AIMC Topic: Metabolic Networks and Pathways

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Deep learning for metabolic pathway design.

Metabolic engineering
The establishment of a bio-based circular economy is imperative in tackling the climate crisis and advancing sustainable development. In this realm, the creation of microbial cell factories is central to generating a variety of chemicals and material...

DeepRT: Predicting compounds presence in pathway modules and classifying into module classes using deep neural networks based on molecular properties.

Journal of bioinformatics and computational biology
Metabolic pathways play a crucial role in understanding the biochemistry of organisms. In metabolic pathways, modules refer to clusters of interconnected reactions or sub-networks representing specific functional units or biological processes within ...

Modeling of astaxanthin biosynthesis via machine learning, mathematical and metabolic network modeling.

Critical reviews in biotechnology
Natural astaxanthin is synthesized by diverse organisms including: bacteria, fungi, microalgae, and plants involving complex cellular processes, which depend on numerous interrelated parameters. Nonetheless, existing knowledge regarding astaxanthin b...

Message Passing Neural Networks Improve Prediction of Metabolite Authenticity.

Journal of chemical information and modeling
Cytochrome P450 enzymes aid in the elimination of a preponderance of small molecule drugs, but can generate reactive metabolites that may adversely react with protein and DNA and prompt drug candidate attrition or market withdrawal. Previously develo...

Exploring the expressiveness of abstract metabolic networks.

PloS one
Metabolism is characterised by chemical reactions linked to each other, creating a complex network structure. The whole metabolic network is divided into pathways of chemical reactions, such that every pathway is a metabolic function. A simplified re...

Metabolic engineering for sustainability and health.

Trends in biotechnology
Bio-based production of chemicals and materials has attracted much attention due to the urgent need to establish sustainability and enhance human health. Metabolic engineering (ME) allows purposeful modification of cellular metabolic, regulatory, and...

A novel hybrid framework for metabolic pathways prediction based on the graph attention network.

BMC bioinformatics
BACKGROUND: Making clear what kinds of metabolic pathways a drug compound involves in can help researchers understand how the drug is absorbed, distributed, metabolized, and excreted. The characteristics of a compound such as structure, composition a...

DeepRF: A deep learning method for predicting metabolic pathways in organisms based on annotated genomes.

Computers in biology and medicine
The rapid increase of metabolomics has led to an increasing focus on metabolic pathway modeling and reconstruction. In particular, reconstructing an organism's metabolic network based on its genome sequence is a key challenge in systems biology. The ...

Machine Learning Study of Metabolic Networks ChEMBL Data of Antibacterial Compounds.

Molecular pharmaceutics
Antibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. However, antibiotic resistance and the emergence of multidrug-resistant bacteria increase interest in understanding metabolic network (MN) mutations an...

Establishment of a Combined Diagnostic Model of Abdominal Aortic Aneurysm with Random Forest and Artificial Neural Network.

BioMed research international
OBJECTIVES: Abdominal aortic aneurysm (AAA), a disease with high mortality, is limited by the current diagnostic methods in the early screening. This study aimed to screen novel and significant biomarkers and construct a diagnostic model for AAA by u...