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...
Saved in:
Main Author: | Charoenkwan P. |
---|---|
Other Authors: | Mahidol University |
Format: | Article |
Published: |
2023
|
Subjects: | |
Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/83863 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Mahidol University |
Similar Items
-
EMPIRICAL COMPARISON AND ANALYSIS OF MACHINE LEARNING-BASED PREDICTORS FOR PREDICTING AND ANALYZING OF THERMOPHILIC PROTEINS
by: Phasit Charoenkwan, et al.
Published: (2022) -
Review and Comparative Analysis of Machine Learning-based Predictors for Predicting and Analyzing Anti-angiogenic Peptides
by: Charoenkwan P.
Published: (2023) -
Review and Comparative Analysis of Machine Learning-based Predictors for Predicting and Analyzing Anti-angiogenic Peptides
by: Phasit Charoenkwan, et al.
Published: (2022) -
EMPIRICAL COMPARISON AND ANALYSIS OF MACHINE LEARNING-BASED APPROACHES FOR DRUGGABLE PROTEIN IDENTIFICATION
by: Shoombuatong W.
Published: (2023) -
RECENT DEVELOPMENT OF MACHINE LEARNING-BASED METHODS FOR THE PREDICTION OF DEFENSIN FAMILY AND SUBFAMILY
by: Charoenkwan P.
Published: (2023)