Eric E. Bardes
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- Gene expression and cancer classification
- RNA Research and Splicing
- Epigenetics and DNA Methylation
- Single-cell and spatial transcriptomics
Papers in
-
- Bioinformatics and Genomic Networks 4
- Gene expression and cancer classification 2
- Gene Regulatory Network Analysis 2
- Single-cell and spatial transcriptomics 1
- Microbial Metabolic Engineering and Bioproduction 1
- Co-authors
- Anil G. Jegga (4 shared papers)Bruce J. Aronow (5 shared papers)Jing Chen (2 shared papers)Vinod Kaimal (1 shared paper)Scott Tabar (1 shared paper)Chao Wu (1 shared paper)Ranga Chandra Gudivada (1 shared paper)Vivek Kaimal (1 shared paper)
- Journals
- Nucleic Acids Research (3 papers)iScience (1 paper)Methods in molecular biology (1 paper)SSRN Electronic Journal (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Eric E. Bardes
6 papers receiving 2.4k citations
Eric E. Bardes's Hit Papers
Peers
Comparison fields: 5 of 135
- Cancer Research 388
- Molecular Biology 1.5k
- Genetics 379
- Biological Psychiatry 33
- Immunology 275
Countries citing papers authored by Eric E. Bardes
This map shows the geographic impact of Eric E. Bardes'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 Eric E. Bardes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric E. Bardes more than expected).
Fields of papers citing papers by Eric E. Bardes
This network shows the impact of papers produced by Eric E. Bardes. 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 Eric E. Bardes. The network helps show where Eric E. Bardes may publish in the future.
Co-authors
The 14 scholars most cited alongside Eric E. Bardes, 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 | ToppGene Suite for gene list enrichment analysis and candidate gene prioritization Hit paper breakdown → | 2009 | 2047 |
| 2 | 2010 | 275 | |
| 3 | 2010 | 19 | |
| 4 | 2014 | 17 | |
| 5 | 2021 | 12 | |
| 6 | 2021 | 1 |
About Eric E. Bardes
Eric E. Bardes is a scholar working on Molecular Biology, Infectious Diseases, Computational Theory and Mathematics, Genetics and Cancer Research, having authored 6 papers that have together received 2.4k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (2 papers), Gene Regulatory Network Analysis (2 papers), Single-cell and spatial transcriptomics (1 paper), Genetic Associations and Epidemiology (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper), Computational Drug Discovery Methods (1 paper) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Cancer Research (388 citations), Molecular Biology (1.5k citations), Genetics (379 citations), Biological Psychiatry (33 citations) and Immunology (275 citations). Eric E. Bardes has collaborated with scholars based in United States and Israel. Frequent co-authors include Anil G. Jegga, Bruce J. Aronow, Jing Chen, Vinod Kaimal, Scott Tabar, Chao Wu, Ranga Chandra Gudivada, Vivek Kaimal, Surbhi Bhatnagar and Marc E. Rothenberg. Their work appears in journals such as Nucleic Acids Research, iScience, Methods in molecular biology and SSRN Electronic Journal.
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.