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Michael Snyder

Researcher at Stanford University

Publications -  938
Citations -  150929

Michael Snyder is an academic researcher from Stanford University. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 169, co-authored 840 publications receiving 130225 citations. Previous affiliations of Michael Snyder include Wyss Institute for Biologically Inspired Engineering & Public Health Research Institute.

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MOTIPS: automated motif analysis for predicting targets of modular protein domains.

TL;DR: An efficient search algorithm is developed to scan the target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder to demonstrate a notably improved prediction of modular protein domain targets.
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The alpha-factor receptor C-terminus is important for mating projection formation and orientation in Saccharomyces cerevisiae.

TL;DR: A complex role for the Ste2p carboxy-terminal tail in the formation, orientation, and directional adjustment of the mating projection, and that endocytosis of the receptor is important for this process are suggested.
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Long-read sequencing of the human cytomegalovirus transcriptome with the Pacific Biosciences RSII platform.

TL;DR: This work presents a long-read RNA sequencing dataset of HCMV infected human lung fibroblast cells sequenced by the Pacific Biosciences RSII platform, which contains 122,636 human and 33,086 viral reads.
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Spindle checkpoint maintenance requires Ame1 and Okp1.

TL;DR: It is proposed that Ame1 and Okp1 are required for a sustained checkpoint arrest in the presence of mis-segregated chromosomes and the results suggest that checkpoint response might be controlled not only at the level of activation but also via signals that ensure maintenance of the response.
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Predicting Ovarian Cancer Patients’ Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures

TL;DR: It is demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics.