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Recent trends & applications of big data science in chronobiology

Journal of Entomology and Zoology Studies · 2020 · Vol. 8(4) · pp. 2244–2250
Harshit KumarManjit PanigrahiKaiho KaisaDivya RajawatK.A. SaravananTriveni DuttBharat Bhushan

Abstract

With the advent of sequencing technologies, now we have observed rapid advancements in biological research. Avenue of big data science steered the development of many new areas of interests with life science researchers. Approaches using big data mining and machine learning (ML) along with other well-established methods of genomics, molecular biology and biotechnology may be implemented with researches in chronobiology. Methodologies demonstrating usage of these techniques with “omics” studies have shown a noteworthy impact on the results of the same. On the other hand, data science unaided will not reject the need for a considerate understanding of the field of research, nor can such approaches substitute the need for researchers and analysts. Hence, so far understanding with this region of investigation is significantly important. It is obvious that the familiarity which has been generated via chronobiology and the applications of various tools resulting from big data science has backed up the acknowledgement of the various patterns and immense biological rhythms reported in organisms. The present text goals to create novel and vital applications in the coming future through chronobiology research orchestrating with big data science.

Metabolomics and Mass Spectrometry StudiesGenetics, Bioinformatics, and Biomedical ResearchBig dataAcknowledgementChronobiologyData scienceBiological dataResponsible Research and InnovationComputer scienceEngineering ethicsBiologyBioinformatics

Funding

  • Indian Council of Agricultural Research
Citations
3
FWCI
0.08
field-weighted impact
References
44
Percentile
45%
vs. same field & year
Citations per year
References
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Recent trends & applications of big data science in chronobiology · Scinovex