ArticlePloS one2014
Functional abstraction as a method to discover knowledge in gene ontologies.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
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- Drugs and Epigenetic Molecular Functions. A Pharmacological Data Scientometric Analysis.International journal of molecular sciences · 2021Article
- Computational Functional Genomics-Based AmpliSeq™ Panel for Next-Generation Sequencing of Key Genes of Pain.International journal of molecular sciences · 2021Article
- Machine Learning in Human Olfactory Research.Chemical senses · 2019Review
- A machine-learned analysis of human gene polymorphisms modulating persisting pain points to major roles of neuroimmune processes.European journal of pain (London, England) · 2018Article
- Integrated Computational Analysis of Genes Associated with Human Hereditary Insensitivity to Pain. A Drug Repurposing Perspective.Frontiers in molecular neuroscience · 2017Article
- A machine-learned computational functional genomics-based approach to drug classification.European journal of clinical pharmacology · 2016Article
- Process Pharmacology: A Pharmacological Data Science Approach to Drug Development and Therapy.CPT: pharmacometrics & systems pharmacology · 2016Article
- Computational functional genomics based analysis of pain-relevant micro-RNAs.Human genetics · 2015Article
- Association of genetic and psychological factors with persistent pain after cosmetic thoracic surgery.Journal of pain research · 2015Article
- What do all the (human) micro-RNAs do?BMC genomics · 2014Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational analyses of functions of gene sets obtained in microarray analyses or by topical database searches are increasingly important in biology. To understand their functions, the sets are usually mapped to Gene Ontology knowledge bases by means of over-representation analysis (ORA). Its result represents the specific knowledge of the functionality of the gene set. However, the specific ontology typically consists of many terms and relationships, hindering the understanding of the 'main story'. We developed a methodology to identify a comprehensibly small number of GO terms as "headlines" of the specific ontology allowing to understand all central aspects of the roles of the involved genes. The Functional Abstraction method finds a set of headlines that is specific enough to cover all details of a specific ontology and is abstract enough for human comprehension. This method exceeds the classical approaches at ORA abstraction and by focusing on information rather than decorrelation of GO terms, it directly targets human comprehension. Functional abstraction provides, with a maximum of certainty, information value, coverage and conciseness, a representation of the biological functions in a gene set plays a role. This is the necessary means to interpret complex Gene Ontology results thus strengthening the role of functional genomics in biomarker and drug discovery.
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