AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model
This study demonstrates that our proposed method is simple and efficient for PPII prediction without using pre-trained large models or complex features such as position-specific scoring matrices.PMID:37899354 | DOI:10.1142/S0219720023500221 (Source: Journal of Bioinformatics and Computational Biology)
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Jiasheng He Shun Zhang Chun Fang Source Type: research

CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection
J Bioinform Comput Biol. 2023 Oct;21(5):2350024. doi: 10.1142/S0219720023500245. Epub 2023 Oct 28.ABSTRACTO-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier design, greatly affect the accuracy of computational methods for predicting Oglyc sites. Based on an efficient feature selection algorithm and a classifier capable of handling imbalanced datasets, a new computational method, ChiMIC-based balanced decision table O-glycosylation (CBDT-Ogl...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Ying Zeng Zheming Yuan Yuan Chen Ying Hu Source Type: research

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm
In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Zizheng Yu Zhijian Yin Hongliang Zou Source Type: research

AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model
This study demonstrates that our proposed method is simple and efficient for PPII prediction without using pre-trained large models or complex features such as position-specific scoring matrices.PMID:37899354 | DOI:10.1142/S0219720023500221 (Source: Journal of Bioinformatics and Computational Biology)
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Jiasheng He Shun Zhang Chun Fang Source Type: research

CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection
J Bioinform Comput Biol. 2023 Oct;21(5):2350024. doi: 10.1142/S0219720023500245. Epub 2023 Oct 28.ABSTRACTO-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier design, greatly affect the accuracy of computational methods for predicting Oglyc sites. Based on an efficient feature selection algorithm and a classifier capable of handling imbalanced datasets, a new computational method, ChiMIC-based balanced decision table O-glycosylation (CBDT-Ogl...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Ying Zeng Zheming Yuan Yuan Chen Ying Hu Source Type: research

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm
In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Zizheng Yu Zhijian Yin Hongliang Zou Source Type: research

AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model
This study demonstrates that our proposed method is simple and efficient for PPII prediction without using pre-trained large models or complex features such as position-specific scoring matrices.PMID:37899354 | DOI:10.1142/S0219720023500221 (Source: Journal of Bioinformatics and Computational Biology)
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Jiasheng He Shun Zhang Chun Fang Source Type: research

CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection
J Bioinform Comput Biol. 2023 Oct;21(5):2350024. doi: 10.1142/S0219720023500245. Epub 2023 Oct 28.ABSTRACTO-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier design, greatly affect the accuracy of computational methods for predicting Oglyc sites. Based on an efficient feature selection algorithm and a classifier capable of handling imbalanced datasets, a new computational method, ChiMIC-based balanced decision table O-glycosylation (CBDT-Ogl...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Ying Zeng Zheming Yuan Yuan Chen Ying Hu Source Type: research

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm
In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Zizheng Yu Zhijian Yin Hongliang Zou Source Type: research

AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model
This study demonstrates that our proposed method is simple and efficient for PPII prediction without using pre-trained large models or complex features such as position-specific scoring matrices.PMID:37899354 | DOI:10.1142/S0219720023500221 (Source: Journal of Bioinformatics and Computational Biology)
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Jiasheng He Shun Zhang Chun Fang Source Type: research

CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection
J Bioinform Comput Biol. 2023 Oct;21(5):2350024. doi: 10.1142/S0219720023500245. Epub 2023 Oct 28.ABSTRACTO-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier design, greatly affect the accuracy of computational methods for predicting Oglyc sites. Based on an efficient feature selection algorithm and a classifier capable of handling imbalanced datasets, a new computational method, ChiMIC-based balanced decision table O-glycosylation (CBDT-Ogl...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Ying Zeng Zheming Yuan Yuan Chen Ying Hu Source Type: research

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm
In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Zizheng Yu Zhijian Yin Hongliang Zou Source Type: research

AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model
This study demonstrates that our proposed method is simple and efficient for PPII prediction without using pre-trained large models or complex features such as position-specific scoring matrices.PMID:37899354 | DOI:10.1142/S0219720023500221 (Source: Journal of Bioinformatics and Computational Biology)
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Jiasheng He Shun Zhang Chun Fang Source Type: research

CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection
J Bioinform Comput Biol. 2023 Oct;21(5):2350024. doi: 10.1142/S0219720023500245. Epub 2023 Oct 28.ABSTRACTO-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier design, greatly affect the accuracy of computational methods for predicting Oglyc sites. Based on an efficient feature selection algorithm and a classifier capable of handling imbalanced datasets, a new computational method, ChiMIC-based balanced decision table O-glycosylation (CBDT-Ogl...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Ying Zeng Zheming Yuan Yuan Chen Ying Hu Source Type: research

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm
In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector...
Source: Journal of Bioinformatics and Computational Biology - October 29, 2023 Category: Bioinformatics Authors: Zizheng Yu Zhijian Yin Hongliang Zou Source Type: research