ArticlePloS one2012
A framework for annotating human genome in disease context.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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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.
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Who cites it
10 citing papers in PubMed.
- Identification of Novel Potential Genes Involved in Cancer by Integrated Comparative Analyses.International journal of molecular sciences · 2020Article
- Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings.Nature communications · 2019Article
- HumanNet v2: human gene networks for disease research.Nucleic acids research · 2019Article
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- Article
- Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.BioMed research international · 2016Article
- Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care.JMIR medical informatics · 2015Article
- MORPHIN: a web tool for human disease research by projecting model organism biology onto a human integrated gene network.Nucleic acids research · 2014Article
- SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association.PloS one · 2014Article
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Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Identification of gene-disease association is crucial to understanding disease mechanism. A rapid increase in biomedical literatures, led by advances of genome-scale technologies, poses challenge for manually-curated-based annotation databases to characterize gene-disease associations effectively and timely. We propose an automatic method-The Disease Ontology Annotation Framework (DOAF) to provide a comprehensive annotation of the human genome using the computable Disease Ontology (DO), the NCBO Annotator service and NCBI Gene Reference Into Function (GeneRIF). DOAF can keep the resulting knowledgebase current by periodically executing automatic pipeline to re-annotate the human genome using the latest DO and GeneRIF releases at any frequency such as daily or monthly. Further, DOAF provides a computable and programmable environment which enables large-scale and integrative analysis by working with external analytic software or online service platforms. A user-friendly web interface (doa.nubic.northwestern.edu) is implemented to allow users to efficiently query, download, and view disease annotations and the underlying evidences.
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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.