David Pellow
Impact in
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria
- Artificial Intelligence top 10%
- Algorithms and Data Compression
- Text Readability and Simplification
Papers in
-
- Algorithms and Data Compression 7
- Text Readability and Simplification 1
-
- Genomics and Phylogenetic Studies 4
- Gut microbiota and health 1
- Co-authors
- Ron Shamir A (9 shared papers)Carl Kingsford (5 shared papers)Guillaume Marçais (3 shared papers)Yaron Orenstein (3 shared papers)Maxine Eskénazi (2 shared papers)Itzhak Mizrahi (3 shared papers)Alvah Zorea (3 shared papers)Arik Segal (1 shared paper)
- Journals
- PLoS Computational Biology (3 papers)Microbiome (2 papers)Journal of Computational Biology (2 papers)Nature Communications (1 paper)Bioinformatics (1 paper)
- Partner nations
- IsraelUnited StatesIndia
In The Last Decade
David Pellow
13 papers receiving 309 citations
Peers
Comparison fields: 5 of 37
- Molecular Medicine 50
- Artificial Intelligence 126
- Pollution 30
- Molecular Biology 124
- Applied Microbiology and Biotechnology 4
Countries citing papers authored by David Pellow
This map shows the geographic impact of David Pellow'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 David Pellow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Pellow more than expected).
Fields of papers citing papers by David Pellow
This network shows the impact of papers produced by David Pellow. 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 David Pellow. The network helps show where David Pellow may publish in the future.
Co-authors
The 18 scholars most cited alongside David Pellow, 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 | 2020 | 86 | |
| 2 | 2021 | 48 | |
| 3 | 2017 | 47 | |
| 4 | 2017 | 33 | |
| 5 | 2016 | 23 | |
| 6 | 2014 | 18 | |
| 7 | 2016 | 18 | |
| 8 | 2024 | 17 | |
| 9 | 2022 | 12 | |
| 10 | 2016 | 4 | |
| 11 | 2022 | 4 | |
| 12 | 2014 | 2 | |
| 13 | 2025 | 1 |
About David Pellow
David Pellow is a scholar working on Artificial Intelligence, Molecular Biology, Computer Science Applications, Molecular Medicine and Genetics, having authored 13 papers that have together received 313 indexed citations. Recurring topics across this work include Algorithms and Data Compression (7 papers), Genomics and Phylogenetic Studies (4 papers), Bacterial Genetics and Biotechnology (2 papers), Text Readability and Simplification (1 paper), Mobile Crowdsensing and Crowdsourcing (1 paper), Microbial Community Ecology and Physiology (1 paper), Antibiotic Resistance in Bacteria (1 paper) and Gut microbiota and health (1 paper). The work is most often cited by research in Molecular Medicine (50 citations), Artificial Intelligence (126 citations), Pollution (30 citations), Molecular Biology (124 citations) and Applied Microbiology and Biotechnology (4 citations). David Pellow has collaborated with scholars based in Israel, United States and India. Frequent co-authors include Ron Shamir A, Carl Kingsford, Guillaume Marçais, Yaron Orenstein, Maxine Eskénazi, Itzhak Mizrahi, Alvah Zorea, Arik Segal, Darya Filippova and Maraike Probst. Their work appears in journals such as PLoS Computational Biology, Microbiome, Journal of Computational Biology, Nature Communications and Bioinformatics.
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.