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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:Analytical and computational approaches to define the Aspergillus niger secretome.
Authors:Tsang A,  Butler G,  Powlowski J,  Panisko EA,  Baker SE
Link:https://www.ncbi.nlm.nih.gov/pubmed/19618504?dopt=Abstract
DOI:10.1016/j.fgb.2008.07.014
Category:Fungal Genet Biol
PMID:19618504
Dept Affiliation: BIOLOGY
1 Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke West, Montréal, Québec, Canada H4B 1R6, Department of Biology, Concordia University, Montréal, Québec, Canada. tsang@gene.concordia.ca

Description:

Analytical and computational approaches to define the Aspergillus niger secretome.

Fungal Genet Biol. 2009 Mar;46 Suppl 1:S153-S160

Authors: Tsang A, Butler G, Powlowski J, Panisko EA, Baker SE

Abstract

We used computational and mass spectrometric approaches to characterize the Aspergillus niger secretome.The 11,200 gene models predicted in the genome of A. niger strain ATCC 1015 were the data source for the analysis. Depending on the computational methods used, 691 to 881 proteins were predicted to be secreted proteins. We cultured A. niger in six different media and analyzed the extracellular proteins produced using mass spectrometry. A total of 222 proteins were identified, with 39 proteins expressed under all six conditions and 74 proteins expressed under only one condition. The secreted proteins identified by mass spectrometry were used to guide the correction of about 20 gene models. Additional analysis focused on extracellular enzymes of interest for biomass processing. Of the 63 glycoside hydrolases predicted to be capable of hydrolyzing cellulose, hemicellulose or pectin, 94% of the exo-acting enzymes and only 18% of the endo-acting enzymes were experimentally detected.

PMID: 19618504 [PubMed - indexed for MEDLINE]