Tag: computational biology

A new algorithmic framework finds small sets of transcription factors that jointly cover disease-related gene networks with near-optimal efficiency on ...

An AI framework combining Kolmogorov–Arnold network drug–target prediction with AutoML modeling of Chinese Materia Medica properties identified lipid-lowering candidates from ...

A computational survey of 381 oral bacterial genomes found 48,234 G-quadruplex motifs, with a 2.5 to 3-fold enrichment in promoter ...

Researchers have introduced scDECA, a dual-encoder cross-attention framework that combines raw gene expression, pretrained gene priors and local structure to ...

A new open-access framework called scCIF adaptively fuses single-cell multi-omics data and outperformed competing methods on eight public datasets.

A new deconvolution framework called ESMF uses single-cell reference data, negative binomial noise modeling and dual-validated marker selection to estimate ...

A new deep learning framework called RCNNricePPI predicts rice protein-protein interactions from amino acid sequences, achieving an accuracy of 0.8996 ...

A computational study combined gene co-expression network analysis and machine learning to nominate twelve candidate biomarkers for malignant pleural mesothelioma, ...

A new method called CSDE uses a small set of expert-validated cells to correct systematic preprocessing errors in spatial transcriptomics ...

The circMAC model predicted candidate microRNA-binding regions across complete circular RNA isoforms while preserving sequence continuity at back-splice junctions.