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Yuxing Liao

Researcher at Baylor College of Medicine

Publications -  23
Citations -  4246

Yuxing Liao is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Proteogenomics & Cancer. The author has an hindex of 14, co-authored 21 publications receiving 1982 citations. Previous affiliations of Yuxing Liao include University of Texas Southwestern Medical Center.

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WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs.

TL;DR: In the 2019 update, WebGestalt supports 12 organisms, 342 gene identifiers and 155 175 functional categories, as well as user-uploaded functional databases and has completely redesigned result visualizations and user interfaces to improve user-friendliness and to provide multiple types of interactive and publication-ready figures.
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ECOD: An Evolutionary Classification of Protein Domains

TL;DR: A hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented as an interactive and updatable online database that catalogs the largest number of evolutionary links among structural domain classifications.
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Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

Michael A. Gillette, +189 more
- 09 Jul 2020 - 
TL;DR: Comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK.
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The WAVE Regulatory Complex Links Diverse Receptors to the Actin Cytoskeleton

TL;DR: A large family of potential WRC ligands, consisting of ∼120 diverse membrane proteins, including protocadherins, ROBOs, netrin receptors, neuroligins, GPCRs, and channels, are identified and a sequence motif that defines these ligands binds to a highly conserved interaction surface of the WRC formed by the Sra and Abi subunits.
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Large scale determination of previously unsolved protein structures using evolutionary information

TL;DR: The use of this method is described to generate structure models for 58 of the 121 large protein families in prokaryotes for which three-dimensional structures are not available, and suggest hypotheses about mechanism for the subset for which the function is known, and hypotheses about function for the remainder.