Gary D. Bader
Impact in
- Molecular Biology top 0.05%
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Microbial Metabolic Engineering and Bioproduction
- RNA modifications and cancer
- Gene Regulatory Network Analysis
- Fungal and yeast genetics research
- Cancer Research top 0.2%
- Cancer-related molecular mechanisms research
Papers in
-
- Bioinformatics and Genomic Networks 77
- Microbial Metabolic Engineering and Bioproduction 26
- Single-cell and spatial transcriptomics 21
- Gene expression and cancer classification 17
- Gene Regulatory Network Analysis 16
- Ubiquitin and proteasome pathways 11
- Protein Structure and Dynamics 11
-
- Cancer Genomics and Diagnostics 14
- Co-authors
- Christopher W.V. Hogue (9 shared papers)Ruth Isserlin (24 shared papers)Max Franz (10 shared papers)Christian Lopes (8 shared papers)Quaid Morris (7 shared papers)Daniele Merico (8 shared papers)Jason Montojo (5 shared papers)Khalid Zuberi (5 shared papers)
- Journals
- Bioinformatics (16 papers)Blood (10 papers)Nucleic Acids Research (10 papers)BMC Bioinformatics (8 papers)Molecular Systems Biology (7 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Gary D. Bader
211 papers receiving 32.9k citations
Gary D. Bader's Hit Papers
Peers
Comparison fields: 5 of 207
- Molecular Biology 21.4k
- Cancer Research 3.6k
- Aging 351
- Computational Theory and Mathematics 2.3k
- Cell Biology 2.0k
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-authors
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
Showing the 20 most-cited of 216 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | An automated method for finding molecular complexes in large protein interaction networks Hit paper breakdown → | 2003 | 4600 |
| 2 | The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function Hit paper breakdown → | 2010 | 3365 |
| 3 | Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants Hit paper breakdown → | 2001 | 1689 |
| 4 | Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation Hit paper breakdown → | 2010 | 1540 |
| 5 | BIND--The Biomolecular Interaction Network Database Hit paper breakdown → | 2001 | 1324 |
| 6 | Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap Hit paper breakdown → | 2019 | 1195 |
| 7 | A travel guide to Cytoscape plugins Hit paper breakdown → | 2012 | 1193 |
| 8 | GeneMANIA update 2018 Hit paper breakdown → | 2018 | 910 |
| 9 | BIND: the Biomolecular Interaction Network Database Hit paper breakdown → | 2003 | 905 |
| 10 | Pathway Commons, a web resource for biological pathway data Hit paper breakdown → | 2010 | 821 |
| 11 | Biological Network Exploration with Cytoscape 3 Hit paper breakdown → | 2014 | 794 |
| 12 | Cytoscape Web: an interactive web-based network browser Hit paper breakdown → | 2010 | 597 |
| 13 | A Combined Experimental and Computational Strategy to Define Protein Interaction Networks for Peptide Recognition Modules Hit paper breakdown → | 2002 | 579 |
| 14 | Cytoscape.js: a graph theory library for visualisation and analysis Hit paper breakdown → | 2015 | 494 |
| 15 | 2010 | 492 | |
| 16 | Single-cell transcriptomic profiling of the aging mouse brain Hit paper breakdown → | 2019 | 469 |
| 17 | 2011 | 464 | |
| 18 | 2002 | 434 | |
| 19 | 2008 | 378 | |
| 20 | 2013 | 376 |
About Gary D. Bader
Gary D. Bader is a scholar working on Molecular Biology, Cancer Research, Oncology, Genetics and Hematology, having authored 216 papers that have together received 33.4k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (77 papers), Microbial Metabolic Engineering and Bioproduction (26 papers), Single-cell and spatial transcriptomics (21 papers), Gene expression and cancer classification (17 papers), Gene Regulatory Network Analysis (16 papers), Cancer Genomics and Diagnostics (14 papers), Ubiquitin and proteasome pathways (11 papers) and Protein Structure and Dynamics (11 papers). The work is most often cited by research in Molecular Biology (21.4k citations), Cancer Research (3.6k citations), Aging (351 citations), Computational Theory and Mathematics (2.3k citations) and Cell Biology (2.0k 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, Blood, Nucleic Acids Research, 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.