Background: Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification...
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
Background: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. Result...
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Background: Whole genome sequence data is a step towards generating the 'parts list' of life to understand the underlying principles of Biocomplexity. Genome sequencing ...
Urmila Kulkarni-Kale, Shriram Bhosle, G. Sunitha M...