Framework for Parallel Preprocessing of Microarray Data Using Hadoop.

ABSTRACT: Nowadays, microarray technology has become one of the popular ways to study gene expression and diagnosis of disease. National Center for Biology Information (NCBI) hosts public databases containing large volumes of biological data required to be preprocessed, since they carry high levels of noise and bias. Robust Multiarray Average (RMA) is one of the standard and popular methods that is utilized to preprocess the data and remove the noises. Most of the preprocessing algorithms are time-consuming and not able to handle a large number of datasets with thousands of experiments. Parallel processing can be used to address the above-mentioned issues. Hadoop is a well-known and ideal distributed file system framework that provides a parallel environment to run the experiment. In this research,

SUBMITTER: Sahlabadi A 

PROVIDER: S-EPMC5896349 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature