Jared Flatow
Impact in
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- Bioinformatics and Genomic Networks
- Biomedical Text Mining and Ontologies
- Genomics and Chromatin Dynamics
- Gene expression and cancer classification
- RNA and protein synthesis mechanisms
- Renal and related cancers
Papers in ⓘ
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- Bioinformatics and Genomic Networks 4
- Genomics and Phylogenetic Studies 3
- Biomedical Text Mining and Ontologies 3
- Genetics, Bioinformatics, and Biomedical Research 2
- RNA and protein synthesis mechanisms 2
- Protein Degradation and Inhibitors 1
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- Parvovirus B19 Infection Studies 1
- Co-authors
- Michelle Holko (3 shared papers)Simon Lin (3 shared papers)Gang Feng (2 shared papers)Warren A. Kibbe (3 shared papers)John D. Osborne (2 shared papers)Rex L. Chisholm (1 shared paper)Maria I. Danila (1 shared paper)Lihua Julie Zhu (2 shared papers)
- Journals
- BMC Genomics (1 paper)Advances in experimental medicine and biology (1 paper)RNA (1 paper)BMC Bioinformatics (1 paper)The Journal of Infectious Diseases (1 paper)
- Partner nations
- United StatesNew ZealandCanada
In The Last Decade
Jared Flatow
10 papers receiving 645 citations
Peers
Comparison fields: 5 of 87
- Molecular Biology 501
- Aging 8
- Hematology 45
- Genetics 82
- Computational Theory and Mathematics 40
Countries citing papers authored by Jared Flatow
This map shows the geographic impact of Jared Flatow'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 Jared Flatow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jared Flatow more than expected).
Fields of papers citing papers by Jared Flatow
This network shows the impact of papers produced by Jared Flatow. 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 Jared Flatow. The network helps show where Jared Flatow may publish in the future.
Co-authors
The 25 scholars most cited alongside Jared Flatow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 206 | |
| 2 | 2010 | 105 | |
| 3 | 2011 | 99 | |
| 4 | 2009 | 91 | |
| 5 | 2009 | 60 | |
| 6 | 2009 | 43 | |
| 7 | Annotating the human genome with Disease | 2009 | 20 |
| 8 | 2012 | 19 | |
| 9 | 2011 | 14 | |
| 10 | 2010 | 4 |
About Jared Flatow
Jared Flatow is a scholar working on Molecular Biology, Infectious Diseases, Surgery, Computer Networks and Communications and Information Systems, having authored 10 papers that have together received 661 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Genomics and Phylogenetic Studies (3 papers), Biomedical Text Mining and Ontologies (3 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), RNA and protein synthesis mechanisms (2 papers), Protein Degradation and Inhibitors (1 paper), Cloud Computing and Resource Management (1 paper) and Parvovirus B19 Infection Studies (1 paper). The work is most often cited by research in Molecular Biology (501 citations), Aging (8 citations), Hematology (45 citations), Genetics (82 citations) and Computational Theory and Mathematics (40 citations). Jared Flatow has collaborated with scholars based in United States, New Zealand and Canada. Frequent co-authors include Michelle Holko, Simon Lin, Gang Feng, Warren A. Kibbe, John D. Osborne, Rex L. Chisholm, Maria I. Danila, Lihua Julie Zhu, Yvonne Fondufe‐Mittendorf and Liqun Xi. Their work appears in journals such as BMC Genomics, Advances in experimental medicine and biology, RNA, BMC Bioinformatics and The Journal of Infectious Diseases.
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.