Gary D. Bader
- Molecular Biology top 0.05%
- Bioinformatics and Genomic Networks 85
- Microbial Metabolic Engineering and Bioproduction 28
- Gene expression and cancer classification 25
- Single-cell and spatial transcriptomics 21
- Gene Regulatory Network Analysis 19
- Protein Structure and Dynamics 13
- Ubiquitin and proteasome pathways 12
- Cancer Research top 0.2%
- Cancer Genomics and Diagnostics 15
- Aging top 0.5%
- Computational Theory and Mathematics top 0.1%
- Cell Biology top 0.5%
- Co-authors
- Christopher W.V. HogueRuth IsserlinMax FranzChristian LopesQuaid MorrisDaniele MericoJason MontojoKhalid Zuberi
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Gary D. Bader
208 papers receiving 31.3k citations
Hit Papers
Peers
Comparison fields: 5 of 202
- Molecular Biology 22.9k
- Cancer Research 4.4k
- Aging 373
- Computational Theory and Mathematics 2.6k
- Cell Biology 2.1k
Countries citing papers authored by Gary D. Bader
This map shows the geographic impact of Gary D. Bader'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 Gary D. Bader with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary D. Bader more than expected).
Fields of papers citing papers by Gary D. Bader
This network shows the impact of papers produced by Gary D. Bader. 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 Gary D. Bader. The network helps show where Gary D. Bader may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gary D. Bader, 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 | 1 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 86 | |
| 4 | 2023 | 5 | |
| 5 | 2021 | 7 | |
| 6 | 2021 | 1 | |
| 7 | DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representationsbreakdown → | 2021 | 243 |
| 8 | 2020 | 64 | |
| 9 | 2019 | 51 | |
| 10 | 2019 | 64 | |
| 11 | 2019 | 58 | |
| 12 | Single-cell transcriptomic profiling of the aging mouse brainbreakdown → | 2019 | 439 |
| 13 | 2018 | 106 | |
| 14 | 2017 | 28 | |
| 15 | 2014 | 21 | |
| 16 | 2011 | 40 | |
| 17 | 2010 | 97 | |
| 18 | 2010 | 130 | |
| 19 | 2009 | 78 | |
| 20 | Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutantsbreakdown → | 2001 | 1620 |
About Gary D. Bader
Gary D. Bader is a scholar working on Molecular Biology, Aging and Cancer Research, having authored 211 papers that have together received 31.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (85 papers), Microbial Metabolic Engineering and Bioproduction (28 papers), Gene expression and cancer classification (25 papers), Single-cell and spatial transcriptomics (21 papers), Gene Regulatory Network Analysis (19 papers), Cancer Genomics and Diagnostics (15 papers), Protein Structure and Dynamics (13 papers) and Ubiquitin and proteasome pathways (12 papers). The work is most often cited by research in Molecular Biology (22.9k citations), Cancer Research (4.4k citations) and Aging (373 citations). Gary D. Bader has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Christopher W.V. Hogue, Ruth Isserlin, Max Franz, Christian Lopes, Quaid Morris, Daniele Merico, Jason Montojo, Khalid Zuberi, Jüri Reimand and Sylva L. Donaldson. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, Blood, BMC Bioinformatics and Molecular Systems 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.