Avi Ma’ayan
- Immunology top 0.2%
- Molecular Biology top 0.1%
- Bioinformatics and Genomic Networks 76
- Gene expression and cancer classification 37
- Gene Regulatory Network Analysis 37
- Single-cell and spatial transcriptomics 12
- Biomedical Text Mining and Ontologies 11
- RNA modifications and cancer 10
- Cancer Research top 0.2%
- Genetics top 0.2%
- Hematology top 0.2%
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- Computational Drug Discovery Methods 33
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- Renal Diseases and Glomerulopathies 11
- Co-authors
- Zichen WangAlexander LachmannQiaonan DuanNeil R. ClarkKathleen M. JagodnikNicolas FernandezYan KouEdward Y. Chen
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Avi Ma’ayan
183 papers receiving 29.2k citations
Hit Papers
Peers
Comparison fields: 5 of 193
- Immunology 5.2k
- Molecular Biology 16.8k
- Cancer Research 3.6k
- Genetics 2.2k
- Hematology 2.1k
Countries citing papers authored by Avi Ma’ayan
This map shows the geographic impact of Avi Ma’ayan'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 Avi Ma’ayan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Avi Ma’ayan more than expected).
Fields of papers citing papers by Avi Ma’ayan
This network shows the impact of papers produced by Avi Ma’ayan. 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 Avi Ma’ayan. The network helps show where Avi Ma’ayan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Avi Ma’ayan, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 28 | |
| 5 | 2024 | 11 | |
| 6 | 2023 | 78 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 4 | |
| 10 | 2021 | 15 | |
| 11 | 2021 | 48 | |
| 12 | 2019 | 74 | |
| 13 | 2018 | 19 | |
| 14 | 2018 | 76 | |
| 15 | 2017 | 22 | |
| 16 | 2015 | 65 | |
| 17 | 2011 | 13 | |
| 18 | 2010 | 164 | |
| 19 | ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experimentsbreakdown → | 2010 | 677 |
| 20 | 2008 | 40 |
About Avi Ma’ayan
Avi Ma’ayan is a scholar working on Molecular Biology, Computational Theory and Mathematics and Biophysics, having authored 186 papers that have together received 29.4k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (76 papers), Gene expression and cancer classification (37 papers), Gene Regulatory Network Analysis (37 papers), Computational Drug Discovery Methods (33 papers), Single-cell and spatial transcriptomics (12 papers), Renal Diseases and Glomerulopathies (11 papers), Biomedical Text Mining and Ontologies (11 papers) and RNA modifications and cancer (10 papers). The work is most often cited by research in Immunology (5.2k citations), Molecular Biology (16.8k citations) and Cancer Research (3.6k citations). Avi Ma’ayan has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Zichen Wang, Alexander Lachmann, Qiaonan Duan, Neil R. Clark, Kathleen M. Jagodnik, Nicolas Fernandez, Yan Kou, Edward Y. Chen, Sherry L. Jenkins and Maxim V. Kuleshov. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, BMC Bioinformatics, Science Signaling and Nature Communications.
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.