Applying interpretable machine learning in computational biology—pitfalls, recommendations and opportunities for new developments

V Chen, M Yang, W Cui, JS Kim, A Talwalkar, J Ma - Nature methods, 2024 - nature.com
Recent advances in machine learning have enabled the development of next-generation
predictive models for complex computational biology problems, thereby spurring the use of …

Machine learning for antimicrobial peptide identification and design

F Wan, F Wong, JJ Collins… - Nature Reviews …, 2024 - nature.com
Artificial intelligence (AI) and machine learning (ML) models are being deployed in many
domains of society and have recently reached the field of drug discovery. Given the …

[HTML][HTML] Automated data processing and feature engineering for deep learning and big data applications: a survey

A Mumuni, F Mumuni - Journal of Information and Intelligence, 2024 - Elsevier
Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …

SeqNAS: Neural architecture search for event sequence classification

I Udovichenko, E Shvetsov, D Divitsky, D Osin… - IEEE …, 2024 - ieeexplore.ieee.org
Neural Architecture Search (NAS) methods are widely used in various industries to obtain
high-quality, task-specific solutions with minimal human intervention. Event Sequences …

[PDF][PDF] AutoXAI4Omics: an automated explainable AI tool for omics and tabular data

J Strudwick, LJ Gardiner… - Briefings in …, 2025 - academic.oup.com
Abstract Machine learning (ML) methods offer opportunities for gaining insights into the
intricate workings of complex biological systems, and their applications are increasingly …

[HTML][HTML] Generative and predictive neural networks for the design of functional RNA molecules

AT Riley, JM Robson, AA Green - bioRxiv, 2023 - ncbi.nlm.nih.gov
RNA is a remarkably versatile molecule that has been engineered for applications in
therapeutics, diagnostics, and in vivo information-processing systems. However, the …

Current computational tools for protein lysine acylation site prediction

Z Qin, H Ren, P Zhao, K Wang, H Liu… - Briefings in …, 2024 - academic.oup.com
As a main subtype of post-translational modification (PTM), protein lysine acylations (PLAs)
play crucial roles in regulating diverse functions of proteins. With recent advancements in …

GPro: generative AI-empowered toolkit for promoter design

H Wang, Q Du, Y Wang, H Xu, Z Wei, X Wang - Bioinformatics, 2024 - academic.oup.com
Motivation Promoters with desirable properties are crucial in biotechnological applications.
Generative AI (GenAI) has demonstrated potential in creating novel synthetic promoters with …

Synthetic translational coupling system for accurate and predictable polycistronic gene expression control in bacteria

YH Han, HJ Kim, K Kim, J Yang, SW Seo - Metabolic Engineering, 2024 - Elsevier
Precise and predictable genetic elements are required to address various issues, such as
suboptimal metabolic flux or imbalanced protein assembly caused by the inadequate control …

Physicians should build their own machine-learning models

YM Mekki - Patterns, 2024 - cell.com
Yosra Mekki suggests that doctors should have the ability to develop their own machine-
learning models. She proposes an approach with the" spotlight" on physicians, to create …