Applying interpretable machine learning in computational biology—pitfalls, recommendations and opportunities for new developments
Recent advances in machine learning have enabled the development of next-generation
predictive models for complex computational biology problems, thereby spurring the use of …
predictive models for complex computational biology problems, thereby spurring the use of …
Machine learning for antimicrobial peptide identification and design
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 …
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 …
from data. This approach has achieved impressive results and has contributed significantly …
SeqNAS: Neural architecture search for event sequence classification
Neural Architecture Search (NAS) methods are widely used in various industries to obtain
high-quality, task-specific solutions with minimal human intervention. Event Sequences …
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 …
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
RNA is a remarkably versatile molecule that has been engineered for applications in
therapeutics, diagnostics, and in vivo information-processing systems. However, the …
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 …
play crucial roles in regulating diverse functions of proteins. With recent advancements in …
GPro: generative AI-empowered toolkit for promoter design
Motivation Promoters with desirable properties are crucial in biotechnological applications.
Generative AI (GenAI) has demonstrated potential in creating novel synthetic promoters with …
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 …
suboptimal metabolic flux or imbalanced protein assembly caused by the inadequate control …