What is he best known for?
The fields of study he is best known for:
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 most cited work include:
- Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles (22405 citations)
- Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. (11046 citations)
- Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. (11046 citations)
What are the main themes of his work throughout his whole career to date?
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
- Regulation of gene expression that connect with fields like Cell biology,
- microRNA which is related to area like Gene silencing.
Cancer is closely attributed to Oncology in his study.
He most often published in these fields:
- Cancer research (65.40%)
- Genetics (45.71%)
- Gene (42.62%)
What were the highlights of his more recent work (between 2016-2021)?
- Cancer research (65.40%)
- Cancer (27.29%)
- Computational biology (30.52%)
In recent papers he was focusing on the following fields of study:
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.
Between 2016 and 2021, his most popular works were:
- A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. (857 citations)
- Defining a Cancer Dependency Map (689 citations)
- Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells. (595 citations)
In his most recent research, the most cited papers focused on:
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.
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