Latest Articles for Computational Biology

Pool PaRTI enhances protein analysis by improving data representation and biological insight.

This article introduces a method for modeling neural activity using low-rank RNNs.

A novel tool for designing RNA sequences based on their shapes.

Study reveals complex behaviors of fruit fly larvae in response to their environment.

Investigating how crowded conditions affect protein movement and interaction in cells.

AlphaFold's evolution enhances accurate protein structure predictions for science and medicine.

Research sheds light on microtubule behavior and their role in cellular processes.

ReconcILS algorithm improves accuracy in comparing gene trees and species trees.

Examining how to define and identify cell death in biological systems.

A new technique improves understanding of mutations in viral evolution.

A new model improves predictions of where proteins bind, aiding drug discovery.

New tools improve RNA structure predictions and help identify false homologs.

New insights on AlphaFold's ability to predict protein structures and its limitations.

NeKo streamlines the process of creating biological interaction networks using data and knowledge.

Chai-1 predicts biomolecule shapes, enhancing drug design and biological research.

A novel method enhances drug-target prediction using machine learning techniques.

KinPFN uses deep learning to speed up RNA folding analysis.

PSALM improves protein domain predictions through innovative modeling techniques.

Learn how subgraph queries enhance graph analysis and data predictions.

Carafe improves peptide detection in DIA studies through innovative spectral library generation.

ARROW-Diff efficiently generates large, realistic graphs using random walks.

Analyzing neural motifs in C. elegans reveals insights into nervous system function.

This study evaluates methods for predicting how mutated peptides bind to proteins.

Scientists use machine learning to identify enzymes that break down plastic waste.

A new method for generating peptides with single sequence input enhances drug discovery.

A new method improves predictions of gene expression using gene regulatory networks.

SOFA integrates guiding variables to enhance multi-omics data analysis.

New strategies enhance speed and accuracy in long-read DNA processing.

A look into the challenges of reconstructing ancestral sequences through deletions.

FilmCPI improves drug discovery by addressing data imbalance and enhancing prediction efficiency.

New deep learning model BPfold improves RNA structure predictions.

Discover how active learning optimizes experiments in biological research.

A new model improves prediction of drug effects on cancer cells.

An overview of LED trees and their role in studying species evolution.

A look at methods for aligning protein sequences and structures.

Introducing LEGEND, a method for analyzing gene expression across cell types and tissues.

Understanding reticulation events in phylogenetic networks and their implications for evolution.

New framework aids in predicting protein interactions, especially for corals.

A look at AlphaFold2's predictions and potential misinterpretations in protein structures.

Different Cell Ranger versions significantly affect scRNA-seq data analysis outcomes.