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Institution

Icahn School of Medicine at Mount Sinai

EducationNew York, New York, United States
About: Icahn School of Medicine at Mount Sinai is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 37488 authors who have published 76057 publications receiving 3704104 citations. The organization is also known as: Mount Sinai School of Medicine.


Papers
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Journal ArticleDOI
TL;DR: Crucially, ablation of different senescence effectors improves the efficiency of reprogramming, suggesting novel strategies for maximizing the generation of iPS cells.
Abstract: Somatic cells can be reprogrammed into induced pluripotent stem (iPS) cells by overexpressing combinations of factors such as Oct4, Sox2, Klf4, and c-Myc. Reprogramming is slow and stochastic, suggesting the existence of barriers limiting its efficiency. Here we identify senescence as one such barrier. Expression of the four reprogramming factors triggers senescence by up-regulating p53, p16INK4a, and p21CIP1. Induction of DNA damage response and chromatin remodeling of the INK4a/ARF locus are two of the mechanisms behind senescence induction. Crucially, ablation of different senescence effectors improves the efficiency of reprogramming, suggesting novel strategies for maximizing the generation of iPS cells.

616 citations

Journal ArticleDOI
01 Jan 2019-Database
TL;DR: An online database, PanglaoDB, accessible through a user-friendly interface that can be used to explore published mouse and human single cell RNA sequencing studies, and establishes a community-curated cell-type marker compendium, containing more than 6000 gene-cell-type associations, as a resource for automatic annotation of cell types.
Abstract: Single-cell RNA sequencing is an increasingly used method to measure gene expression at the single cell level and build cell-type atlases of tissues. Hundreds of single-cell sequencing datasets have already been published. However, studies are frequently deposited as raw data, a format difficult to access for biological researchers due to the need for data processing using complex computational pipelines. We have implemented an online database, PanglaoDB, accessible through a user-friendly interface that can be used to explore published mouse and human single cell RNA sequencing studies. PanglaoDB contains pre-processed and pre-computed analyses from more than 1054 single-cell experiments covering most major single cell platforms and protocols, based on more than 4 million cells from a wide range of tissues and organs. The online interface allows users to query and explore cell types, genetic pathways and regulatory networks. In addition, we have established a community-curated cell-type marker compendium, containing more than 6000 gene-cell-type associations, as a resource for automatic annotation of cell types.

615 citations

Journal ArticleDOI
TL;DR: The evolution, accomplishments, opportunities, and challenges of the network are described, from its inception as a five- group consortium focused on genotype–phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting toward the implementation of genomic medicine.

614 citations

Journal ArticleDOI
TL;DR: This randomised, open-label, phase 3 trial aimed to study whether the addition of bortezomib to lenalidomide and dexamethasone would improve progression-free survival and provide better response rates in patients with previously untreated multiple myeloma who were not planned for immediate autologous stem-cell transplant.

614 citations


Authors

Showing all 37948 results

NameH-indexPapersCitations
Robert Langer2812324326306
Shizuo Akira2611308320561
Gordon H. Guyatt2311620228631
Eugene Braunwald2301711264576
Bruce S. McEwen2151163200638
Robert J. Lefkowitz214860147995
Peter Libby211932182724
Mark J. Daly204763304452
Stuart H. Orkin186715112182
Paul G. Richardson1831533155912
Alan C. Evans183866134642
John C. Morris1831441168413
Paul M. Thompson1832271146736
Tadamitsu Kishimoto1811067130860
Bruce M. Psaty1811205138244
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023157
2022844
20217,117
20206,224
20195,200
20184,505