Journal of Bioinformatics and Computational Biology This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

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 28:2350024. doi: 10.1142/S0219720023500245. Online ahead of print.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-O...
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

Analyzing omics data by feature combinations based on kernel functions
J Bioinform Comput Biol. 2023 Oct 18:2350021. doi: 10.1142/S021972002350021X. Online ahead of print.ABSTRACTDefining meaningful feature (molecule) combinations can enhance the study of disease diagnosis and prognosis. However, feature combinations are complex and various in biosystems, and the existing methods examine the feature cooperation in a single, fixed pattern for all feature pairs, such as linear combination. To identify the appropriate combination between two features and evaluate feature combination more comprehensively, this paper adopts kernel functions to study feature relationships and proposes a new omics d...
Source: Journal of Bioinformatics and Computational Biology - October 18, 2023 Category: Bioinformatics Authors: Chao Li Tianxiang Wang Xiaohui Lin Source Type: research