Finding Gene Associations by Text Mining and Annotating it with Gene Ontology-Reference-Cited by-同舟云学术

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Finding Gene Associations by Text Mining and Annotating it with Gene Ontology

Published:2022 Issue: Volume: Page:71-90
ISSN:1064-3745
Container-title:Methods in Molecular Biology
language:
Short-container-title:

Author:

Iyyappan Oviya Ramalakshmi,Manoharan Sharanya

Publisher

Springer US

Link

https://link.springer.com/content/pdf/10.1007/978-1-0716-2305-3_4

Reference25 articles.

1. Vitale O, Preste R, Palmisano D, Attimonelli M (2020) A data and text mining pipeline to annotate human mitochondrial variants with functional and clinical information. Mol Genet Genomic Med 8(2):e1085. https://doi.org/10.1002/mgg3.1085

2. Werner T (2010) Next generation sequencing in functional genomics. Brief Bioinform 11(5):499–511. https://doi.org/10.1093/bib/bbq018

3. Bian J, Liu C, Wang H, Xing J, Kachroo P, Zhou X (2013) SNVHMM: predicting single nucleotide variants from next generation sequencing. BMC Bioinformatics 14(1):225. https://doi.org/10.1186/1471-2105-14-225

4. Fyad HB, Bouamrane K (2016) Computational methods for functional analysis of gene expression. In: Second international conference on advances in computer science and information technology (ACSTY 2016). Chennai, India. pp 1–14. https://doi.org/10.5121/csit.2016.61401

5. Tsoi LC, Patel R, Zhao W, Zheng WJ (2009) Text-mining approach to evaluate terms for ontology development. J Biomed Inform 42(5):824–830. https://doi.org/10.1016/j.jbi.2009.03.009

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