[HTML][HTML] Machine learning for metabolomics research in drug discovery
DD Martinelli - Intelligence-Based Medicine, 2023 - Elsevier
In a pharmaceutical context, metabolomics is an underexplored area of research.
Nevertheless, its utility in clinical pathology, biomarker discovery, metabolic subtyping, and …
Nevertheless, its utility in clinical pathology, biomarker discovery, metabolic subtyping, and …
ML-FGAT: Identification of multi-label protein subcellular localization by interpretable graph attention networks and feature-generative adversarial networks
C Wang, Y Wang, P Ding, S Li, X Yu, B Yu - Computers in Biology and …, 2024 - Elsevier
The prediction of multi-label protein subcellular localization (SCL) is a pivotal area in
bioinformatics research. Recent advancements in protein structure research have facilitated …
bioinformatics research. Recent advancements in protein structure research have facilitated …
MVML-MPI: Multi-View Multi-Label Learning for Metabolic Pathway Inference
Abstract Development of robust and effective strategies for synthesizing new compounds,
drug targeting and constructing GEnome-scale Metabolic models (GEMs) requires a deep …
drug targeting and constructing GEnome-scale Metabolic models (GEMs) requires a deep …
CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning
Motivation Metabolic stability plays a crucial role in the early stages of drug discovery and
development. Accurately modeling and predicting molecular metabolic stability has great …
development. Accurately modeling and predicting molecular metabolic stability has great …
A cautionary tale about properly vetting datasets used in supervised learning predicting metabolic pathway involvement
ED Huckvale, HNB Moseley - Plos one, 2024 - journals.plos.org
The mapping of metabolite-specific data to pathways within cellular metabolism is a major
data analysis step needed for biochemical interpretation. A variety of machine learning …
data analysis step needed for biochemical interpretation. A variety of machine learning …
Benchmark dataset for training machine learning models to predict the pathway involvement of metabolites
Metabolic pathways are a human-defined grouping of life sustaining biochemical reactions,
metabolites being both the reactants and products of these reactions. But many public …
metabolites being both the reactants and products of these reactions. But many public …
[HTML][HTML] Predicting the Association of Metabolites with Both Pathway Categories and Individual Pathways
ED Huckvale, HNB Moseley - Metabolites, 2024 - mdpi.com
Metabolism is a network of chemical reactions that sustain cellular life. Parts of this
metabolic network are defined as metabolic pathways containing specific biochemical …
metabolic network are defined as metabolic pathways containing specific biochemical …
A Novel Multi-Scale Graph Neural Network for Metabolic Pathway Prediction
Predicting the metabolic pathway classes of compounds in the human body is an important
problem in drug research and development. For this purpose, we propose a Multi-Scale …
problem in drug research and development. For this purpose, we propose a Multi-Scale …
Predicting the Pathway Involvement of Metabolites in Both Pathway Categories and Individual Pathways
ED Huckvale, HNB Moseley - bioRxiv, 2024 - biorxiv.org
Metabolism is the network of chemical reactions that sustain cellular life. Parts of this
metabolic network are defined as metabolic pathways containing specific biochemical …
metabolic network are defined as metabolic pathways containing specific biochemical …
Prediction of plant secondary metabolic pathways using deep transfer learning
H Bao, J Zhao, X Zhao, C Zhao, X Lu, G Xu - BMC bioinformatics, 2023 - Springer
Background Plant secondary metabolites are highly valued for their applications in
pharmaceuticals, nutrition, flavors, and aesthetics. It is of great importance to elucidate plant …
pharmaceuticals, nutrition, flavors, and aesthetics. It is of great importance to elucidate plant …