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Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins

Thermophilic proteins (TPPs) are critical for basic research and in the food industry due to their ability to maintain a thermodynamically stable fold at extremely high temperatures. Thus, the expeditious identification of novel TPPs through computational models from protein sequences is very desira...

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Huvudupphov: Phasit Charoenkwan, Nalini Schaduangrat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lió, Watshara Shoombuatong
Materialtyp: Artigo
Språk:Inglês
Utgiven: IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund 2022-03-01
Serie:EXCLI Journal : Experimental and Clinical Sciences
Ämnen:
thermophilic protein
bioinformatics
classification
machine learning
feature representation
feature selection
Länkar:https://www.excli.de/index.php/excli/article/view/4723
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