AIMC Topic: Escherichia coli

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Establishing the validity of different susceptibility testing methods to evaluate the in vitro activity of amoxicillin-clavulanate against Escherichia coli.

Diagnostic microbiology and infectious disease
Amoxicillin-clavulanate MICs of 160 Escherichia coli isolates with characterized resistance mechanisms were obtained by 2 MIC gradient strip brands, 3 automated systems, and reference ISO microdilution method using EUCAST (fixed 2μg/mL clavulanate) a...

Semi-Supervised Multi-View Learning for Gene Network Reconstruction.

PloS one
The task of gene regulatory network reconstruction from high-throughput data is receiving increasing attention in recent years. As a consequence, many inference methods for solving this task have been proposed in the literature. It has been recently ...

Prediction of recombinant protein overexpression in Escherichia coli using a machine learning based model (RPOLP).

Computers in biology and medicine
Recombinant protein overexpression, an important biotechnological process, is ruled by complex biological rules which are mostly unknown, is in need of an intelligent algorithm so as to avoid resource-intensive lab-based trial and error experiments i...

The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed-batch fermentations.

Biotechnology journal
Product quality assurance strategies in production of biopharmaceuticals currently undergo a transformation from empirical "quality by testing" to rational, knowledge-based "quality by design" approaches. The major challenges in this context are the ...

SPECTRUS: A Dimensionality Reduction Approach for Identifying Dynamical Domains in Protein Complexes from Limited Structural Datasets.

Structure (London, England : 1993)
Identifying dynamical, quasi-rigid domains in proteins provides a powerful means for characterizing functionally oriented structural changes via a parsimonious set of degrees of freedom. In fact, the relative displacements of few dynamical domains us...

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
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...

Assessing the effects of data selection and representation on the development of reliable E. coli sigma 70 promoter region predictors.

PloS one
As the number of sequenced bacterial genomes increases, the need for rapid and reliable tools for the annotation of functional elements (e.g., transcriptional regulatory elements) becomes more desirable. Promoters are the key regulatory elements, whi...

Analysis of strand-specific RNA-seq data using machine learning reveals the structures of transcription units in Clostridium thermocellum.

Nucleic acids research
Identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-...

Computationally predicting protein-RNA interactions using only positive and unlabeled examples.

Journal of bioinformatics and computational biology
Protein-RNA interactions (PRIs) are considerably important in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulations of gene expression to the active defense of host against virus. With the development...

EcoliNet: a database of cofunctional gene network for Escherichia coli.

Database : the journal of biological databases and curation
During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellular processes have been discovered through research on this bacterium. Although much basic research n...