The reconstruction and analysis of genome-scale metabolic models constitutes a powerful
systems biology approach, with applications ranging from basic understanding of genotype …

Essential genes are critical for the growth and survival of any organism. The machine
learning approach complements the experimental methods to minimize the resources …

Resolving the spatial distribution of the transcriptome at a subcellular level can increase our
understanding of biology and diseases. To facilitate studies of biological functions and …

Background AP2/ERF transcription factors are important in a variety of biological activities,
including plant growth, development, and responses to biotic and abiotic stressors …

Although knowing where a protein functions in a cell is important to characterize biological
processes, this information remains unavailable for most known proteins. Machine learning …

Protein subcellular localization prediction is of great significance in bioinformatics and
biological research. Most of the proteins do not have experimentally determined localization …

Automated function prediction (AFP) of proteins is of great significance in biology. AFP can
be regarded as a problem of the large-scale multi-label classification where a protein can be …

Yeasts have been widely used for production of bread, beer and wine, as well as for
production of bioethanol, but they have also been designed as cell factories to produce …

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective
endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine …

The endoplasmic reticulum (ER) coordinates mRNA translation and processing of secreted
and endomembrane proteins. ER-associated degradation (ERAD) prevents the …