AIMC Topic: Genomic Library

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Patchy promiscuity: machine learning applied to predict the host specificity of and .

Microbial genomics Oct 3, 2017
and are bacterial species that colonize different animal hosts with sub-types that can cause life-threatening infections in humans. Source attribution of zoonoses is an important goal for infection control as is identification of isolates in reserv...
Genomic Library Host Specificity Salmonella enterica Zoonoses Machine Learning Animals Phylogeny Escherichia coli Humans
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Model-enabled gene search (MEGS) allows fast and direct discovery of enzymatic and transport gene functions in the marine bacterium .

The Journal of biological chemistry Apr 26, 2017
Whereas genomes can be rapidly sequenced, the functions of many genes are incompletely or erroneously annotated because of a lack of experimental evidence or prior functional knowledge in sequence databases. To address this weakness, we describe here...
Genetic Complementation Test Bacterial Proteins Genomic Library Aquatic Organisms High-Throughput Nucleotide Sequencing Decapodiformes Escherichia coli Aquaculture Models, Genetic Molecular Sequence Annotation Computer Simulation Gene Deletion Pacific Ocean Open Reading Frames Species Specificity Genomics Reproducibility of Results Expert Systems Aliivibrio fischeri Recombinant Proteins Animals Hawaii
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High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

PloS one Mar 20, 2017
Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in human...
Robotics Hot Temperature Saccharomyces cerevisiae Gene Knockout Techniques Time Factors Culture Media Automation, Laboratory Transformation, Genetic Canavanine Genomic Library
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Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network.

Medicine May 1, 2019
The aim of this study was to investigate the clinical factors affecting the survival prognosis of lung adenocarcinoma, and to establish a predictive model of survival prognosis of lung adenocarcinoma by artificial neural network.Download the cancer g...
Prognosis Female Humans Neural Networks, Computer Predictive Value of Tests Neoplasm Staging Logistic Models Regression Analysis Adenocarcinoma of Lung Genomic Library Cigarette Smoking Kaplan-Meier Estimate Aged, 80 and over Male Adult Middle Aged Risk Factors ROC Curve Aged Lung Neoplasms
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