In the coming years, the integration of the study of data science in the field of biotechnology will have a great impact on present environmental issues, healthcare sectors, and ecological imbalances.
Today, the biotech industry is gaining popularity and it has massive data structures, rich data sources, and efficient storage forms. Companies in various industries have succeeded in solving some serious issues and as a result created profitable gains because of the awareness about the importance of big data and the use of data science techniques. The biotechnology domain does not just consist of big data in terms of DNA information, but it is a rich data source to identify and understand various emerging social, economic, environmental and healthcare problems. The genetic data of plants, animals and humans is stored in the data banks as to preserve individual identity. Researchers use this massive gene data for research purposes related to various genetic disorders or to analyse and extract meaningful patterns of each gene expression. Researchers tag the certain gene sequence with specific names so that they can track and identify similar bacterial gene sequences from any new gene data. When combined with the genetic information or composition of each person’s lifestyle, health and medicines they take, then it is easy to predict the new person’s health issues and which medicines can be effective based on billions of gene records collected and analysed. Thus, supervised and unsupervised learning algorithms can be applied to understand each individual’s gene data, its relations, similarities and differences when compared with other individual’s gene sequence. By applying data science methodologies to the human genome, we can predict the diseases which are prone to happen. We can solve the mystery – why do some human beings get affected with certain diseases at certain ages? Also we could know – how did they got that infection? When is it likely that they will suffer from a certain type of disease? Which enzymes can cure certain diseases? By analyzing many individual data points we are able to track and control the behavior of each gene sequence during data synthesis and data sequencing, which is useful in order to retrieve any target enzymes. In the human body there are more than 10,000 microbes; with several data science techniques we can predict which microbes might be useful for an individual’s health and a great life.
Personalized healthcare and medication is possible simply with the aids of data science and artificial intelligence. The DNA synthesis work will likely gain high revenues and its operational work will become cheaper than it ever was. Analyzing relationships within various forms of big genetic data sets can achieve new insightful knowledge, solutions to critical problems, and decision making power.
Thus, we will be able to store the world’s digital data about several genes and data storage problems will soon be history. Thus, we can achieve faster computational work in the biotech field. Researchers will focus mainly on optimizing parameters, which can provide the best solution rather than having, for example, an intense focus on just DNA analysis.
Each gene expresses a different function in a living cell. Advances in computational studies will help clarify interactions between foreign and human genes within the body, as well as help to disclose ecological and environmental concerns. Data science and artificial intelligence applications will disrupt the biotechnology industry.