Computational and Systems Biology

Computational and Systems Biology

eLife publishes research involving the use of methods, models and software. Learn more about what we publish and sign up for the latest research.
Illustration by Davide Bonazzi

Latest articles

    1. Computational and Systems Biology
    2. Neuroscience

    Sex differences in learning from exploration

    Cathy S Chen et al.
    A new computational analysis of decision making in mice shows sex biases in value-updating while exploring unknown options, with male mice tending to explore longer than females due to updating values more slowly.
    1. Computational and Systems Biology
    2. Evolutionary Biology

    Predicting bacterial promoter function and evolution from random sequences

    Mato Lagator et al.
    An inferred mechanistic model that connects sequence (genotype) to function (constitutive gene expression phenotype) for any random sequence in Escherichia coli reveals the structure of constitutive promoters and how they evolve.
    1. Computational and Systems Biology
    2. Medicine

    Personalized computational heart models with T1-mapped fibrotic remodeling predict sudden death risk in patients with hypertrophic cardiomyopathy

    Ryan P O'Hara et al.
    Personalized virtual-heart technology for arrhythmia risk assessment could transform the management of hypertrophic cardiomyopathy patients, eliminating many unnecessary primary-prevention defibrillator deployments while ensuring patients at high risk for arrhythmia are adequately protected.
    1. Computational and Systems Biology
    2. Medicine

    A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease

    James A Timmons et al.
    Optimising the use of transcriptomics enables screening of thousands of compounds and illustrates an approach that yields quantitative pharmacology at the single-gene and pathway level.
    1. Computational and Systems Biology
    2. Medicine

    Data mining methodology for response to hypertension symptomology—application to COVID-19-related pharmacovigilance

    Xuan Xu et al.
    Quantitative models and data-driven approaches developed for the COVID-19 pandemic and predicting SARS-Cov-2 comorbidities for high-risk populations including hypertension show that the future of large-scale biomedical science will be significantly underscored by data-driven decision-making and AI knowledge-based development and validation.
    1. Computational and Systems Biology

    Response to comment on ‘SARS-CoV-2 suppresses anticoagulant and fibrinolytic gene expression in the lung’

    Alan E Mast et al.
    We are writing to respond to the comment by FitzGerald and Jamieson, 2022 on our article about the drivers of coagulopathy in the lungs of COVID-19 patients (Mast et al., 2021).

Senior editors

  1. Naama Barkai
    Naama Barkai
    Weizmann Institute of Science, Israel
  2. Aleksandra Walczak
    Ecole Normale Superieure, France
  3. See more editors