Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling
نویسندگان
چکیده
منابع مشابه
Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling
Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of mac...
متن کاملKinetic Modeling of Central Metabolic Pathway for Phenotype MicroArray Analysis
Metabolic networks link cellular phenotypes to the corresponding genotypes. Large-scale structural analysis of metabolic networks is now focusing on the mechanisms underlying robustness in structural networks. Our primary goal is to analyze the mechanisms of metabolic networks using Phenotype Microarray (PM) data. We developed a computational model of central metabolism in Escherichia coli unde...
متن کاملMachine Learning Methods for Microarray Data Analysis
As members of the Dissertation Committee, we certify that we have read the dis-sertation prepared by Prasad Amaresh Gabbur entitled Machine Learning Methods for Microarray Data Analysis and recommend that it be accepted as fulfilling the dissertation requirement for the Degree of Doctor of Philosophy. Final approval and acceptance of this dissertation is contingent upon the candidate's submissi...
متن کاملIn Silico Metabolic Pathway Modeling and Analysis of Mycoplasma pneumoniae
Completion of genome projects gives us a lot of information to deal with and analyze. From the genomic sequence data, cellular information can be obtained. The complexity of cellular processes can be analyzed not only by the individual components but also by the systematic approaches. However in general, these approaches are limited by the lack of kinetic information on the metabolism. The ulti...
متن کاملEfficient Modeling of MS/MS Data for Metabolic Flux Analysis
Metabolic flux analysis (MFA) is a widely used method for quantifying intracellular metabolic fluxes. It works by feeding cells with isotopic labeled nutrients, measuring metabolite isotopic labeling, and computationally interpreting the measured labeling data to estimate flux. Tandem mass-spectrometry (MS/MS) has been shown to be useful for MFA, providing positional isotopic labeling data. Spe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Metabolites
سال: 2018
ISSN: 2218-1989
DOI: 10.3390/metabo8010004