2023 - Research.com Biology and Biochemistry in United States Leader Award
2022 - Research.com Best Scientist Award
2014 - Member of the National Academy of Medicine (NAM)
2008 - E. Mead Johnson Award, Society for Pediatric Research
2007 - Paul Marks Prize for Cancer Research, Memorial Sloan Kettering Cancer Center
Member of the Association of American Physicians
Todd R. Golub mainly investigates Gene expression profiling, Genetics, Cancer research, Cancer and Gene. Todd R. Golub has included themes like Medical diagnosis, Bioinformatics, DNA microarray, Computational biology and Adenocarcinoma in his Gene expression profiling study. His Bioinformatics research incorporates themes from Cell cycle and Myeloid leukemia.
His Cancer research research integrates issues from Janus kinase 2, Cancer stem cell, Leukemia, Immunology and MAPK/ERK pathway. His work carried out in the field of Cancer brings together such families of science as Mutation, Fusion gene and PTEN. His studies in RNA interference integrate themes in fields like Gene silencing and microRNA.
His primary areas of investigation include Cancer research, Genetics, Gene, Gene expression profiling and Cancer. His Cancer research study combines topics from a wide range of disciplines, such as Leukemia, Immunology, Transcription factor and Cellular differentiation. He interconnects Molecular biology and Computational biology in the investigation of issues within Gene.
Todd R. Golub has researched Computational biology in several fields, including Cancer cell and CRISPR. His Gene expression profiling study also includes
Todd R. Golub mainly focuses on Cancer research, Cancer, Computational biology, Gene and Genetics. The various areas that Todd R. Golub examines in his Cancer research study include Cell culture, Cell, Carcinogenesis, Mutation and RNA interference. Todd R. Golub regularly ties together related areas like Bioinformatics in his Cancer studies.
His Computational biology research includes themes of Gene expression, Gene expression profiling, Genome editing, CRISPR and Genomics. Todd R. Golub works mostly in the field of Gene, limiting it down to topics relating to Dependency and, in certain cases, Replication and Pan cancer. His work deals with themes such as Gene silencing and microRNA, which intersect with RNA.
His scientific interests lie mostly in Cancer research, Computational biology, Cancer, Genetics and Gene. His studies deal with areas such as Cellular differentiation, Carcinogenesis, DNA mismatch repair, Histone deacetylase and Neuroblastoma as well as Cancer research. The Computational biology study combines topics in areas such as International Prognostic Index, CRISPR, Somatic cell, Gene expression profiling and Marginal zone.
His Gene expression profiling research includes elements of Phenotype, Kinase, Cell cycle, Transcription and Cytostasis. His work in the fields of Cancer, such as Human cancer, intersects with other areas such as Gammaproteobacteria. Todd R. Golub combines subjects such as Dependency, Breast cancer and Data mining with his study of Gene.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Aravind Subramanian;Pablo Tamayo;Vamsi K. Mootha;Sayan Mukherjee.
Proceedings of the National Academy of Sciences of the United States of America (2005)
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
T. R. Golub;T. R. Golub;D. K. Slonim;P. Tamayo;C. Huard.
MicroRNA expression profiles classify human cancers
Jun Lu;Gad Getz;Eric A. Miska;Eric A. Miska;Ezequiel Alvarez-Saavedra.
Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1
Roel G. W. Verhaak;Katherine A. Hoadley;Elizabeth Purdom;Victoria Wang.
Cancer Cell (2010)
PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes
Vamsi K Mootha;Cecilia M Lindgren;Cecilia M Lindgren;Karl-Fredrik Eriksson;Aravind Subramanian.
Nature Genetics (2003)
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Jordi Barretina;Giordano Caponigro;Nicolas Stransky;Kavitha Venkatesan.
Comprehensive genomic characterization defines human glioblastoma genes and core pathways
Roger McLendon;Allan Friedman;Darrell Bigner;Erwin G. Van Meir.
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Michael S. Lawrence;Petar Stojanov;Petar Stojanov;Paz Polak;Paz Polak;Paz Polak;Gregory V. Kryukov;Gregory V. Kryukov;Gregory V. Kryukov.
The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease
Justin Lamb;Emily D. Crawford;David Peck;Joshua W. Modell.
Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation
Pablo Tamayo;Donna Slonim;Jill Mesirov;Qing Zhu.
Proceedings of the National Academy of Sciences of the United States of America (1999)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: