Genomic Data Science And COVID -19 Genome Analysis Using Bio Python

Abstract

The last few years have been amazing for biology and healthcare and the best thing that happens in this field was the human genome project .it was an international research project with the goal of mapping and understanding the entire human genome .data science is the field in which we study data, understand the data to get valuable insight from that. Data science has already become an umbrella under which every industry and field comes. We can work in medical, marketing, Information technology, and every other field, even far before data science comes into the real world, we were using statistical and computational knowledge to get an outcome from our data. But today with the grace of the internet and social media our ability to decipher the information from that data is out of our range, where data science has come as a saviour. Because of the amount of genomic data being generated it become essential that the field of genomics or biology must be combined with modern technology and tools so that we can properly analyze such big data for precise and accurate prediction of disease and prevention mechanisms for that, which ultimately will result in improved human health. The data collected from a single week-long sequence today can create more data than whole genome research done a few years ago. “Bioinformatics”, “computational genomics” and “genomic data science” are all very similar fields. To provide biological insights in these disciplines, we must be able to process and analyse huge genomics datasets, as well as validate the processed data's quality and transform it. Afterwards, depending on the nature of our issue, we must apply statistical or machine-learning models. The most likely scenario is to first perform some dimension reduction and clustering, then visualisation. In this paper, I will use python to pass my accountancies over genomic data science and genomic data analysis.