Institution
Broad Institute
Nonprofit•Cambridge, Massachusetts, United States•
About: Broad Institute is a nonprofit organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 6584 authors who have published 11618 publications receiving 1522743 citations. The organization is also known as: Eli and Edythe L. Broad Institute of MIT and Harvard.
Topics: Population, Genome-wide association study, Genome, Gene, Chromatin
Papers published on a yearly basis
Papers
More filters
••
University of Bonn1, Radboud University Nijmegen2, University of Chicago3, Université de Montréal4, Dresden University of Technology5, University of Edinburgh6, McGill University Health Centre7, McGill University8, Rockefeller University9, University of Cape Town10, Instituto de Medicina Molecular11, Eindhoven University of Technology12, Icahn School of Medicine at Mount Sinai13, University of Southern Denmark14, Memorial Sloan Kettering Cancer Center15, Cornell University16, Harvard University17, Broad Institute18, German Center for Neurodegenerative Diseases19, University of Massachusetts Medical School20
TL;DR: A group of leaders in the field define ‘trained immunity’ as a biological process and discuss the innate stimuli and the epigenetic and metabolic reprogramming events that shape the induction of trained immunity.
Abstract: Immune memory is a defining feature of the acquired immune system, but activation of the innate immune system can also result in enhanced responsiveness to subsequent triggers. This process has been termed 'trained immunity', a de facto innate immune memory. Research in the past decade has pointed to the broad benefits of trained immunity for host defence but has also suggested potentially detrimental outcomes in immune-mediated and chronic inflammatory diseases. Here we define 'trained immunity' as a biological process and discuss the innate stimuli and the epigenetic and metabolic reprogramming events that shape the induction of trained immunity.
1,116 citations
••
TL;DR: This Review focuses on the methodological considerations for characterizing somatic genome alterations in cancer and the future prospects for these approaches.
Abstract: Cancer is fundamentally a disease of the genome and so high-throughput sequencing technologies offer great potential for improving our understanding of the biology and treatment of cancer Experimental strategies, computational approaches and cancer-specific considerations for detecting different types of genomic alterations are discussed Cancers are caused by the accumulation of genomic alterations Therefore, analyses of cancer genome sequences and structures provide insights for understanding cancer biology, diagnosis and therapy The application of second-generation DNA sequencing technologies (also known as next-generation sequencing) — through whole-genome, whole-exome and whole-transcriptome approaches — is allowing substantial advances in cancer genomics These methods are facilitating an increase in the efficiency and resolution of detection of each of the principal types of somatic cancer genome alterations, including nucleotide substitutions, small insertions and deletions, copy number alterations, chromosomal rearrangements and microbial infections This Review focuses on the methodological considerations for characterizing somatic genome alterations in cancer and the future prospects for these approaches
1,114 citations
01 Nov 2015
TL;DR: A genome-wide single-guide RNA library is constructed to screen for genes required for proliferation and survival in a human cancer cell line and reveals a set of cell-essential genes, which was validated with an orthogonal gene-trap–based screen and comparison with yeast gene knockouts.
Abstract: Large-scale genetic analysis of lethal phenotypes has elucidated the molecular underpinnings of many biological processes. Using the bacterial clustered regularly interspaced short palindromic repeats (CRISPR) system, we constructed a genome-wide single-guide RNA library to screen for genes required for proliferation and survival in a human cancer cell line. Our screen revealed the set of cell-essential genes, which was validated with an orthogonal gene-trap-based screen and comparison with yeast gene knockouts. This set is enriched for genes that encode components of fundamental pathways, are expressed at high levels, and contain few inactivating polymorphisms in the human population. We also uncovered a large group of uncharacterized genes involved in RNA processing, a number of whose products localize to the nucleolus. Last, screens in additional cell lines showed a high degree of overlap in gene essentiality but also revealed differences specific to each cell line and cancer type that reflect the developmental origin, oncogenic drivers, paralogous gene expression pattern, and chromosomal structure of each line. These results demonstrate the power of CRISPR-based screens and suggest a general strategy for identifying liabilities in cancer cells.
1,113 citations
••
TL;DR: Features of brain organization are revealed, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions.
1,110 citations
••
[...]
TL;DR: A new version of the Java based software (GSEA-P 2.0) is reported that represents a major improvement on the previous release through the addition of a leading edge analysis component, seamless integration with the Molecular Signature Database (MSigDB) and an embedded browser that allows users to search for gene sets and map them to a variety of microarray platform formats.
Abstract: Gene Set Enrichment Analysis (GSEA) is a computational method that assesses whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states. We report the availability of a new version of the Java based software (GSEA-P 2.0) that represents a major improvement on the previous release through the addition of a leading edge analysis component, seamless integration with the Molecular Signature Database (MSigDB) and an embedded browser that allows users to search for gene sets and map them to a variety of microarray platform formats. This functionality makes it possible for users to directly import gene sets from MSigDB for analysis with GSEA. We have also improved the visualizations in GSEA-P 2.0 and added links to a new form of concise gene set annotations called Gene Set Cards. These additions, as well as other improvements suggested by over 3500 users who have downloaded the software over the past year have been incorporated into this new release of the GSEA-P Java desktop program.
Availability:GSEA-P 2.0 is freely available for academic and commercial users and can be downloaded from http://www.broad.mit.edu/GSEA
Contact: mesirov@broad.mit.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
1,107 citations
Authors
Showing all 7146 results
Name | H-index | Papers | Citations |
---|---|---|---|
Eric S. Lander | 301 | 826 | 525976 |
Albert Hofman | 267 | 2530 | 321405 |
Frank B. Hu | 250 | 1675 | 253464 |
David J. Hunter | 213 | 1836 | 207050 |
Kari Stefansson | 206 | 794 | 174819 |
Mark J. Daly | 204 | 763 | 304452 |
Lewis C. Cantley | 196 | 748 | 169037 |
Matthew Meyerson | 194 | 553 | 243726 |
Gad Getz | 189 | 520 | 247560 |
Stacey Gabriel | 187 | 383 | 294284 |
Stuart H. Orkin | 186 | 715 | 112182 |
Ralph Weissleder | 184 | 1160 | 142508 |
Chris Sander | 178 | 713 | 233287 |
Michael I. Jordan | 176 | 1016 | 216204 |
Richard A. Young | 173 | 520 | 126642 |