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Haipeng Wang

Researcher at Chinese Academy of Sciences

Publications -  21
Citations -  2215

Haipeng Wang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Statistical classification & Support vector machine. The author has an hindex of 10, co-authored 20 publications receiving 1924 citations. Previous affiliations of Haipeng Wang include Toyota Technological Institute at Chicago.

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Template-based protein structure modeling using the RaptorX web server

TL;DR: This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling.
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pFind 2.0: a software package for peptide and protein identification via tandem mass spectrometry.

TL;DR: The pFind 2.0 software package for peptide and protein identification via tandem mass spectrometry offers a modularized and customized platform for third parties to test and compare their algorithms, and is of high accuracy and high speed.
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pNovo: De novo Peptide Sequencing and Identification Using HCD Spectra

TL;DR: It is shown that higher-energy collisional dissociation (HCD) is of great help to de novo sequencing because it produces high mass accuracy tandem mass spectrometry (MS/MS) spectra without the low-mass cutoff associated with CID in ion trap instruments.
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A Strategy for Precise and Large Scale Identification of Core Fucosylated Glycoproteins

TL;DR: A robust strategy is developed that integrates molecular weight cutoff, neutral loss-dependent MS3, database-independent candidate spectrum filtering, and optimization to effectively identify CF glycoproteins and shows great progress for finding biomarkers with a particular and attractive prospect.
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Open MS/MS spectral library search to identify unanticipated post-translational modifications and increase spectral identification rate

TL;DR: An open spectral library search tool, named pMatch, which extends the existing library search algorithms in at least three aspects to support the identification of unanticipated modifications and significantly increase spectral identification rate.