Digital genomics to build a smart franchise in real time applications

Muneshwara, M S; Swetha, M.; Thungamani, M.; Anil, G. N.

doi:10.1109/iccpct.2017.8074247

Cited by 10 publications

(1 citation statement)

References 3 publications

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“…The rationale behind the discussion question is to review and discuss those contributions existing within the resulting papers of the systematic mapping process ( Table 5). One distinctive attempt to display an opinion research based on well-known approaches in feature selection applied to digital genetics in order to enhance machine intelligence is found on [17] by Muneshwara et al In their paper, Muneshwara et al do not focus on a single type of feature selection method, paradoxically, however, the rest of the contributions display diverse solutions that can be categorized according to the six types of feature selection methods.…”

Section: Mapping Results and Discussionmentioning

confidence: 99%

Feature selection methods and genomic big data: a systematic review

et al. 2019

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With the advance of computational techniques, the amount of genomic data has risen exponentially, with a rapid rate [1] making it hard to utilize such data in the medical field without appropriate pre-processing, which in turn leads to more complexity and veracity issues [2] eventually creating multiple complications such as storage, analysis, privacy and security. Therefore, genomic data may look easy to handle in terms of its volume, but it actually requires quite a complicated process due to the complexity, heterogeneity and hybridity of its features. This process is entitled knowledge discovery process [3]: • Data recording Includes the different challenges and tools regarding the capture and storage of data. • Data pre-processing Which includes all the operations of cleaning and appropriation of the captured data to the ready to analyze form in order to optimize the analysis step. • Data analysis The task of evaluating data using different algorithms following a logical reasoning to examine each component of the data provided, with the aim of dispensing insightful outcomes.

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Section: Mapping Results and Discussionmentioning

confidence: 99%