New ESMF Method Sharpens Cell-Type Estimates from Bulk RNA Sequencing Data
A new deconvolution framework called ESMF uses single-cell reference data, negative binomial noise modeling and dual-validated marker selection to estimate ...
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.
A new computational framework, Akita Semifreddo, combines a fast genome folding model with sequence optimization to design DNA with specified ...
A Nature Reviews Cancer review surveys the statistical and computational methods that reconstruct tumour evolutionary histories from single-cell sequencing data ...
A new method called ReadsRatio estimates tissue contributions to circulating cell-free DNA from unmethylated read ratios in cell type-specific marker ...
A new PLOS Computational Biology perspective sets out ten practical rules defining where AI assistance in computational biology is legitimate ...
SERNA and SERNAlign compare RNA secondary structures with arbitrary pseudoknots using integer sequences, achieving competitive clustering performance at lower computational ...
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© 2025 Scienmag - Science Magazine