AIMC Topic: Metabolic Networks and Pathways

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Ensemble learning application to discover new trypanothione synthetase inhibitors.

Molecular diversity Jul 15, 2021
Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is ...
Drug Evaluation, Preclinical Enzyme Inhibitors Antiprotozoal Agents Databases, Pharmaceutical Models, Theoretical Structure-Activity Relationship Metabolic Networks and Pathways Amide Synthases Humans Drug Discovery ROC Curve Machine Learning Algorithms
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SCOUR: a stepwise machine learning framework for predicting metabolite-dependent regulatory interactions.

BMC bioinformatics Jul 8, 2021
BACKGROUND: The topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms-t...
Gene Regulatory Networks Metabolomics Metabolic Networks and Pathways Gene Expression Regulation Machine Learning Algorithms
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Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance.

Nature communications May 11, 2021
Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learnin...
Humans Cell Line, Tumor Gene Expression Regulation, Neoplastic Treatment Outcome Databases, Genetic Machine Learning Neoplasms Transcriptome Atlases as Topic Radiation, Ionizing Neoplasm Proteins Datasets as Topic Metabolic Networks and Pathways Genome, Human Survival Analysis Radiation Tolerance
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Cognitive analysis of metabolomics data for systems biology.

Nature protocols Jan 22, 2021
Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. M...
Natural Language Processing Metabolic Networks and Pathways Workflow Data Analysis Databases, Factual Animals Humans Artificial Intelligence Mass Spectrometry Software Big Data Metabolomics Systems Biology
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A network-based machine-learning framework to identify both functional modules and disease genes.

Human genetics Jan 7, 2021
Disease gene identification is a critical step towards uncovering the molecular mechanisms of diseases and systematically investigating complex disease phenotypes. Despite considerable efforts to develop powerful computing methods, candidate gene ide...
Gastrointestinal Diseases Protein Interaction Mapping Immune System Diseases Musculoskeletal Diseases Metabolic Diseases Terminology as Topic Gene Regulatory Networks Computational Biology Predictive Value of Tests Supervised Machine Learning Amino Acid Sequence Metabolic Networks and Pathways Neurodegenerative Diseases Humans Mental Disorders Neoplasms
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Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.

PloS one Nov 30, 2020
Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been useful for the prediction of gene essentiality. However, currently available ML pipelines perform poorly ...
Metabolic Networks and Pathways Area Under Curve Genetic Diseases, Inborn Support Vector Machine Humans Cluster Analysis Machine Learning Genes, Essential Algorithms
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Pathway information extracted from 25 years of pathway figures.

Genome biology Nov 9, 2020
Thousands of pathway diagrams are published each year as static figures inaccessible to computational queries and analyses. Using a combination of machine learning, optical character recognition, and manual curation, we identified 64,643 pathway figu...
Machine Learning Databases, Factual Humans Literature Computational Biology Metabolic Networks and Pathways Genes
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Metabolic pathway inference using multi-label classification with rich pathway features.

PLoS computational biology Oct 1, 2020
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...
Logistic Models Databases, Genetic Metabolic Networks and Pathways Proteobacteria Software Algorithms Genomics Machine Learning
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Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism.

Nature communications Sep 25, 2020
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...
Machine Learning Biochemical Phenomena Algorithms Metabolic Engineering Phenotype Biosensing Techniques Genotype Amino Acids Tryptophan Metabolic Networks and Pathways Models, Biological Saccharomyces cerevisiae
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Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.

Molecules (Basel, Switzerland) Jul 29, 2020
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...
Humans Protein Binding Animals Fuzzy Logic Energy Metabolism Proteins Metabolic Networks and Pathways Models, Biological
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