Problem Solving Protocol: Accurate Residue-Level Phase Separation Prediction Using Protein Conformational and Language Model Embeddings

Life Sciences, Biochemistry, Genetics, Biophysics,
phase separation   language model   residue-level prediction   conformational embeddings   intrinsically disordered regions  

1. Academic Background and Research Significance In recent years, protein liquid–liquid phase separation (PS) has emerged as a key mechanism regulating biomolecules inside cells, attracting widespread attention in the life sciences. Phase separation not only drives the formation of biomolecular condensates (membraneless organelles), but also extens...

Chrombus-XMBD: A Graph Convolution Model Predicting 3D-Genome from Chromatin Features

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Cell Biology, Genetics, Biophysics,
3D-genome   graph convolution model   chromatin features   long-range interaction   model generalizability  

Research Background and Disciplinary Significance In eukaryotic cells, the three-dimensional (3D) spatial structure of chromatin plays a crucial role in gene expression regulation. Through complex folding, looping, and local spatial reconfiguration of DNA, different genetic elements (such as promoters and enhancers) are brought into spatial proximi...

Deep scSTAR: Leveraging Deep Learning for the Extraction and Enhancement of Phenotype-Associated Features from Single-Cell RNA Sequencing and Spatial Transcriptomics Data

Information Science, Artificial Intelligence, Medicine, Life Sciences, Cell Biology, Immunology,
Single-cell RNA sequencing   Spatial transcriptomics   Deep learning   Phenotype-associated features   Tumor microenvironment  

In recent years, cutting-edge technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have greatly advanced the development of life sciences and clinical medicine. These technologies have revealed cellular heterogeneity and brought novel insights into major fields such as disease, development, and immunity. Howe...

Ensemble Learning Based on Matrix Completion Improves Microbe-Disease Association Prediction

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Microbiology,
microbe-disease association   ensemble learning   matrix completion   prediction algorithm   bioinformatics  

Academic Background and Research Problem Microorganisms, as one of the most widely distributed forms of life on Earth, are closely related to oceans, soil, and the human body. The human body contains approximately 350 trillion microbial cells, which are intricately linked to human health and the onset and progression of diseases. In recent years, w...

Benchmarking Copy Number Aberrations Inference Tools Using Single-Cell Multi-Omics Datasets

Information Science, Artificial Intelligence, Medicine, Oncology, Life Sciences, Cell Biology, Bioengineering, Genetics,
Single-cell RNA sequencing   Copy number aberrations   Tumor heterogeneity   Benchmarking   Multi-omics  

1. Research Background and Significance In the fields of oncology and genomics, chromosomal copy number alterations (CNAs) are a key type of genetic variation driving the occurrence and progression of cancer. CNAs not only determine tumor heterogeneity but also play a crucial role in early tumor detection, subclone evolution analysis, research on d...

HSSPPI: Hierarchical and Spatial-Sequential Modeling for PPIs Prediction

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Genetics,
protein–protein interaction sites   hierarchical graph   spatial form   sequential form   feature fusion  

Background: Unveiling the Bottlenecks and Opportunities in Protein Interaction Prediction Proteins serve as the core molecules for life activities, participating in almost all biological processes and cellular functions, including gene expression, RNA transcription, DNA synthesis, immune response, and more. Protein-protein interactions (PPI), as we...

GCduo: An Open-Source Software for GC × GC–MS Data Analysis

Chemistry, Analytical Chemistry, Computational Chemistry,
GC × GC–MS   multi-dimensional chromatography   metabolomics   chemometrics   PARAFAC   PARAFAC2   open-source software  

Academic Background and Research Motivation With the growing demand for the analysis of complex samples, chromatographic technologies—especially comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC–MS)—have emerged as a powerhouse for untargeted metabolomics and related fields, demonstrating exceptional resolving p...

Unveiling a Novel Cancer Hallmark by Evaluation of Neural Infiltration in Cancer

Medicine, Oncology, Life Sciences, Cell Biology, Immunology, Genetics,
neural infiltration   cancer hallmark   tumor microenvironment   single-cell RNA sequencing   immunotherapy  

Cancer, as a major global public health challenge, is characterized by complex mechanisms underlying its onset and progression. For a long time, processes within the tumor microenvironment (TME)—such as immunity, inflammation, and angiogenesis—have been extensively studied and considered key determinants of tumor biological behavior. In recent year...

MAEST: Accurate Spatial Domain Detection in Spatial Transcriptomics with Graph Masked Autoencoder

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Bioengineering,
spatial transcriptomics   spatial domain identification   joint domain detection   graph masked autoencoder   graph contrastive learning  

Spatial Transcriptomics: Cutting-Edge Technology for Deciphering Spatial Heterogeneity in Tissues Spatial transcriptomics (ST) is an emerging sequencing technology that has rapidly developed in recent years. Its core advantage lies in the simultaneous acquisition of gene expression and spatial location information at the tissue section level, provi...

TopoQA: A Topological Deep Learning-Based Approach for Protein Complex Structure Interface Quality Assessment

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Biophysics,
Quality Assessment   Protein Interface   Persistent Homology   Graph Neural Network   Topological Data  

Academic Background The elucidation of protein complex 3D structures is a central topic in modern structural biology, molecular mechanism studies, drug design, and even artificial protein design. The function of a protein is often determined by its structure, and many biological processes involve complex interactions between proteins. Although trad...