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Metabolic Networks and Pathways

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A Support Vector Machine Model Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis at the Transcript Levels.

BioMed research international
OBJECTIVE: Familial adenomatous polyposis (FAP) is one major type of inherited duodenal cancer. The estimate of duodenal cancer risk in patients with FAP is critical for selecting the optimal treatment strategy.

Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning.

Cell systems
Mechanistic models explicitly represent hypothesized biological knowledge. As such, they offer more generalizability than data-driven models. However, identifying model curation efforts that improve performance for mechanistic models is nontrivial. H...

The Metabolic Rainbow: Deep Learning Phase I Metabolism in Five Colors.

Journal of chemical information and modeling
Metabolism of drugs affects their absorption, distribution, efficacy, excretion, and toxicity profiles. Metabolism is routinely assessed experimentally using recombinant enzymes, human liver microsome, and animal models. Unfortunately, these experime...

Improving lipid mapping in Genome Scale Metabolic Networks using ontologies.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: To interpret metabolomic and lipidomic profiles, it is necessary to identify the metabolic reactions that connect the measured molecules. This can be achieved by putting them in the context of genome-scale metabolic network reconstructi...

Machine Learning and Bioinformatics Models to Identify Pathways that Mediate Influences of Welding Fumes on Cancer Progression.

Scientific reports
Welding generates and releases fumes that are hazardous to human health. Welding fumes (WFs) are a complex mix of metallic oxides, fluorides and silicates that can cause or exacerbate health problems in exposed individuals. In particular, WF inhalati...

A deep learning architecture for metabolic pathway prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Understanding the mechanisms and structural mappings between molecules and pathway classes are critical for design of reaction predictors for synthesizing new molecules. This article studies the problem of prediction of classes of metabol...

SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice.

Plant science : an international journal of experimental plant biology
Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data ...

Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.

Molecules (Basel, Switzerland)
The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how the...

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism.

Nature communications
Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be c...

Metabolic pathway inference using multi-label classification with rich pathway features.

PLoS computational biology
Metabolic inference from genomic sequence information is a necessary step in determining the capacity of cells to make a living in the world at different levels of biological organization. A common method for determining the metabolic potential encod...