Advancing peptide-based cancer therapy with AI: in-depth analysis of state-of-the-art AI models

S Bhattarai, H Tayara, KT Chong - Journal of Chemical …, 2024 - ACS Publications
Anticancer peptides (ACPs) play a vital role in selectively targeting and eliminating cancer
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …

Multi-dimensional deep learning drives efficient discovery of novel neuroprotective peptides from walnut protein isolates

L Lin, C Li, L Zhang, Y Zhang, L Gao, T Li, L **… - Food & Function, 2023 - pubs.rsc.org
Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are multi-factor induced
neurological disorders that require management from multiple pathologies. The peptides …

Dynamic Visualization of Computer-Aided Peptide Design for Cancer Therapeutics

D Hou, H Zhou, Y Tang, Z Liu, L Su, J Guo… - Drug Design …, 2025 - Taylor & Francis
Purpose Cancer stands as a significant global public health concern, with traditional
therapies potentially yielding severe side effects. Peptide-based cancer therapy is …

Discovery of anticancer peptides from natural and generated sequences using deep learning

J Yue, T Li, J Xu, Z Chen, Y Li, S Liang, Z Liu… - International Journal of …, 2025 - Elsevier
Anticancer peptides (ACPs) demonstrate significant potential in clinical cancer treatment
due to their ability to selectively target and kill cancer cells. In recent years, numerous …

Classification of Hand-Movement Disabilities in Parkinson's Disease Using a Motion-Capture Device and Machine Learning

J Shin, M Matsumoto, M Maniruzzaman… - IEEE …, 2024 - ieeexplore.ieee.org
Parkinson's disease (PD) is a neurological disorder caused by degeneration of
dopaminergic neurons in the midbrain. PD patients mainly suffer from motor symptoms …

iACP-GE: accurate identification of anticancer peptides by using gradient boosting decision tree and extra tree

Y Liang, X Ma - SAR and QSAR in Environmental Research, 2023 - Taylor & Francis
Cancer is one of the main diseases threatening human life, accounting for millions of deaths
around the world each year. Traditional physical and chemical methods for cancer treatment …

Contrastive learning for enhancing feature extraction in anticancer peptides

B Lee, D Shin - Briefings in Bioinformatics, 2024 - academic.oup.com
Cancer, recognized as a primary cause of death worldwide, has profound health
implications and incurs a substantial social burden. Numerous efforts have been made to …

An efficient consolidation of word embedding and deep learning techniques for classifying anticancer peptides: FastText+ BiLSTM

O Karakaya, ZH Kilimci - PeerJ Computer Science, 2024 - peerj.com
Anticancer peptides (ACPs) are a group of peptides that exhibit antineoplastic properties.
The utilization of ACPs in cancer prevention can present a viable substitute for conventional …

Apex-phla: A novel method for accurate prediction of the binding between exogenous short peptides and hla class i molecules

Z Su, Y Wu, K Cao, J Du, L Cao, Z Wu, X Wu, X Wang… - Methods, 2024 - Elsevier
Human leukocyte antigen (HLA) molecules play critically significant role within the realm of
immunotherapy due to their capacities to recognize and bind exogenous antigens such as …

MDTL-ACP: Anticancer Peptides Prediction Based on Multi-Domain Transfer Learning

J Cao, W Zhou, Q Yu, J Ji, J Zhang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Anticancer peptides (ACPs) have emerged as one of the most promising therapeutic agents
for cancer treatment. They are bioactive peptides featuring broad-spectrum activity and low …