Live intent to amazon redshift11/30/2023 In the process, it created the world's first exascale distributed computing resource, enabling it to generate valuable scientific datasets of unprecedented size. During the COVID-19 epidemic, focused its resources on understanding the vulnerabilities in SARS-CoV-2, the virus that causes COVID-19 disease, and working closely with a number of experimental collaborators to accelerate progress toward effective therapies for treating COVID-19 and ending the pandemic. Run by the Consortium, a worldwide network of research laboratories focusing on a variety of different diseases, seeks to address problems in human health on a scale that is infeasible by another other means, sharing the results of these large-scale studies with the research community through peer-reviewed publications and publicly shared datasets. Granja, et al.Īlchemical free energy calculations biomolecular modeling coronavirus COVID-19 foldingathome health life sciences molecular dynamics protein SARS-CoV-2 simulations structural is a massively distributed computing project that uses biomolecular simulations to investigate the molecular origins of disease and accelerate the discovery of new therapies. The chromatin accessibility landscape of primary human cancers by M.Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas by Joshua D.Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Typesīy Katherine A.Broad Institute FireCloud by The Broad Institute of MIT & Harvard.TCGA Cancers Selected for Study by National Cancer Institute.The dataset contains open Clinical Supplement, Biospecimen Supplement, RNA-Seq Gene Expression Quantification, miRNA-Seq Isoform Expression Quantificati. TCGA has analyzed matched tumor and normal tissues from 11,000 patients, allowing for the comprehensive characterization of 33 cancer types and subtypes, including 10 rare cancers. The Cancer Genome Atlas (TCGA), a collaboration between the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI), aims to generate comprehensive, multi-dimensional maps of the key genomic changes in major types and subtypes of cancer. by Nassi TE, Ganglberger W, Sun H, Bucklin AA, Biswal S, van Putten MJAM, et al.Ĭancer genomic life sciences STRIDES whole genome sequencing IEEE Transactions on Biomedical Engineering. Automated Scoring of Respiratory Events in Sleep with a Single Effort Belt and Deep Neural Networks. by Paixao L, Sikka P, Sun H, Jain A, Hogan J, Thomas RJ, et al. Excess Brain Age Reflected in the Electroencephalogram of Sleep Predicts Reduced Life Expectancy.by Bucklin AA, Ganglberger W, Quadri SA, Tesh RA, Adra N, Da Silva Cardoso M, et al. High prevalence of sleep-disordered breathing in the intensive care unit - a cross-sectional study.PMID: 36448766.* by Ye E*, Sun H*, Krishnamurthy PV, Adra N, Ganglberger W, Thomas RJ, et al. Dementia Detection from Brain Activity During Sleep.by Chu-Shore C, Kramer MA, Pathmanathan J, Bianchi MT, Westover MB, Wizon L, et al. Emergence of stable functional networks in long-term human EEG.This data is being used to develop CAISR (Complete AI Sleep Report), a collection of deep neural networks, rule-based algorithms, and signal processing approaches designed to provide better-than-human detection of conventional PSG. Beginning with PSG recordings from from ~15K patients evaluated at the Massachusetts General Hospital, the HSP will grow over the coming years to include data from >200K patients, as well as people evaluated outside of the clinical setting. The Human Sleep Project (HSP) sleep physiology dataset is a growing collection of clinical polysomnography (PSG) recordings. Bioinformatics deep learning life sciences machine learning medicine neurophysiology neuroscience
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