Keyword search (4,163 papers available)

"Butler G" Authored Publications:

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:BENIN: Biologically enhanced network inference.
Authors:Wonkap SK,  Butler G
Link:https://www.ncbi.nlm.nih.gov/pubmed/32698722
DOI:10.1142/S0219720020400077
Publication:Journal of bioinformatics and computational biology
Keywords:Gene regulatory network;  data integration;  elastic net;  feature selection;  network inference; 
PMID:32698722 Category:J Bioinform Comput Biol Date Added:2020-07-24
Dept Affiliation: ENCS
1 Computer Science and Software Engineering, Concordia University, 1455 Boulevard de Maisonneuve Ouest, Montreal, Quebec H3G1M8, Canada.

Description:

BENIN: Biologically enhanced network inference.

J Bioinform Comput Biol. 2020 Jun;18(3):2040007

Authors: Wonkap SK, Butler G

Abstract

Gene regulatory network inference is one of the central problems in computational biology. We need models that integrate the variety of data available in order to use their complementarity information to overcome the issues of noisy and limited data. BENIN: Biologically Enhanced Network INference is our proposal to integrate data and infer more accurate networks. BENIN is a general framework that jointly considers different types of prior knowledge with expression datasets to improve the network inference. The method states the network inference as a feature selection problem and uses a popular penalized regression method, the Elastic net, combined with bootstrap resampling to solve it. BENIN significantly outperforms the state-of-the-art methods on the simulated data from the DREAM 4 challenge when combining genome-wide location data, knockout gene expression data, and time series expression data.

PMID: 32698722 [PubMed - in process]




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