Succinylation Site Prediction Based on Protein Sequences Using the IFS-LightGBM (BO) Model.
Comput Math Methods Med
; 2020: 8858489, 2020.
Article
in En
| MEDLINE
| ID: mdl-33224267
ABSTRACT
Succinylation is an important posttranslational modification of proteins, which plays a key role in protein conformation regulation and cellular function control. Many studies have shown that succinylation modification on protein lysine residue is closely related to the occurrence of many diseases. To understand the mechanism of succinylation profoundly, it is necessary to identify succinylation sites in proteins accurately. In this study, we develop a new model, IFS-LightGBM (BO), which utilizes the incremental feature selection (IFS) method, the LightGBM feature selection method, the Bayesian optimization algorithm, and the LightGBM classifier, to predict succinylation sites in proteins. Specifically, pseudo amino acid composition (PseAAC), position-specific scoring matrix (PSSM), disorder status, and Composition of k-spaced Amino Acid Pairs (CKSAAP) are firstly employed to extract feature information. Then, utilizing the combination of the LightGBM feature selection method and the incremental feature selection (IFS) method selects the optimal feature subset for the LightGBM classifier. Finally, to increase prediction accuracy and reduce the computation load, the Bayesian optimization algorithm is used to optimize the parameters of the LightGBM classifier. The results reveal that the IFS-LightGBM (BO)-based prediction model performs better when it is evaluated by some common metrics, such as accuracy, recall, precision, Matthews Correlation Coefficient (MCC), and F-measure.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Proteins
/
Protein Processing, Post-Translational
/
Succinic Acid
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Animals
/
Humans
Language:
En
Journal:
Comput Math Methods Med
Journal subject:
INFORMATICA MEDICA
Year:
2020
Document type:
Article
Affiliation country:
China