AIMC Topic: Escherichia coli Proteins

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Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging.

PloS one Mar 2, 2016
The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields ...
Codon Escherichia coli Gene Expression Escherichia coli Proteins Base Sequence Least-Squares Analysis Proteomics Models, Genetic Support Vector Machine
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All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences.

Proceedings of the National Academy of Sciences of the United States of America Apr 9, 2015
Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-hel...
Artificial Intelligence Escherichia coli Models, Molecular Protein Structure, Tertiary Sequence Analysis, Protein Receptors, Cell Surface Escherichia coli Proteins Protein Structure, Secondary
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Decoding the role of the arginine dihydrolase pathway in shaping human gut community assembly and health-relevant metabolites.

Cell systems May 21, 2025
The arginine dihydrolase pathway (arc operon) provides a metabolic niche by transforming arginine into metabolic byproducts. We investigate the role of the arc operon in probiotic Escherichia coli Nissle 1917 on human gut community assembly and healt...
Arginine Operon Animals Humans Machine Learning Metabolic Networks and Pathways Gastrointestinal Microbiome Escherichia coli Hydrogen-Ion Concentration Escherichia coli Proteins Mice
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A multi-scale expression and regulation knowledge base for Escherichia coli.

Nucleic acids research Oct 27, 2023
Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from this data are critical. Here, we assembled a top-down expression and regulation knowledge base for Escherichia coli. The expression component is a 1035-...
Gene Expression Profiling Knowledge Bases Escherichia coli Proteins Transcriptome Gene Expression Regulation, Bacterial Escherichia coli
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Deep representation learning improves prediction of LacI-mediated transcriptional repression.

Proceedings of the National Academy of Sciences of the United States of America Jul 6, 2021
Recent progress in DNA synthesis and sequencing technology has enabled systematic studies of protein function at a massive scale. We explore a deep mutational scanning study that measured the transcriptional repression function of 43,669 variants of ...
Epistasis, Genetic Lac Repressors Escherichia coli Proteins Transcription, Genetic Reproducibility of Results Mutation Protein Domains Deep Learning
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Pathogenic potential assessment of the Shiga toxin-producing by a source attribution-considered machine learning model.

Proceedings of the National Academy of Sciences of the United States of America May 18, 2021
Instead of conventional serotyping and virulence gene combination methods, methods have been developed to evaluate the pathogenic potential of newly emerging pathogens. Among them, the machine learning (ML)-based method using whole-genome sequencing ...
Reproducibility of Results ROC Curve Support Vector Machine Humans Machine Learning Shiga Toxin 2 Virulence Escherichia coli Infections Shiga-Toxigenic Escherichia coli Whole Genome Sequencing Escherichia coli Proteins
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iML1515, a knowledgebase that computes Escherichia coli traits.

Nature biotechnology Oct 11, 2017
Knowledge Bases Escherichia coli Proteins Database Management Systems Escherichia coli
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Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

Journal of biosciences Oct 1, 2015
Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown tha...
Databases, Protein Area Under Curve Escherichia coli Proteins Protein Interaction Mapping Gene Expression Humans Support Vector Machine Escherichia coli Sensitivity and Specificity Protein Interaction Domains and Motifs Fuzzy Logic
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Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

Journal of biosciences Oct 1, 2015
Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low predicti...
Gene Expression Regulation, Fungal Saccharomyces cerevisiae Proteins Escherichia coli Computational Biology Datasets as Topic Saccharomyces cerevisiae Escherichia coli Proteins Gene Regulatory Networks Transcription Factors Support Vector Machine Gene Expression Regulation, Bacterial
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