Pablo Tamayo
Impact in
- Cancer Research top 0.01%
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
- Molecular Biology top 0.01%
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- RNA Research and Splicing
Papers in
-
- Gene expression and cancer classification 35
- Bioinformatics and Genomic Networks 20
- Genomics and Chromatin Dynamics 16
- Single-cell and spatial transcriptomics 9
- RNA Research and Splicing 8
- RNA modifications and cancer 8
- Oncology 22
- Co-authors
- Jill P. Mesirov (56 shared papers)Todd R. Golub (21 shared papers)Eric S. Lander (11 shared papers)Aravind Subramanian (4 shared papers)Sayan Mukherjee (5 shared papers)Scott L. Pomeroy (11 shared papers)Benjamin L. Ebert (6 shared papers)Michael A. Gillette (3 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (11 papers)Cancer Research (9 papers)Journal of Statistical Physics (6 papers)Journal of Clinical Oncology (5 papers)Bioinformatics (5 papers)
- Partner nations
- United StatesGermanyChina
In The Last Decade
Pablo Tamayo
145 papers receiving 72.7k citations
Pablo Tamayo's Hit Papers
Peers
Comparison fields: 5 of 218
- Cancer Research 14.4k
- Molecular Biology 48.4k
- Immunology 9.9k
- Oncology 11.6k
- Genetics 3.3k
Countries citing papers authored by Pablo Tamayo
This map shows the geographic impact of Pablo Tamayo'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 Pablo Tamayo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pablo Tamayo more than expected).
Fields of papers citing papers by Pablo Tamayo
This network shows the impact of papers produced by Pablo Tamayo. 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 Pablo Tamayo. The network helps show where Pablo Tamayo may publish in the future.
Co-authors
The 25 scholars most cited alongside Pablo Tamayo, 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 149 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles Hit paper breakdown → | 2005 | 33983 |
| 2 | Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring Hit paper breakdown → | 1999 | 8040 |
| 3 | The Molecular Signatures Database Hallmark Gene Set Collection Hit paper breakdown → | 2015 | 7058 |
| 4 | Molecular signatures database (MSigDB) 3.0 Hit paper breakdown → | 2011 | 3978 |
| 5 | Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation Hit paper breakdown → | 1999 | 2148 |
| 6 | Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning Hit paper breakdown → | 2002 | 1842 |
| 7 | Gene expression correlates of clinical prostate cancer behavior Hit paper breakdown → | 2002 | 1823 |
| 8 | Multiclass cancer diagnosis using tumor gene expression signatures Hit paper breakdown → | 2001 | 1458 |
| 9 | Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data Hit paper breakdown → | 2003 | 1365 |
| 10 | Metagenes and molecular pattern discovery using matrix factorization Hit paper breakdown → | 2004 | 1310 |
| 11 | GSEA-P: a desktop application for Gene Set Enrichment Analysis Hit paper breakdown → | 2007 | 1013 |
| 12 | Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Hit paper breakdown → | 2003 | 719 |
| 13 | Expression analysis with oligonucleotide microarrays reveals that MYC regulates genes involved in growth, cell cycle, signaling, and adhesion Hit paper breakdown → | 2000 | 667 |
| 14 | Identification of RPS14 as a 5q- syndrome gene by RNA interference screen Hit paper breakdown → | 2008 | 629 |
| 15 | Chemosensitivity prediction by transcriptional profiling Hit paper breakdown → | 2001 | 532 |
| 16 | 2010 | 476 | |
| 17 | 2007 | 439 | |
| 18 | 2000 | 432 | |
| 19 | 2009 | 416 | |
| 20 | A Melanoma Cell State Distinction Influences Sensitivity to MAPK Pathway Inhibitors Hit paper breakdown → | 2014 | 357 |
About Pablo Tamayo
Pablo Tamayo is a scholar working on Molecular Biology, Oncology, Condensed Matter Physics, Cancer Research and Immunology, having authored 149 papers that have together received 74.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (35 papers), Theoretical and Computational Physics (21 papers), Bioinformatics and Genomic Networks (20 papers), Genomics and Chromatin Dynamics (16 papers), Stochastic processes and statistical mechanics (10 papers), Single-cell and spatial transcriptomics (9 papers), RNA Research and Splicing (8 papers) and RNA modifications and cancer (8 papers). The work is most often cited by research in Cancer Research (14.4k citations), Molecular Biology (48.4k citations), Immunology (9.9k citations), Oncology (11.6k citations) and Genetics (3.3k citations). Pablo Tamayo has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Jill P. Mesirov, Todd R. Golub, Eric S. Lander, Aravind Subramanian, Sayan Mukherjee, Scott L. Pomeroy, Benjamin L. Ebert, Michael A. Gillette, Vamsi K. Mootha and Amanda G. Paulovich. Their work appears in journals such as Proceedings of the National Academy of Sciences, Cancer Research, Journal of Statistical Physics, Journal of Clinical Oncology 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.