PERFORM Publications

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Title		Authors	PubMed ID
1	Ion channel classification through machine learning and protein language model embeddings	Ghazikhani H; Butler G;	39572876 ENCS
2	SPOT: A machine learning model that predicts specific substrates for transport proteins	Kroll A; Niebuhr N; Butler G; Lercher MJ;	39325691 ENCS
3	Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses	Steindorff AS; Aguilar-Pontes MV; Robinson AJ; Andreopoulos B; LaButti K; Kuo A; Mondo S; Riley R; Otillar R; Haridas S; Lipzen A; Grimwood J; Schmutz J; Clum A; Reid ID; Moisan MC; Butler G; Nguyen TTM; Dewar K; Conant G; Drula E; Henrissat B; Hansel C; Singer S; Hutchinson MI; de Vries RP; Natvig DO; Powell AJ; Tsang A; Grigoriev IV;	39266695 CSFG
4	Exploiting protein language models for the precise classification of ion channels and ion transporters	Ghazikhani H; Butler G;	38656743 CSFG
5	Enhanced identification of membrane transport proteins: a hybrid approach combining ProtBERT-BFD and convolutional neural networks	Ghazikhani H; Butler G;	37497772 ENCS
6	Integrative approach for detecting membrane proteins.	Alballa M, Butler G	33349234 CSFG
7	BENIN: Biologically enhanced network inference.	Wonkap SK, Butler G	32698722 ENCS
8	TooT-T: discrimination of transport proteins from non-transport proteins.	Alballa M, Butler G	32321420 CSFG
9	TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information.	Alballa M, Aplop F, Butler G	31935244 CSFG
10	Analytical and computational approaches to define the Aspergillus niger secretome.	Tsang A, Butler G, Powlowski J, Panisko EA, Baker SE	19618504 BIOLOGY
11	SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models.	Reid I, O'Toole N, Zabaneh O, Nourzadeh R, Dahdouli M, Abdellateef M, Gordon PM, Soh J, Butler G, Sensen CW, Tsang A	24980894 CSFG
12	Machine learning for biomedical literature triage.	Almeida H, Meurs MJ, Kosseim L, Butler G, Tsang A	25551575 CSFG
13	mycoCLAP, the database for characterized lignocellulose-active proteins of fungal origin: resource and text mining curation support.	Strasser K, McDonnell E, Nyaga C, Wu M, Wu S, Almeida H, Meurs MJ, Kosseim L, Powlowski J, Butler G, Tsang A	25754864 CSFG
14	An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures.	Zandi K, Butler G, Kharma N	27499762 CSFG

Title:	mycoCLAP, the database for characterized lignocellulose-active proteins of fungal origin: resource and text mining curation support.
Authors:	Strasser K, McDonnell E, Nyaga C, Wu M, Wu S, Almeida H, Meurs MJ, Kosseim L, Powlowski J, Butler G, Tsang A
Link:	https://www.ncbi.nlm.nih.gov/pubmed/25754864?dopt=Abstract
DOI:	10.1093/database/bav008
Publication:	Database : the journal of biological databases and curation
Keywords:
PMID:	25754864	Category:	Database (Oxford)	Date Added:	2019-06-07
Dept Affiliation:	CSFG 1 Centre for Structural and Functional Genomics, Department of Computer Science and Software Engineering, Department of Chemistry and Biochemistry, and Department of Biology Concordia University, Montréal, QC, USA. 2 Centre for Structural and Functional Genomics, Department of Computer Science and Software Engineering, Department of Chemistry and Biochemistry, and Department of Biology Concordia University, Montréal, QC, USA Centre for Structural and Functional Genomics, Department of Computer Science and Software Engineering, Department of Chemistry and Biochemistry, and Department of Biology Concordia University, Montréal, QC, USA. 3 Centre for Structural and Functional Genomics, Department of Computer Science and Software Engineering, Department of Chemistry and Biochemistry, and Department of Biology Concordia University, Montréal, QC, USA Centre for Structural and Functional Genomics, Department of Computer Science and Software Engineering, Department of Chemistry and Biochemistry, and Department of Biology Concordia University, Montréal, QC, USA gregb@encs.concordia.ca.

Description:

mycoCLAP, the database for characterized lignocellulose-active proteins of fungal origin: resource and text mining curation support.

Database (Oxford). 2015;2015:

Authors: Strasser K, McDonnell E, Nyaga C, Wu M, Wu S, Almeida H, Meurs MJ, Kosseim L, Powlowski J, Butler G, Tsang A

Abstract

Enzymes active on components of lignocellulosic biomass are used for industrial applications ranging from food processing to biofuels production. These include a diverse array of glycoside hydrolases, carbohydrate esterases, polysaccharide lyases and oxidoreductases. Fungi are prolific producers of these enzymes, spurring fungal genome sequencing efforts to identify and catalogue the genes that encode them. To facilitate the functional annotation of these genes, biochemical data on over 800 fungal lignocellulose-degrading enzymes have been collected from the literature and organized into the searchable database, mycoCLAP (http://mycoclap.fungalgenomics.ca). First implemented in 2011, and updated as described here, mycoCLAP is capable of ranking search results according to closest biochemically characterized homologues: this improves the quality of the annotation, and significantly decreases the time required to annotate novel sequences. The database is freely available to the scientific community, as are the open source applications based on natural language processing developed to support the manual curation of mycoCLAP. Database URL: http://mycoclap.fungalgenomics.ca.

PMID: 25754864 [PubMed - indexed for MEDLINE]

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