M
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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Journal ArticleDOI
Dynamic Human Environmental Exposome Revealed by Longitudinal Personal Monitoring
TL;DR: It is demonstrated that human exposomes are diverse, dynamic, spatiotemporally-driven interaction networks with the potential to impact human health.
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The nuclear-mitotic apparatus protein is important in the establishment and maintenance of the bipolar mitotic spindle apparatus.
C H Yang,Michael Snyder +1 more
TL;DR: It is demonstrated that microinjection of anti-NuMA antibodies into interphase and prophase cells results in a failure to form a mitotic spindle apparatus, and it is suggested that nonmicrotubule structural components may be important for these processes.
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The current excitement about copy-number variation: how it relates to gene duplications and protein families.
Jan O. Korbel,Philip M. Kim,Xueying Chen,Alexander E. Urban,Sherman M. Weissman,Michael Snyder,Mark Gerstein +6 more
TL;DR: CNVs tend to affect specific gene functional categories, such as those associated with environmental response, and are depleted in genes related to basic cellular processes, which means they occur more often at the periphery of the protein interaction network.
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Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping
Thomas Royce,Joel Rozowsky,Paul Bertone,Manoj P. Samanta,Viktor Stolc,Viktor Stolc,Sherman M. Weissman,Michael Snyder,Mark Gerstein +8 more
TL;DR: The informatics challenges arising in the analysis of tiling microarray experiments are introduced as open problems to the scientific community and initial approaches for the analysis are presented for this nascent technology.
Journal ArticleDOI
Metabolic Dynamics and Prediction of Gestational Age and Time to Delivery in Pregnant Women.
Liang Liang,Marie-Louise Hee Rasmussen,Brian D. Piening,Xiaotao Shen,Songjie Chen,Hannes L. Röst,John K. Snyder,Robert Tibshirani,Line Skotte,Norman Lee,Kévin Contrepois,Bjarke Feenstra,Hanyah Zackriah,Michael Snyder,Mads Melbye,Mads Melbye,Mads Melbye +16 more
TL;DR: This study represents a weekly characterization of the human pregnancy metabolome, providing a high-resolution landscape for understanding pregnancy with potential clinical utilities.