A transformer-based ensemble framework for the prediction of protein–protein interaction sites

M Mou, Z Pan, Z Zhou, L Zheng, H Zhang, S Shi, F Li… - Research, 2023 - spj.science.org
The identification of protein–protein interaction (PPI) sites is essential in the research of
protein function and the discovery of new drugs. So far, a variety of computational tools …

Stabilization challenges and aggregation in protein-based therapeutics in the pharmaceutical industry

M Rahban, F Ahmad, MA Piatyszek, T Haertlé, L Saso… - RSC …, 2023 - pubs.rsc.org
Protein-based therapeutics have revolutionized the pharmaceutical industry and become
vital components in the development of future therapeutics. They offer several advantages …

Growing ecosystem of deep learning methods for modeling protein–protein interactions

JR Rogers, G Nikolényi… - … Engineering, Design and …, 2023 - academic.oup.com
Numerous cellular functions rely on protein–protein interactions. Efforts to comprehensively
characterize them remain challenged however by the diversity of molecular recognition …

A knowledge distillation-guided equivariant graph neural network for improving protein interaction site prediction performance

S Chen, Z Tang, L You, CYC Chen - Knowledge-Based Systems, 2024 - Elsevier
Protein–protein interactions play crucial roles in biological systems. The precise
identification of protein interaction sites is essential for advancing our understanding of …

MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction

J Wang, Z Yang, C Chen, G Yao, X Wan… - Briefings in …, 2024 - academic.oup.com
Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and
target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme …

Deciphering 3'UTR Mediated Gene Regulation Using Interpretable Deep Representation Learning

Y Yang, G Li, K Pang, W Cao, Z Zhang… - Advanced Science, 2024 - Wiley Online Library
Abstract The 3'untranslated regions (3'UTRs) of messenger RNAs contain many important
cis‐regulatory elements that are under functional and evolutionary constraints. It is …

PDNAPred: Interpretable prediction of protein-DNA binding sites based on pre-trained protein language models

L Zhang, T Liu - International Journal of Biological Macromolecules, 2024 - Elsevier
Protein-DNA interactions play critical roles in various biological processes and are essential
for drug discovery. However, traditional experimental methods are labor-intensive and …

[PDF][PDF] Diversification of the Rho transcription termination factor in bacteria

SM Moreira, T Chyou, JT Wade… - Nucleic acids …, 2024 - academic.oup.com
Correct termination of transcription is essential for gene expression. In bacteria, factor-
dependent termination relies on the Rho factor, that classically has three conserved …

Deep learning in computational biology: Advancements, challenges, and future outlook

S Kumar, D Guruparan, P Aaron, P Telajan… - arxiv preprint arxiv …, 2023 - arxiv.org
Deep learning has become a powerful tool in computational biology, revolutionising the
analysis and interpretation of biological data over time. In our article review, we delve into …

Insights into the inner workings of transformer models for protein function prediction

M Wenzel, E Grüner, N Strodthoff - Bioinformatics, 2024 - academic.oup.com
Motivation We explored how explainable artificial intelligence (XAI) can help to shed light
into the inner workings of neural networks for protein function prediction, by extending the …