mACPpred 2.0: Stacked deep learning for anticancer peptide prediction with integrated spatial and probabilistic feature representations

VK Sangaraju, NT Pham, L Wei, X Yu… - Journal of Molecular …, 2024 - Elsevier
Anticancer peptides (ACPs), naturally occurring molecules with remarkable potential to
target and kill cancer cells. However, identifying ACPs based solely from their primary amino …

The Dawn of a New Pharmaceutical Epoch: Can AI and Robotics Reshape Drug Formulation?

P Bannigan, RJ Hickman… - Advanced Healthcare …, 2024 - Wiley Online Library
Over the last four decades, pharmaceutical companies' expenditures on research and
development have increased 51‐fold. During this same time, clinical success rates for new …

PhosBERT: A self-supervised learning model for identifying phosphorylation sites in SARS-CoV-2-infected human cells

Y Li, R Gao, S Liu, H Zhang, H Lv, H Lai - Methods, 2024 - Elsevier
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA
virus, which mainly causes respiratory and enteric diseases and is responsible for the …

E-mula: an ensemble multi-localized attention feature extraction network for viral protein subcellular localization

GM Bakanina Kissanga, H Zulfiqar, S Gao, SB Yussif… - Information, 2024 - mdpi.com
Accurate prediction of subcellular localization of viral proteins is crucial for understanding
their functions and developing effective antiviral drugs. However, this task poses a …

mHPpred: Accurate identification of peptide hormones using multi-view feature learning

S Basith, VK Sangaraju, B Manavalan, G Lee - Computers in Biology and …, 2024 - Elsevier
Peptide hormones were first used in medicine in the early 20th century, with the pivotal
event being the isolation and purification of insulin in 1921. These hormones are integral to …

A protein pre-trained model-based approach for the identification of the liquid-liquid phase separation (LLPS) proteins

Z Ahmed, K Shahzadi, SA Temesgen, B Ahmad… - International Journal of …, 2024 - Elsevier
Liquid-liquid phase separation (LLPS) regulates many biological processes including RNA
metabolism, chromatin rearrangement, and signal transduction. Aberrant LLPS potentially …

MST-m6A: A Novel Multi-Scale Transformer-based Framework for Accurate Prediction of m6A Modification Sites Across Diverse Cellular Contexts

Q Su, NT Pham, L Wei, B Manavalan - Journal of Molecular Biology, 2024 - Elsevier
Abstract N6-methyladenosine (m6A) modification, a prevalent epigenetic mark in eukaryotic
cells, is crucial in regulating gene expression and RNA metabolism. Accurately identifying …

ACVPred: Enhanced prediction of anti-coronavirus peptides by transfer learning combined with data augmentation

Y Xu, T Liu, Y Yang, J Kang, L Ren, H Ding… - Future Generation …, 2024 - Elsevier
Anti-coronavirus peptides (ACVPs) have garnered significant attention in COVID-19
therapeutic research due to their precise targeting, low risk of drug resistance, flexible …

Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration

X Wang, C Yu, Y Sun, Y Liu, S Tang, Y Sun… - Computers in Biology …, 2024 - Elsevier
Background The morphological attributes could serve as pivotal indicators precipitating
early recurrence and dismal overall survival in hepatocellular carcinoma (HCC), and …

METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images

Y Sun, J Guo, Y Liu, N Wang, Y Xu, F Wu, J Xiao… - Computers in Biology …, 2024 - Elsevier
Background Mesenchymal epithelial transformation (MET) is a key molecular target for
diagnosis and treatment of non-small cell lung cancer (NSCLC). The corresponding …