breakdown → | 2008 | 9786 |
| 2 | The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing Hit paper breakdown → | 2008 | 1926 |
| 3 | Global Analysis of Protein Activities Using Proteome Chips Hit paper breakdown → | 2001 | 1609 |
| 4 | Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis Hit paper breakdown → | 2019 | 1432 |
| 5 | Comparing protein abundance and mRNA expression levels on a genomic scale. Hit paper breakdown → | 2003 | 1384 |
| 6 | CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing Hit paper breakdown → | 2011 | 1104 |
| 7 | A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data Hit paper breakdown → | 2003 | 996 |
| 8 | Global Identification of Human Transcribed Sequences with Genome Tiling Arrays Hit paper breakdown → | 2004 | 857 |
| 9 | FOXG1-Dependent Dysregulation of GABA/Glutamate Neuron Differentiation in Autism Spectrum Disorders Hit paper breakdown → | 2015 | 824 |
| 10 | The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics Hit paper breakdown → | 2007 | 781 |
| 11 | Genomic analysis of regulatory network dynamics reveals large topological changes Hit paper breakdown → | 2004 | 750 |
| 12 | Structural Mechanisms for Domain Movements in Proteins Hit paper breakdown → | 1994 | 655 |
| 13 | Analysis of yeast protein kinases using protein chips Hit paper breakdown → | 2000 | 655 |
| 14 | Subcellular localization of the yeast proteome Hit paper breakdown → | 2002 | 619 |
| 15 | Unlocking the secrets of the genome Hit paper breakdown → | 2009 | 619 |
| 16 | Structure and evolution of transcriptional regulatory networks Hit paper breakdown → | 2004 | 596 |
| 17 | Statistical analysis of amino acid patterns in transmembrane helices: the GxxxG motif occurs frequently and in association with β-branched residues at neighboring positions Hit paper breakdown → | 2000 | 523 |
| 18 | Spectral Biclustering of Microarray Data: Coclustering Genes and Conditions Hit paper breakdown → | 2003 | 510 |
| 19 | A standard reference frame for the description of nucleic acid base-pair geometry Hit paper breakdown → | 2001 | 505 |
| 20 | 1994 | 478 |
About Mark Gerstein
Mark Gerstein is a scholar working on Molecular Biology, Genetics, Cancer Research, Plant Science and Materials Chemistry, having authored 576 papers that have together received 66.0k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (106 papers), RNA and protein synthesis mechanisms (104 papers), Bioinformatics and Genomic Networks (91 papers), Genomics and Chromatin Dynamics (81 papers), Protein Structure and Dynamics (75 papers), RNA Research and Splicing (58 papers), Gene expression and cancer classification (56 papers) and Machine Learning in Bioinformatics (35 papers). The work is most often cited by research in Molecular Biology (47.2k citations), Cancer Research (7.2k citations), Aging (739 citations), Genetics (8.3k citations) and Plant Science (6.8k 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 Michael Levitt. 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.