Tag: BMC Bioinformatics

Researchers in China have developed GEPMC-Loc, a dynamic gated ensemble network that fuses pre-trained language models with multi-scale convolution to ...

Researchers have developed GTVelo, a graph transformer-based neural ordinary differential equation model that improves RNA velocity inference by capturing long-range ...

Researchers have developed TCM-Complexity, an active learning framework that uses the local structural complexity of drug–target embedding spaces to select ...

Researchers at the Universidade de Lisboa have developed a graph neural network method that ranks metabolites by their impact on ...

Researchers have developed Hyb-Adam-UA, a two-stage algorithm that fills missing entries in mitochondrial DNA distance matrices by optimizing tree-like additivity, ...

Researchers have developed GenPTM, a text-mining framework that extracts protein post-translational modification information from scientific abstracts and generalizes to modification ...

A hybrid XGBoost-based machine learning framework has distilled Crohn's disease risk prediction down to just 15 genetic variants, achieving over ...

A new structural equation modeling framework called FT-SEM uses family trios and parental phenotypes to eliminate dynastic effects in GWAS ...

Researchers have developed RecAlign, an A*-based sequence-to-graph aligner that efficiently handles recombination events and enables recombination-aware long-read mapping against chromosome-wide ...

A new machine learning method called PrePssmCas fuses protein language model embeddings with evolutionary PSSM features to classify CRISPR-Cas proteins ...