DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm

M Ullah, S Akbar, A Raza, Q Zou - Bioinformatics, 2024 - academic.oup.com
Motivation Despite the extensive manufacturing of antiviral drugs and vaccination, viral
infections continue to be a major human ailment. Antiviral peptides (AVPs) have emerged as …

Protein secondary structure prediction: A survey of the state of the art

Q Jiang, X **, SJ Lee, S Yao - Journal of Molecular Graphics and …, 2017 - Elsevier
Protein secondary structure prediction (PSSP) is a fundamental task in protein science and
computational biology, and it can be used to understand protein 3-dimensional (3-D) …

Designing template-free predictor for targeting protein-ligand binding sites with classifier ensemble and spatial clustering

DJ Yu, J Hu, J Yang, HB Shen, J Tang… - … /ACM transactions on …, 2013 - ieeexplore.ieee.org
Accurately identifying the protein-ligand binding sites or pockets is of significant importance
for both protein function analysis and drug design. Although much progress has been made …

Predicting protein-DNA binding residues by weightedly combining sequence-based features and boosting multiple SVMs

J Hu, Y Li, M Zhang, X Yang… - IEEE/ACM transactions …, 2016 - ieeexplore.ieee.org
Protein-DNA interactions are ubiquitous in a wide variety of biological processes. Correctly
locating DNA-binding residues solely from protein sequences is an important but …

Improving protein-ATP binding residues prediction by boosting SVMs with random under-sampling

DJ Yu, J Hu, ZM Tang, HB Shen, J Yang, JY Yang - Neurocomputing, 2013 - Elsevier
Correctly localizing the protein-ATP binding residues is valuable for both basic experimental
biology and drug discovery studies. Protein-ATP binding residues prediction is a typical …

DeepCPPred: a deep learning framework for the discrimination of cell-penetrating peptides and their uptake efficiencies

M Arif, M Kabir, S Ahmed, A Khan, F Ge… - IEEE/ACM …, 2021 - ieeexplore.ieee.org
Cell-penetrating peptides (CPPs) are special peptides capable of carrying a variety of
bioactive molecules, such as genetic materials, short interfering RNAs and nanoparticles …

A cascade random forests algorithm for predicting protein-protein interaction sites

ZS Wei, JY Yang, HB Shen… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Protein-protein interactions exist ubiquitously and play important roles in the life cycles of
living cells. The interaction sites (residues) are essential to understanding the underlying …

An enhanced protein secondary structure prediction using deep learning framework on hybrid profile based features

P Kumar, S Bankapur, N Patil - Applied Soft Computing, 2020 - Elsevier
Accurate protein secondary structure prediction (PSSP) is essential to identify structural
classes, protein folds, and its tertiary structure. To identify the secondary structure …

Constructing query-driven dynamic machine learning model with application to protein-ligand binding sites prediction

DJ Yu, J Hu, QM Li, ZM Tang, JY Yang… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
We are facing an era with annotated biological data rapidly and continuously generated.
How to effectively incorporate new annotated data into the learning step is crucial for …

Metaheuristics for Protein Structure Prediction: Review and Empirical Analysis

SO Oladejo - 2024 IEEE International Conference on Artificial …, 2024 - ieeexplore.ieee.org
Metaheuristics have been employed in solving several optimization and NP-hard problems
owing to their ability to avoid local optima entrapment, flexibility and robustness, simplicity …