PERFORM Publications

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Title		Authors	PubMed ID
1	Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics	Gruninger RJ; Tsang A; McAllister TA;	37149538 CSFG
2	Transcriptional Profiling of the Candida albicans Response to the DNA Damage Agent Methyl Methanesulfonate	Feng Y; Zhang Y; Li J; Omran RP; Whiteway M; Feng J;	35886903 BIOLOGY
3	Deletion of the Aspergillus niger Pro-Protein Processing Protease Gene kexB Results in a pH-Dependent Morphological Transition during Submerged Cultivations and Increases Cell Wall Chitin Content.	van Leeuwe TM, Arentshorst M, Forn-Cuní G, Geoffrion N, Tsang A, Delvigne F, Meijer AH, Ram AFJ, Punt PJ	33276589 CSFG
4	Characterization of the Esi3/RCI2/PMP3 gene family in the Triticeae.	Brunetti SC, Arseneault MKM, Gulick PJ	30537926 BIOLOGY
5	Transcriptome and exoproteome analysis of utilization of plant-derived biomass by Myceliophthora thermophila.	Kolbusz MA, Di Falco M, Ishmael N, Marqueteau S, Moisan MC, Baptista CDS, Powlowski J, Tsang A	24881579 BIOLOGY
6	Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics.	Gruninger RJ, Reid I, Forster RJ, Tsang A, McAllister TA	28417376 CSFG
7	Evaluating Programs for Predicting Genes and Transcripts with RNA-Seq Support in Fungal Genomes.	Reid I	29876820 CSFG

Title:	Evaluating Programs for Predicting Genes and Transcripts with RNA-Seq Support in Fungal Genomes.
Authors:	Reid I
Link:	https://www.ncbi.nlm.nih.gov/pubmed/29876820?dopt=Abstract
DOI:	10.1007/978-1-4939-7804-5_17
Publication:	Methods in molecular biology (Clifton, N.J.)
Keywords:	Bioinformatics; Cleaning short sequence reads; Gene prediction; RNA-Seq; Transcript prediction;
PMID:	29876820	Category:	Methods Mol Biol	Date Added:	2019-06-07
Dept Affiliation:	CSFG 1 Centre for Structural and Functional Genomics, Concordia University, Montreal, QC, Canada. ian.reid@concordia.ca.

Description:

Evaluating Programs for Predicting Genes and Transcripts with RNA-Seq Support in Fungal Genomes.

Methods Mol Biol. 2018;1775:209-227

Authors: Reid I

Abstract

The steps needed to computationally predict genes and transcripts in fungal genomes with support from RNA-Seq data are described in detail for three prediction programs: CodingQuarry, BRAKER1, and Harfang. These programs predicted from 86% to 92% (Harfang) of the genes in a manually curated reference set for Aspergillus niger strain NRRL3. Genes with little or no RNA-Seq read coverage were predicted less successfully than genes with adequate coverage.

PMID: 29876820 [PubMed - indexed for MEDLINE]

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