Literature DB >> 28582481

FunGAP: Fungal Genome Annotation Pipeline using evidence-based gene model evaluation.

Byoungnam Min1, Igor V Grigoriev2,3, In-Geol Choi1.   

Abstract

MOTIVATION: Successful genome analysis depends on the quality of gene prediction. Although fungal genome sequencing and assembly have become trivial, its annotation procedure has not been standardized yet.
RESULTS: FunGAP predicts protein-coding genes in a fungal genome assembly. To attain high-quality gene models, this program runs multiple gene predictors, evaluates all predicted genes, and assembles gene models that are highly supported by homology to known sequences. To do this, we built a scoring function to estimate the congruency of each gene model based on known protein or domain homology.
AVAILABILITY AND IMPLEMENTATION: FunGAP is written in Python script and is available in GitHub ( https://github.com/CompSynBioLab-KoreaUniv/FunGAP ). This software is freely available only for noncommercial users. CONTACT: igchoi@korea.ac.kr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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Year:  2017        PMID: 28582481     DOI: 10.1093/bioinformatics/btx353

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  13 in total

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6.  Dynamics in Secondary Metabolite Gene Clusters in Otherwise Highly Syntenic and Stable Genomes in the Fungal Genus Botrytis.

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