Browse our latest Computational and Systems Biology articles

SCellBOW is a language model-based scRNA-seq analysis method that identifies malignant cell subpopulations and infers marker-free survival risks using transfer learning.

A model was developed to predict human biological age from physiological traits, enabling the prediction of future health and mortality and the identification of genetic loci that influence aging.

Systematic simulations reveal how growth feedback undermines the stability of adaptive gene circuits in a topology-dependent manner.

The combination of growth optimization and cell heterogeneity enables a quantitative explanation of overflow metabolism in microbes and the classical Warburg effect in cancer cells, resolving this long-standing puzzle.

Drug synergy Interaction Prediction improves personalized drug synergy prediction by utilizing drug-specific pathway activation scores to predict personalized drug synergy and reveals mechanistic pathways underlying synergistic effects.

New protein-protein docking algorithm combining deep learning (AlphaFold2) and physics (Rosetta and enhanced sampling) achieves high success rates.

A computational study reveals that the kinetic models of Escherichia coli metabolism show strong responsiveness to perturbations and that it originates from cofactor dynamics and network sparsity.

MorphoCellSorter is a versatile, user-friendly tool that automates microglial morphology ranking, enabling standardized, reproducible analysis across diverse models, imaging techniques, and conditions using principal component analysis and Andrews plots.