ArticlePLoS biology2018
Enabling precision medicine via standard communication of HTS provenance, analysis, and results.
Article in PLoS biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 38 citations in OpenAlex.
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- BioWorkflow: Retrieving comprehensive bioinformatics workflows from publications.Briefings in bioinformatics · 2025Article
- Playbook workflow builder: Interactive construction of bioinformatics workflows.PLoS computational biology · 2025Article
- Provenance Information for Biomedical Data and Workflows: Scoping Review.Journal of medical Internet research · 2024Article
- Recording provenance of workflow runs with RO-Crate.PloS one · 2024Article
- Bioinformatics analysis and experimental validation of tumorigenic role of PPIA in gastric cancer.Scientific reports · 2023Article
- Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model.Glycobiology · 2022Article
- Lightweight Distributed Provenance Model for Complex Real-world Environments.Scientific data · 2022Article
- eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain.F1000Research · 2022Article
- FAIRSCAPE: a Framework for FAIR and Reproducible Biomedical Analytics.Neuroinformatics · 2022Article
- The role of metadata in reproducible computational research.Patterns (New York, N.Y.) · 2021Review
- Bioinformatics tools developed to support BioCompute Objects.Database : the journal of biological databases and curation · 2021Article
- GlyGen data model and processing workflow.Bioinformatics (Oxford, England) · 2020Article
- OncoMX: A Knowledgebase for Exploring Cancer Biomarkers in the Context of Related Cancer and Healthy Data.JCO clinical cancer informatics · 2020Article
- BCO App: tools for generating BioCompute Objects from next-generation sequencing workflows and computations.F1000Research · 2020Article
- Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv.GigaScience · 2019Article
- Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues.Nature reviews. Microbiology · 2019Review
- Data Lakes, Clouds, and Commons: A Review of Platforms for Analyzing and Sharing Genomic Data.Trends in genetics : TIG · 2019Review
- miCloud: A Plug-n-Play, Extensible, On-Premises Bioinformatics Cloud for Seamless Execution of Complex Next-Generation Sequencing Data Analysis Pipelines.Journal of computational biology : a journal of computational molecular cell biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
37 authors at 20 institutions in 5 countries.
Funding
Abstract
A personalized approach based on a patient's or pathogen's unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods. The BioCompute framework (https://w3id.org/biocompute/1.3.0) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed, and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCOs) offer that standard and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the "Open-Stand.org principles for collaborative open standards development." With high-throughput sequencing (HTS) studies communicated using a BCO, regulatory agencies (e.g., Food and Drug Administration [FDA]), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next-generation sequencing workflow exchange, reporting, and regulatory reviews.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.