Weichuan Yu

Profiling proteome-level amino acid substitutions in Alzheimer's disease brain tissue

This study identifies proteome-level amino acid substitutions in Alzheimer's disease using proteomic datasets and a specialized pipeline, revealing novel substitutions not detectable through genomic or transcriptomic methods.

gSV: a general structural variant detector using the third-generation sequencing data

gSV improves structural variant detection in long-read sequencing data by integrating alignment and assembly approaches, showing better sensitivity for complex variants and uncovering new SVs in breast cancer.

RoBep: A Region-Oriented Deep Learning Model for B-Cell Epitope Prediction

RoBep predicts B-cell epitopes by modeling spatial continuity, improving performance on benchmark datasets and providing antibody-antigen binding regions.

Functional, Biotinylproteomic and Bioinformatic Analysis of Both Cytoskeletal and Plastoskeletal Proteins in Plant Mechanoresponse

The paper identifies WPRa4 and PMI4 as key proteins in Arabidopsis touch response, showing their role in mechano-sensing and calcium signaling through proteomic and transcriptomic analyses.

A comprehensive benchmarking study of protein structure alignment tools based on downstream task performance

This study benchmarks nine protein structure alignment tools across homology detection, phylogeny reconstruction, and function inference, showing structure-based methods often outperform sequence-based ones.

Amino acid substitutomics: profiling amino acid substitutions at proteomic scale unveils biological implication and escape mechanism in cancer

This study introduces a proteomic approach to identify amino acid substitutions in cancer, revealing novel substitutions and their roles in drug resistance and immune escape.

Capturing the Hierarchically Assorted Protein-protein Interaction Modules of Mammalian Cell

The paper identifies protein-protein interaction modules in mammalian cells using XL-MS data and bioinformatics, revealing hierarchical organization into compartments.

PIPI-C: A combinatorial optimization framework for identifying post-translational modification crosstalks in mass spectrometry data

PIPI-C identifies PTM crosstalks in mass spectrometry data using a combinatorial optimization framework, revealing upregulated PTM patterns in cancer datasets.

Acupuncture triggers earlier recovery from ischemic stroke than sham needling in a rat model

This study shows acupuncture at specific acupoints accelerates recovery from ischemic stroke in rats compared to sham needling, with effects observed in motor control regions.

Searching Post-translational Modifications in Cross-linking Mass Spectrometry Data

This study introduces SeaPIC, an XL-MS tool for identifying post-translational modifications in protein-protein interactions and structures, successfully detecting previously undiscovered PTMs.

Voxel-wise regression without intensity normalizationprovides better sensitivity when identifying injuryregions after stroke in FDG-PET images

This paper introduces a regression-based method for analyzing FDG-PET images without intensity normalization, showing improved sensitivity in detecting stroke injury regions compared to existing methods.

Exhaustive Cross-linking Search with Protein Feedback

This paper introduces ECL-PF, a method for cleavable XL-MS data analysis that improves sensitivity in detecting protein-protein interactions and structures.

Capturing the Hierarchically Assorted Modules of Protein Interaction in the Organized Nucleome

The paper introduces a pipeline called CHAMPION that uses qXL-MS and MONET modulomics to identify nuclear protein interactions and modules, revealing novel interactors and hormone-specific variants.

Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-fluorodeoxyglucose Positron Emission Tomography

The paper introduces a feature-based method using FDG PET images and SVM to assess MCAO quality in rats, achieving high accuracy in classification.

Understanding the limit of open search in the identification of peptides with post-translational modifications -- A simulation-based study

The paper evaluates open search methods for identifying modified peptides through simulations and proposes an analytical model to quantify performance based on spectrum quality and PTM count.

Xolik: finding cross-linked peptides with maximum paired scores in linear time

Xolik identifies cross-linked peptides efficiently by reducing computational complexity and outperforms existing tools in speed and statistical power.

Exhaustively Identifying Cross-Linked Peptideswith a Linear Computational Complexity

ECL 2.0 improves peptide-peptide pair identification by achieving linear complexity and better sensitivity compared to existing tools.

PIPI: PTM-Invariant Peptide Identification Using Coding Method

PIPI improves PTM-invariant peptide identification by using Boolean coding and dynamic programming, achieving higher sensitivity and speed compared to existing tools.