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Integrative approach for detecting membrane proteins.

Author(s): Alballa M, Butler G

BACKGROUND: Membrane proteins are key gates that control various vital cellular functions. Membrane proteins are often detected using transmembrane topology prediction tools. While transmembrane topology prediction tools can detect integral membrane protein...

Article GUID: 33349234
BENIN: Biologically enhanced network inference.

Author(s): Wonkap SK, Butler G

J Bioinform Comput Biol. 2020 Jun;18(3):2040007 Authors: Wonkap SK, Butler G

Article GUID: 32698722
TooT-T: discrimination of transport proteins from non-transport proteins.

Author(s): Alballa M, Butler G

BMC Bioinformatics. 2020 Apr 23;21(Suppl 3):25 Authors: Alballa M, Butler G

Article GUID: 32321420
TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information.

Author(s): Alballa M, Aplop F, Butler G

PLoS One. 2020;15(1):e0227683 Authors: Alballa M, Aplop F, Butler G

Article GUID: 31935244
Analytical and computational approaches to define the Aspergillus niger secretome.

Author(s): Tsang A, Butler G, Powlowski J, Panisko EA, Baker SE

Fungal Genet Biol. 2009 Mar;46 Suppl 1:S153-S160 Authors: Tsang A, Butler G, Powlowski J, Panisko EA, Baker SE

Article GUID: 19618504
SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models.

Author(s): Reid I, O'Toole N, Zabaneh O, Nourzadeh R, Dahdouli M, Abdellateef M, Gordon PM, Soh J, Butler G, Sensen CW, Tsang A

BMC Bioinformatics. 2014 Jul 01;15:229 Authors: Reid I, O'Toole N, Zabaneh O, Nourzadeh R, Dahdouli M, Abdellateef M, Gordon PM, Soh J, Butler G, Sensen CW, Tsang A

Article GUID: 24980894
Machine learning for biomedical literature triage.

Author(s): Almeida H, Meurs MJ, Kosseim L, Butler G, Tsang A

PLoS One. 2014;9(12):e115892 Authors: Almeida H, Meurs MJ, Kosseim L, Butler G, Tsang A

Article GUID: 25551575
mycoCLAP, the database for characterized lignocellulose-active proteins of fungal origin: resource and text mining curation support.

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

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

Article GUID: 25754864
An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures.

Author(s): Zandi K, Butler G, Kharma N

Front Genet. 2016;7:129 Authors: Zandi K, Butler G, Kharma N

Article GUID: 27499762
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
Category:Database (Oxford)
PMID:25754864
Dept Affiliation: GENOMICS
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]