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...

GCLink: A Graph Contrastive Link Prediction Framework for Gene Regulatory Network Inference

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Bioengineering, Genetics,
Gene Regulatory Networks   Single-cell RNA Sequencing   Graph Contrastive Learning   Link Prediction   Machine Learning  

Research Background Gene Regulatory Networks (GRNs) are crucial tools for understanding the complex biological processes within cells. They reveal the interactions between Transcription Factors (TFs) and target genes, thereby controlling gene transcription and regulating cellular behavior. With the advancement of single-cell RNA sequencing (scRNA-s...

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...

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...

Contrastive Mapping Learning for Spatial Reconstruction of Single-Cell RNA Sequencing Data

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Bioengineering,
Single-cell RNA sequencing   Spatial transcriptomics   Contrastive learning   Cell correspondence   Gene expression  

Single-cell RNA sequencing (scRNA-seq) technology enables high-throughput transcriptomic profiling at single-cell resolution, significantly advancing research in cell biology. However, a notable limitation of scRNA-seq is that it requires tissue dissociation, resulting in the loss of the original spatial location information of cells within tissues...