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Deep learning for peptide identification from metaproteomics datasets (open access)

Deep learning for peptide identification from metaproteomics datasets

This article explores a proposed deep-learning-based algorithm called DeepFilter for improving peptide identifications from a collection of tandem mass spectra. The authors find that DeepFilter is believed to generalize properly to new, previously unseen peptide-spectrum-matches and can be readily applied in peptide identification from metaproteomics data.
Date: July 8, 2021
Creator: Feng, Shichao; Sterzenbach, Ryan & Guo, Xuan
Object Type: Article
System: The UNT Digital Library
Child Health and Human Development Extramural Research (open access)

Child Health and Human Development Extramural Research

Data management plan for the grant, "Child Health and Human Development Extramural Research." This study will use the genome-edited human induced pluripotent stem cell (hiPSC) with NOTCH1 knockout to recapitulate the genetic variants of NOTCH1 mutation in the Hypoplastic left heart syndrome (HLHS). It will use advances in the vascularized cardiac organoid directly differentiated from hiPSCs to replay the development and function of cardiomyocytes, endothelial cells, smooth muscle cells, and other cardiac cells in a defined 3D cell culture model by stencil-based micropatterning. It will elucidate the pathogenesis of cardiovascular underdevelopment and dysfunction found in HLHS with NOTCH1 mutation via the NOTCHDELTA/JAG ligand-receptor binding and multicellular crosstalk by single-cell RNA-seq and proteomics analysis.
Date: 2022-09-08/2025-08-31
Creator: Yang, Huaxiao
Object Type: Text
System: The UNT Digital Library