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Institution

Broad Institute

NonprofitCambridge, 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.


Papers
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Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
09 Aug 2018-Cell
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

Journal ArticleDOI

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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

NameH-indexPapersCitations
Eric S. Lander301826525976
Albert Hofman2672530321405
Frank B. Hu2501675253464
David J. Hunter2131836207050
Kari Stefansson206794174819
Mark J. Daly204763304452
Lewis C. Cantley196748169037
Matthew Meyerson194553243726
Gad Getz189520247560
Stacey Gabriel187383294284
Stuart H. Orkin186715112182
Ralph Weissleder1841160142508
Chris Sander178713233287
Michael I. Jordan1761016216204
Richard A. Young173520126642
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202337
2022627
20211,727
20201,534
20191,364
20181,107