Abstract : The NMR data comprises of numerous resonances arising from different metabolites which are building blocks of a cell and are required for its proper functioning. The decoding of information from these cellular metabolites during a pathological condition is an important aspect of NMR based metabonomics. The analysis of data in metabonomics aims primarily in defining the correlation between spectral variables and relationship between groups and secondarily in identifying the significant variations which result in grouping of two groups. Pattern recognition techniques are such tools which play an important role in disease categorization, biomarker identification and verification and for prediction of survival rates for patients of specific disease. Since, metabolites are markers of specific metabolic pathway happening during cell metabolism. The estimation of these metabolites, measuring the degree of deviation and its importance under diseases condition assume a significant part in biomarker validation under clinical settings.
Keywords : TECHNIQUES, PATTERN, METABOLOMICS.
Cite : Srivastava, S., & Roy, R. (2022). Data Mining And Pattern Recognition Techniques For Metabolomics (1st ed., p. 72). Global Research Foundation. https://doi.org/10.52458/9789391842741.2022.eb.grf.asu.ch-16
