Changbin Brad Yu

Aird-MSI: a high compression rate and decompression speed format for mass spectrometry imaging data

This paper introduces Aird-MSI, a new format for mass spectrometry imaging data that reduces storage size and improves decompression speed while maintaining high data precision.

AlphaFold3 and RoseTTAFold All-Atom structures enable radiosensitizers discovery by targeting multiple DNA damage repair proteins

The paper identifies radiosensitizers by docking natural products against AI-predicted and experimental DNA repair protein structures, finding compounds that effectively target tumor radioresistance.

How much storage precision can be lost: Guidance for near-lossless compression of untargeted metabolomics mass spectrometry data

The paper evaluates precision loss in metabolomics mass spectrometry data compression and provides thresholds to minimize impact on downstream analysis.

Entropy-based decoy generation methods for accurate FDR estimation in large-scale metabolomics annotations.

This paper introduces entropy-based decoy generation methods to improve FDR estimation in metabolomics and presents a tool for accurate FDR-controlled analysis.

Aird-ComboComp: A combinable compressor framework with a dynamic-decider for lossy mass spectrometry data compression

The paper introduces Aird-ComboComp, a compression framework for mass spectrometry data that improves compression ratios and decompression speed compared to existing methods.

InjectionDesign: Plate Design with Optimized Stratified Block Randomization for Modern LC/GC-MS-Based Sample Preparation

InjectionDesign provides an online plate design service for GC/LC-MS-based experiments with optimized stratified block randomization.

Alpha-XIC: a deep neural network for scoring the coelution of peak groups improves peptide identification by data-independent acquisition mass spectrometry

Alpha-XIC improves peptide identification in DIA mass spectrometry by learning robust coelution scores from peak group data, enhancing identification accuracy and recovery of misidentified peptides.

Missing Value Imputation using XGboost for Label-Free Mass Spectrometry-Based Proteomics Data

This paper introduces XGboost for missing value imputation in label-free proteomics data, showing it outperforms existing methods with empirical parameter settings.

Alpha-Frag: a deep neural network for fragment presence prediction improves peptide identification

Alpha-Frag improves peptide identification by predicting fragment ion presence with a deep neural network, enhancing detection rates in DDA and DIA data.

Aird: A computation-oriented mass spectrometry data format enables higher compression ratio and less decoding time

Aird is a computation-oriented mass spectrometry data format that achieves higher compression and faster decoding compared to existing formats.