ArticleJournal of biomolecular screening2014
Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS).
Article in Journal of biomolecular screening, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
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- Toward Better Semantic Interoperability of Data Element Repositories in Medicine: Analysis Study.JMIR medical informatics · 2024Article
- Identification of significant gene expression changes in multiple perturbation experiments using knockoffs.Briefings in bioinformatics · 2023Article
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- Disentangling the Molecular Pathways of Parkinson's Disease using Multiscale Network Modeling.Trends in neurosciences · 2021Review
- Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.Nature reviews. Nephrology · 2020Review
- Modelling the gene expression and the DNA-binding in the 3T3-L1 differentiating adipocytes.Adipocyte · 2019Article
- Annot: a Django-based sample, reagent, and experiment metadata tracking system.BMC bioinformatics · 2019Article
- Biomedical Image Processing with Containers and Deep Learning: An Automated Analysis Pipeline: Data architecture, artificial intelligence, automated processing, containerization, and clusters orchestration ease the transition from data acquisition to insights in medium-to-large datasets.BioEssays : news and reviews in molecular, cellular and developmental biology · 2019Article
- OSCI: standardized stem cell ontology representation and use cases for stem cell investigation.BMC bioinformatics · 2019Article
- The GCTx format and cmap{Py, R, M, J} packages: resources for optimized storage and integrated traversal of annotated dense matrices.Bioinformatics (Oxford, England) · 2019Article
- Bioinformatic and biological avenues for understanding alcohol use disorder.Alcohol (Fayetteville, N.Y.) · 2019Review
- EdgeScaping: Mapping the spatial distribution of pairwise gene expression intensities.PloS one · 2019Article
- L1000 Viewer: A Search Engine and Web Interface for the LINCS Data Repository.Frontiers in genetics · 2019Article
- EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to improve prediction accuracy.Bioinformatics (Oxford, England) · 2018Article
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Authors and funding
15 authors.
Funding
Abstract
The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.
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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.