Engineering of increased L-Threonine production in bacteria by combinatorial cloning and machine learning.

The goal of this study is to develop a general strategy for bacterial engineering using an integrated synthetic biology and machine learning (ML) approach. This strategy was developed in the context of increasing L-threonine production in ATCC 21277. A set of 16 genes was initially selected based on metabolic pathway relevance to threonine biosynthesis and used for combinatorial cloning to construct a set of 385 strains to generate training data (i.

Learning curves for drug response prediction in cancer cell lines.

Background: Motivated by the size and availability of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. As drug sensitivity studies continue generating drug response data, a common question is whether the generalization performance of existing prediction models can be further improved with more training data.

Methods: We utilize empirical learning curves for evaluating and comparing the data scaling properties of two neural networks (NNs) and two gradient boosting decision tree (GBDT) models trained on four cell line drug screening datasets.

Essential genes on metabolic maps.

Within the past five years genome-scale gene essentiality data sets have been published for ten diverse bacterial species. These data are a rich source of information about cellular networks that we are only beginning to explore. The analysis of these data, very heterogeneous in nature, is a challenging task.

The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes.

The release of the 1000th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome.

Comparative genome analysis of Bacillus cereus group genomes with Bacillus subtilis.

Genome features of the Bacillus cereus group genomes (representative strains of Bacillus cereus, Bacillus anthracis and Bacillus thuringiensis sub spp. israelensis) were analyzed and compared with the Bacillus subtilis genome. A core set of 1381 protein families among the four Bacillus genomes, with an additional set of 933 families common to the B.

Complete sequence and comparative genome analysis of the dairy bacterium Streptococcus thermophilus.

The lactic acid bacterium Streptococcus thermophilus is widely used for the manufacture of yogurt and cheese. This dairy species of major economic importance is phylogenetically close to pathogenic streptococci, raising the possibility that it has a potential for virulence. Here we report the genome sequences of two yogurt strains of S.

Genome sequence of Bacillus cereus and comparative analysis with Bacillus anthracis.

Bacillus cereus is an opportunistic pathogen causing food poisoning manifested by diarrhoeal or emetic syndromes. It is closely related to the animal and human pathogen Bacillus anthracis and the insect pathogen Bacillus thuringiensis, the former being used as a biological weapon and the latter as a pesticide. B.

The ERGO genome analysis and discovery system.

The ERGO (http://ergo.integratedgenomics.com/ERGO/) genome analysis and discovery suite is an integration of biological data from genomics, biochemistry, high-throughput expression profiling, genetics and peer-reviewed journals to achieve a comprehensive analysis of genes and genomes.

From genetic footprinting to antimicrobial drug targets: examples in cofactor biosynthetic pathways.

Novel drug targets are required in order to design new defenses against antibiotic-resistant pathogens. Comparative genomics provides new opportunities for finding optimal targets among previously unexplored cellular functions, based on an understanding of related biological processes in bacterial pathogens and their hosts. We describe an integrated approach to identification and prioritization of broad-spectrum drug targets.

Genome sequence and analysis of the oral bacterium Fusobacterium nucleatum strain ATCC 25586.

We present a complete DNA sequence and metabolic analysis of the dominant oral bacterium Fusobacterium nucleatum. Although not considered a major dental pathogen on its own, this anaerobe facilitates the aggregation and establishment of several other species including the dental pathogens Porphyromonas gingivalis and Bacteroides forsythus. The F.