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
Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project.
Gilbert S. Omenn,Gilbert S. Omenn,Lydie Lane,Christopher M. Overall,Ileana M. Cristea,Fernando J. Corrales,Cecilia Lindskog,Young Ki Paik,Jennifer E. Van Eyk,Siqi Liu,Stephen R. Pennington,Michael Snyder,Mark S. Baker,Nuno Bandeira,Ruedi Aebersold,Robert L. Moritz,Eric W. Deutsch +16 more
TL;DR: According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19,773 predicted proteins coded in the human genome.
Posted ContentDOI
A Quantitative Proteome Map of the Human Body
Lihua Jiang,Meng Wang,Shin Lin,Ruiqi Jian,Xiao Li,Joanne Chan,Huaying Fang,Guanlan Dong,Hua Tang,Michael Snyder +9 more
TL;DR: Quantitative proteome study of 32 human tissues and integrated analysis with transcriptome data revealed that understanding protein levels could provide in-depth knowledge to post transcriptional or translational regulations, human metabolism, secretome, and diseases.
Journal ArticleDOI
Copy Number Variation detection from 1000 Genomes project exon capture sequencing data
Jiantao Wu,Krzysztof R. Grzeda,Chip Stewart,Fabian Grubert,Alexander E. Urban,Michael Snyder,Gabor T. Marth +6 more
TL;DR: This study demonstrates that exonic sequencing datasets, collected both in population based and medical sequencing projects, will be a useful substrate for detecting genic CNV events, particularly deletions.
Journal ArticleDOI
STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
Konrad J. Karczewski,Guy Haskin Fernald,Alicia R. Martin,Michael Snyder,Nicholas P. Tatonetti,Joel T. Dudley +5 more
TL;DR: This work describes STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience to be used and is provided as a user-friendly interface in Amazon EC2.
Journal ArticleDOI
Yeast proteomics and protein microarrays
Rui Chen,Michael Snyder +1 more
TL;DR: Discovery of post-translational modification networks in protein microarray technology has profound impact on explicating biological processes with a proteomic point of view, which may lead to a better understanding of normal biological phenomena as well as various human diseases.