PLOS Computational Biology

PLOS Computational Biology is a peer-reviewed, open-access scientific journal focusing on computational methods and theoretical approaches applied to biological problems. It publishes original research, perspectives, reviews, and software reports that bridge computational techniques and life sciences. The journal operates under the Public Library of Science umbrella and aims to disseminate reproducible, accessible computational studies to a global research community.

History

PLOS Computational Biology was launched in 2005 during a period of rapid growth in bioinformatics and systems biology, alongside developments at National Institutes of Health, Howard Hughes Medical Institute, Wellcome Trust, European Molecular Biology Laboratory, and National Science Foundation. Its founding followed precedents set by PLoS Biology and PLoS Medicine and paralleled initiatives at Nature Publishing Group and Science (journal). Early editorial leadership included scientists affiliated with University of California, San Diego, Massachusetts Institute of Technology, Cambridge University, Harvard University, and Stanford University. The journal expanded its scope as high-throughput sequencing from Human Genome Project era technologies and computational frameworks from Artificial Intelligence and Bayesian statistics became central to biological research. Over the 2010s it engaged with communities represented by conferences such as RECOMB, ISMB, ACM SIGKDD, and NeurIPS, and with consortia like the ENCODE Project and 1000 Genomes Project.

Scope and Content

The journal emphasizes interdisciplinary work at the interface of computation and biology, publishing studies that combine methods from Machine Learning, Statistical Mechanics, Graph Theory, Dynamical Systems, and Optimization with applications in areas tied to institutions such as National Cancer Institute, Centers for Disease Control and Prevention, European Bioinformatics Institute, Sanger Institute, and Fred Hutchinson Cancer Research Center. Typical topics include algorithms for sequence analysis used in workflows from BLAST-style homology searches to pipelines influenced by GATK practices; structural modeling approaches inspired by techniques from Rosetta (software), Molecular Dynamics simulations established at Los Alamos National Laboratory and Argonne National Laboratory; network inference drawing on work from Stanford University and Caltech; and population genetics shaped by paradigms from Wright–Fisher model and studies linked to Drosophila melanogaster and Homo sapiens populations. The journal also features methodological advances relevant to experimental platforms developed at Broad Institute and Cold Spring Harbor Laboratory, and computational resources associated with XSEDE and European Grid Infrastructure.

Editorial Structure and Policies

Editorial leadership includes professional editors and an academic advisory board populated by researchers from Yale University, Princeton University, University of Oxford, University of Cambridge, ETH Zurich, Max Planck Society, Imperial College London, and University of Tokyo. The peer-review process draws reviewers affiliated with organizations such as American Society for Microbiology, Society for Industrial and Applied Mathematics, International Society for Computational Biology, and discipline-specific groups like Biophysical Society and Genetics Society of America. Policies on data availability and reproducibility reflect standards advocated by Committee on Publication Ethics and align with mandates from funders including Wellcome Trust and Gates Foundation. The journal enforces guidelines for competing interests modeled after practices at The Royal Society and transparency expectations similar to PLOS ONE.

Publication Model and Open Access

As an open-access publication within the Public Library of Science family, the journal adopts Creative Commons licensing analogous to approaches used by BioMed Central and Frontiers Media. Article processing charges are part of the funding model, a practice also employed by Elsevier's open platforms and debated by stakeholders including Plan S signatories and institutions such as University of California and Max Planck Society. The journal supports preprint submissions to servers like arXiv, bioRxiv, and medRxiv and participates in metadata indexing systems maintained by PubMed Central, Scopus, and Web of Science. It has implemented innovations in publishing workflow inspired by developments at eLife and F1000Research.

Impact and Reception

PLOS Computational Biology has been cited in work from laboratories at Salk Institute, Johns Hopkins University, Columbia University, University of Washington, and Weizmann Institute of Science, reflecting influence across computational and experimental communities. Its articles contribute to methodologies adopted in projects such as Human Cell Atlas and translational efforts at Mayo Clinic and Cleveland Clinic. Reception among stakeholders ranges from praise for openness and reproducibility, echoed by proponents at OpenAI-adjacent academic groups and advocates in the open science movement, to critiques about article processing costs voiced by representatives from European Commission funding bodies and library consortia like SPARC. The journal's impact metrics have been tracked alongside peers including Bioinformatics (journal), Genome Research, Nature Communications, and PLoS Genetics.

Category:Academic journals