Daniel Himmelstein
Impact in
-
- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Biomedical Text Mining and Ontologies
- Gene Regulatory Network Analysis
Papers in
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- Biomedical Text Mining and Ontologies 10
- Bioinformatics and Genomic Networks 9
- Gene expression and cancer classification 6
- Genetics 7
- Genetic Associations and Epidemiology 4
- Co-authors
- Sergio E. Baranzini (9 shared papers)Casey S. Greene (14 shared papers)Antoine Lizée (2 shared papers)Kara Dolinski (1 shared paper)Aaron K. Wong (1 shared paper)Elena Zaslavsky (1 shared paper)Tilo Großer (1 shared paper)Arjun Krishnan (1 shared paper)
- Journals
- GigaScience (2 papers)eLife (2 papers)PLoS Computational Biology (2 papers)Scientific Data (2 papers)BioData Mining (2 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Daniel Himmelstein
46 papers receiving 1.5k citations
Daniel Himmelstein's Hit Papers
Peers
Comparison fields: 5 of 142
- Computational Theory and Mathematics 248
- Molecular Biology 847
- Statistics, Probability and Uncertainty 76
- Information Systems and Management 67
- Genetics 254
Countries citing papers authored by Daniel Himmelstein
This map shows the geographic impact of Daniel Himmelstein'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 Daniel Himmelstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Himmelstein more than expected).
Fields of papers citing papers by Daniel Himmelstein
This network shows the impact of papers produced by Daniel Himmelstein. 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 Daniel Himmelstein. The network helps show where Daniel Himmelstein may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Himmelstein, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Understanding multicellular function and disease with human tissue-specific networks Hit paper breakdown → | 2015 | 568 |
| 2 | Systematic integration of biomedical knowledge prioritizes drugs for repurposing Hit paper breakdown → | 2017 | 327 |
| 3 | 2015 | 114 | |
| 4 | 2018 | 102 | |
| 5 | 2010 | 59 | |
| 6 | 2016 | 53 | |
| 7 | 2020 | 49 | |
| 8 | 2009 | 42 | |
| 9 | 2019 | 40 | |
| 10 | 2020 | 39 | |
| 11 | 2015 | 30 | |
| 12 | 2017 | 29 | |
| 13 | 2011 | 20 | |
| 14 | 2022 | 14 | |
| 15 | 2024 | 12 | |
| 16 | 2022 | 7 | |
| 17 | 2016 | 7 | |
| 18 | 2021 | 7 | |
| 19 | 2016 | 6 | |
| 20 | 2022 | 4 |
About Daniel Himmelstein
Daniel Himmelstein is a scholar working on Molecular Biology, Genetics, Information Systems, Information Systems and Management and Artificial Intelligence, having authored 49 papers that have together received 1.6k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (10 papers), Bioinformatics and Genomic Networks (9 papers), Gene expression and cancer classification (6 papers), Genetic Associations and Epidemiology (4 papers), Research Data Management Practices (3 papers), scientometrics and bibliometrics research (3 papers), Computational Drug Discovery Methods (2 papers) and Web Data Mining and Analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (248 citations), Molecular Biology (847 citations), Statistics, Probability and Uncertainty (76 citations), Information Systems and Management (67 citations) and Genetics (254 citations). Daniel Himmelstein has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Sergio E. Baranzini, Casey S. Greene, Antoine Lizée, Kara Dolinski, Aaron K. Wong, Elena Zaslavsky, Tilo Großer, Arjun Krishnan, Daniel I. Chasman and Dexter Hadley. Their work appears in journals such as GigaScience, eLife, PLoS Computational Biology, Scientific Data and BioData Mining.
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.