FlowPacker: Protein Side-Chain Packing with Torsional Flow Matching

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering,
protein side-chain packing   torsional flow matching   equivariant graph attention networks   protein structure prediction   artificial intelligence  

The three-dimensional structure of a protein is determined by its amino acid sequence, and the function of the protein is highly dependent on its three-dimensional structure. The side-chain conformations of proteins play a crucial role in protein folding, protein-protein interactions, and de novo protein design. Accurate prediction of protein side-...

CryoTEN: Efficiently Enhancing Cryo-EM Density Maps Using Transformers

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Biophysics,
Cryo-EM   density map enhancement   Transformer   deep learning   protein structure   image processing   bioinformatics  

Academic Background Cryogenic Electron Microscopy (Cryo-EM) is a crucial experimental technique for determining the structures of macromolecules such as proteins. However, the effectiveness of Cryo-EM is often hindered by noise and missing density values caused by experimental conditions such as low contrast and conformational heterogeneity. Althou...

Relative Quantification of Proteins and Post-Translational Modifications in Proteomic Experiments with Shared Peptides: A Weight-Based Approach

Life Sciences, Biochemistry, Bioengineering,
protein quantification   post-translational modifications   shared peptides   mass spectrometry   bioinformatics  

In proteomics research, mass spectrometry (MS) is widely used to analyze changes in protein abundance and structure. However, protein quantification faces a critical challenge: many proteins share the same peptides (shared peptides), meaning these peptides appear in the sequences of multiple proteins. Traditional methods typically rely solely on un...

Sul-BERTGRU: An Ensemble Deep Learning Method Integrating Information Entropy-Enhanced BERT and Directional Multi-GRU for S-Sulfhydration Sites Prediction

Information Science, Artificial Intelligence, Life Sciences, Cell Biology, Biochemistry,
deep learning   S-sulfhydration sites   information entropy   BERT   multi-directional GRU   protein modification   bioinformatics  

Background Introduction Post-Translational Modifications (PTMs) are crucial mechanisms for regulating cellular activities, including gene transcription, DNA repair, and protein interactions. Among these, cysteine, a rare amino acid, participates in various PTMs through its thiol group, playing a significant role in redox balance and signal transduc...

Trajectory Alignment of Gene Expression Dynamics

Medicine, Life Sciences, Cell Biology, Biochemistry, Bioengineering, Immunology, Genetics, Microbiology,
gene expression   single-cell transcriptomics   trajectory alignment   bioinformatics   differentially expressed genes  

The advent of single-cell RNA sequencing (scRNA-seq) technology has provided unprecedented resolution for studying gene expression dynamics during cell development and differentiation. However, due to the complexity of biological processes, cell developmental trajectories under different conditions are often asymmetric, posing challenges for data i...

SP-DTI: Subpocket-Informed Transformer for Drug–Target Interaction Prediction

Chemistry, Medicinal Chemistry, Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering,
Drug-Target Interaction   Deep Learning   Subpocket Analysis   Transformer Model   Drug Discovery  

Academic Background Drug-Target Interaction (DTI) prediction is a critical step in drug discovery, significantly reducing the cost and time of experimental screening. However, despite the advancements in deep learning that have improved the accuracy of DTI prediction, existing methods still face two major challenges: lack of generalizability and ne...