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
Association of Omics Features with Histopathology Patterns in Lung Adenocarcinoma.
TL;DR: An integrative histopathology-transcriptomics model is built to generate better prognostic predictions for stage I patients and investigate molecular mechanisms of pathology findings and enhance clinical prognostic prediction.
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EBNA1 regulates cellular gene expression by binding cellular promoters
Allon Canaan,Izhak Haviv,Alexander E. Urban,Vincent P. Schulz,Steve Hartman,Zhengdong D. Zhang,Dean Palejev,Albert B. Deisseroth,Jill Lacy,Michael Snyder,Mark Gerstein,Sherman M. Weissman +11 more
TL;DR: This work has examined the effect of EBNA1 on cellular gene expression by microarray analysis using the B cell BJAB and the epithelial 293 cell lines transfected withEBNA1 and correlated EBNA 1 bound promoters with changes in gene expression.
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The NUF1 gene encodes an essential coiled-coil related protein that is a potential component of the yeast nucleoskeleton.
TL;DR: Results indicate that NUF1 encodes an essential coiled-coil protein within the yeast nucleus; it is speculated thatNUF1 is a component of the yeast nucleoskeleton; and immunofluorescence results indicate that mammalian cells contain a NUF 1-related nuclear protein.
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The development of protein microarrays and their applications in DNA-protein and protein-protein interaction analyses of Arabidopsis transcription factors.
Wei Gong,Kun He,Kun He,Michael F. Covington,Savithramma P. Dinesh-Kumar,Michael Snyder,Stacey L. Harmer,Yu-Xian Zhu,Xing Wang Deng,Xing Wang Deng +9 more
TL;DR: It is shown that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions and offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale.
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Network analyses identify liver-specific targets for treating liver diseases
Sunjae Lee,Cheng Zhang,Zhengtao Liu,Martina Klevstig,Bani Mukhopadhyay,Mattias Bergentall,Resat Cinar,Marcus Ståhlman,Natasha Sikanic,Joshua K. Park,Sumit Deshmukh,Azadeh Harzandi,T.J.M. Kuijpers,Morten Grøtli,Simon J. Elsässer,Brian D. Piening,Michael Snyder,Ulf Smith,Jens Nielsen,Jens Nielsen,Fredrik Bäckhed,George Kunos,Mathias Uhlén,Jan Borén,Adil Mardinoglu,Adil Mardinoglu +25 more
TL;DR: Integrative network analyses identified liver‐specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenic, or to PKLR, patatin‐like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.