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Daniel Himmelstein

Researcher at University of Pennsylvania

Publications -  55
Citations -  2806

Daniel Himmelstein is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 12, co-authored 53 publications receiving 1848 citations. Previous affiliations of Daniel Himmelstein include University of California, San Francisco & Dartmouth College.

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Opportunities and obstacles for deep learning in biology and medicine.

TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.
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Systematic integration of biomedical knowledge prioritizes drugs for repurposing.

TL;DR: In this article, an integrative network encoding knowledge from millions of biomedical studies is used to predict whether a compound treats a disease and improve the economy and success rate of drug approval.
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Sci-Hub provides access to nearly all scholarly literature.

TL;DR: For the first time, nearly all scholarly literature is available gratis to anyone with an Internet connection, suggesting the toll access business model may become unsustainable.
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Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes.

TL;DR: Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach for data integration across multiple domains.
Posted ContentDOI

Systematic integration of biomedical knowledge prioritizes drugs for repurposing

TL;DR: The ability to computationally predict whether a compound treats a disease would improve the economy and success rate of drug approval, and help prioritize drug repurposing candidates is described.