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Ion channel classification through machine learning and protein language model embeddings

Author(s): Ghazikhani H; Butler G;

Ion channels are critical membrane proteins that regulate ion flux across cellular membranes, influencing numerous biological functions. The resource-intensive nature of traditional wet lab experiments for ion channel identification has led to an increasing emphasis on computational techniques. This study extends our previous work on protein language mode ...

Article GUID: 39572876


SPOT: A machine learning model that predicts specific substrates for transport proteins

Author(s): Kroll A; Niebuhr N; Butler G; Lercher MJ;

Transport proteins play a crucial role in cellular metabolism and are central to many aspects of molecular biology and medicine. Determining the function of transport proteins experimentally is challenging, as they become unstable when isolated from cell membranes. Machine learning-based predictions could provide an efficient alternative. However, existin ...

Article GUID: 39325691


Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Author(s): 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; Henri ...

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophil ...

Article GUID: 39266695


Exploiting protein language models for the precise classification of ion channels and ion transporters

Author(s): Ghazikhani H; Butler G;

This study introduces TooT-PLM-ionCT, a comprehensive framework that consolidates three distinct systems, each meticulously tailored for one of the following tasks: distinguishing ion channels (ICs) from membrane proteins (MPs), segregating ion transporters (ITs) from MPs, and differentiating ICs from ITs. Drawing upon the strengths of six Protein Languag ...

Article GUID: 38656743


Enhanced identification of membrane transport proteins: a hybrid approach combining ProtBERT-BFD and convolutional neural networks

Author(s): Ghazikhani H; Butler G;

Transmembrane transport proteins (transporters) play a crucial role in the fundamental cellular processes of all organisms by facilitating the transport of hydrophilic substrates across hydrophobic membranes. Despite the availability of numerous membrane protein sequences, their structures and functions remain largely elusive. Recently, natural language p ...

Article GUID: 37497772


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 proteins, they do not address surface-bound proteins. In this study, we focused on finding the best techniq ...

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


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