| Literature DB >> 35713859 |
Oviya Ramalakshmi Iyyappan1, Sharanya Manoharan2.
Abstract
Digitalization of the research articles and their maintenance in a database was the first stage toward the development of biomedical research. With the large amounts of research being published daily, it has created a large gap in accessing all the articles for review to a given problem. To understand any biological process, an insight into the role of each element in the genome is essential. But with this gap in manual curation of literature, there are chances that important biological information may be lost. Hence, text mining plays an important role in bridging this gap and extracting important biological information from the text, finding associations among them and predicting annotations. An annotation may be gene, gene products, gene names, their physical and functional characteristics, and so on. The process of annotations may be classified as structural annotation, functional annotation, and relational annotation. In this chapter, a basic protocol utilizing text mining to extract biological information and predict their functional role based on Gene Ontology is provided.Entities:
Keywords: Functional annotation; Gene Ontology (GO); Gene function prediction; MeSH terms; Semantic similarity; Text mining
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Year: 2022 PMID: 35713859 DOI: 10.1007/978-1-0716-2305-3_4
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745