[HTML][HTML] Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods

H Zulfiqar, Z Guo, BK Grace-Mercure, ZY Zhang… - Computational and …, 2023 - Elsevier
Hormone binding proteins (HBPs) belong to the group of soluble carrier proteins. These
proteins selectively and non-covalently interact with hormones and promote growth …

Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique

H Zulfiqar, QL Huang, H Lv, ZJ Sun, FY Dao… - International Journal of …, 2022 - mdpi.com
4mC is a type of DNA alteration that has the ability to synchronize multiple biological
movements, for example, DNA replication, gene expressions, and transcriptional …

REGLIV: molecular regulation data of diverse living systems facilitating current multiomics research

S Zhang, X Sun, M Mou, K Amahong, H Sun… - Computers in Biology …, 2022 - Elsevier
Multiomics is a powerful technique in molecular biology that facilitates the identification of
new associations among different molecules (genes, proteins & metabolites). It has attracted …

[HTML][HTML] IBPred: A sequence-based predictor for identifying ion binding protein in phage

SS Yuan, D Gao, XQ Xie, CY Ma, W Su… - Computational and …, 2022 - Elsevier
Ion binding proteins (IBPs) can selectively and non-covalently interact with ions. IBPs in
phages also play an important role in biological processes. Therefore, accurate identification …

AAPred-CNN: Accurate predictor based on deep convolution neural network for identification of anti-angiogenic peptides

C Lin, L Wang, L Shi - Methods, 2022 - Elsevier
Recently, deep learning techniques have been developed for various bioactive peptide
prediction tasks. However, there are only conventional machine learning-based methods for …

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

C Lu, J Jiang, Q Chen, H Liu, X Ju, H Wang - BMC genomics, 2024 - Springer
Background Most of the important biological mechanisms and functions of transmembrane
proteins (TMPs) are realized through their interactions with non-transmembrane proteins …

Prediction of protein interactions between pine and pine wood nematode using deep learning and multi-dimensional feature fusion

L Wang, R Li, X Guan, S Yan - Frontiers in Plant Science, 2024 - frontiersin.org
Pine Wilt Disease (PWD) is a devastating forest disease that has a serious impact on
ecological balance ecological. Since the identification of plant-pathogen protein interactions …

Predicting compound-protein interaction by deepening the systemic background via molecular network feature embedding

H Wang, H Zhu, W Li, M Liu, L Zhang… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Identifying compound-protein interactions (CPI) is crucial for drug screening, drug
repurposing, and combination therapy studies. The performance of CPI prediction depends …

MCPI: Integrating Multimodal Data for Enhanced Prediction of Compound Protein Interactions

L Zhang, W Li, H Guan, Z He, M Cheng… - arXiv preprint arXiv …, 2023 - arxiv.org
The identification of compound-protein interactions (CPI) plays a critical role in drug
screening, drug repurposing, and combination therapy studies. The effectiveness of CPI …

Pseudo-188D: Phage Protein Prediction Based on a Model of Pseudo-188D

X Gu, L Guo, B Liao, Q Jiang - Frontiers in Genetics, 2021 - frontiersin.org
Phages have seriously affected the biochemical systems of the world, and not only are
phages related to our health, but medical treatments for many cancers and skin infections …