Browse our latest Computational and Systems Biology articles

A novel metabolic network analysis method enables large-scale computational predictions of biosynthetic capabilities across the human oral microbiome, revealing a unique cluster of fastidious microorganisms and potential metabolic interdependencies.

In multi-channel sensory systems, gain adaptation can help maintain not only coding capacity across changes in signal intensity, but also combinatorial representations of odor identity.

Analysis of data on drug-gene interactions suggests that decentralized collaboration will increase the robustness of scientific findings in biomedical research.

The sharp expression pattern driven by a classic, simple animal enhancer is determined by multiple molecular mechanisms, not only cooperative binding of the activating transcription factor as was previously thought.

We are writing to respond to the comment by Gapsys and de Groot, 2019 on our article about molecular dynamics simulations of human hemoglobin (El Hage et al., 2018).

Mapping of 30 general RNA degradation factors onto the yeast transcriptome provides the global distribution of factors for RNA turnover and surveillance in a eukaryotic cell.

Single-cell analyses of cells infected by Herpes Simplex Virus 1 revealed extreme heterogeneity among infected cells, including the robust activation of developmental gene programs in highly infected cells.

Transient transcriptome sequencing and kinetic modeling suggest how the kinetics and yield of RNA splicing are encoded in the human genome.

Biologically plausible changes in the excitabilities of single neurons may suffice to selectively modulate sequential network dynamics, without modifying of recurrent connectivity.

The NetPyNE software tool provides a framework to efficiently develop, simulate, optimize and analyze experimentally grounded neural models spanning the molecular, cellular and circuit scales.