Unsupervised Learning for Gene Selection and Enrichment

Individual independent analysis results in Genetic aetiology of complex trait unexplained, which results in limited understanding of complex traits. Combined Multiple data Analysis results in compensate for missing /unreliable information, reduced rate of getting false positive and identify genetic variation in complex traits. Data Integration is the process by which different types of omic data are combined as predictor variable, which results in more through and comprehensive modeling of complex traits or phenotypes.

Autorentext

Tripti Swarnkar is currently an Associate Professor of Computer Application at the ITER, Siksha O Anusandhan University, Bhubaneswar, India. her PhD. degree from Indian Institute of Technology, Kharagpur, India, in August 2015. Currently, her research interest includes Machine Learning, Data Mining and Computational Biology.