Bioinformatics and Data Sciences


EOI: 10.11242/viva-tech.01.05.201

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Citation

Shelo Chakkalakkal, Sonali Mishra, "Bioinformatics and Data Sciences", VIVA-IJRI Volume 1, Issue 5, Article 201, pp. 1-5, 2022. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Bioinformatics is an interdisciplinary science of analysing and interpreting biological data by application of statistics, computational methodologies, and information technology. Due to the large amount of genome, proteomics, and other data generated, the analysis and interpretation of such biological datasets requires the use of data science and data mining tools.. Hence, researchers are required to rely on data-science tools to store and analyse the data. Data science is an interdisciplinary science that uses algorithms and scientific methods to derive information and insights from big data. The strategies promote investigation and advancement of innovative methods to improve the incorporation of big data and data science into biological research. Advances in data science and computers provide viable analytical techniques for processing huge biological data.

Keywords

Bioinformatics, computer biotechnology, data science, data visualization, GenBank.

References

  1. [1] Zaki , J.; Wang , T.L. and Toivonen, T.T. (2001). BIOKDD01: Workshop on Data Mining in Bioinformatics”.
  2. [2] Li, J.; Wong, L. and Yang, Q. (2005 ). Data Mining in Bioinformatics, IEEE Intelligent System, IEEE Computer Society
  3. [3] Joannefox (2006). “What Is Bioinformatics?”. The Science Creative Quarterly. Retrieved from: Https://Www.Scq.Ubc.Ca/What-Is-Bioinformatics/
  4. [4] P. Bickerton [2018]. “What is bioinformatics?”. Retrieved from: http://www.earlham.ac.uk/articles/whatis-bioinformatics
  5. [5] N.M. Luscombe, D. Greenbaum, & M. Gerstein (2001). “What is bioinformatics? An introduction and overview”. Retrieved from: https://www.researchgate.net/publication/2330725_Wh at_is_bioinformatics_An_introduction_and_overview
  6. [6] B. R. Schneider (n.d.). "Bioogical Weapon". Retrievd from: https://www.britannica.com/technology/biologicalweapon
  7. [7] http://sbc.ucdavis.edu/Biotech_for_Sustain_pages/Inse ct_resistance/
  8. [8] Arboleya S., Bottacini F., O’Connell-Motherway M., Ryan C., Ross R., Van Sinderen D., et al. (2018). Gene-trait matching across the Bifidobacterium longum pan-genome reveals considerable diversity in carbohydrate catabolism among human infant strains. BMC Genomics 19 (1), 33.
  9. [9] Qu K., Guo F., Liu X., Lin Y., Zou Q. (2019). Application of Machine Learning in Microbiology. Front. Microbiol. 10, 827. 10.3389/fmicb.2019.00827 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  10. [10] Mount, D. W. (2002). Bioinformatics: Sequence and Genome Analysis Spring Harbor Press
  11. [11] Jiong, Lei Liu; Yang, A. and Tung, K. H. Data Mining Techniques for Microarray, Proceedings of the 21st International Conference on Data Engineering (ICDE 2005).
  12. [12] Robert C, Casella G. A short history of Markov chain Monte Carlo: subjective recollections from incomplete data. Stat Sci. 2011;26:102–15.