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Bioinformatics, Covid-19

Bioinformatics prospect after pandemic

Bioinformatics is a combination of more than two areas. It includes programming, data that are huge i.e. big data, biology, etc but especially it is a combination of biology and information technology.  Whenever we are talking about data related to the medical field, means the generation of lots of data and the processing of those large data mathematically is known as bioinformatics. There is a huge opportunity in this field, as this field grows more in a situation like Covid. On average every day we are creating 1 terabyte of data through social networking sites. So again, this field includes more research in combination with big data. Experts in bioinformatics deal with analyzing the large sequences of gene data called genomics.  In pharmaceutical, biochemical industries, biogas research plants, biotechnology, etc all these areas deal with genome sequencing. Now a day, gene sequencing is required to extract different features from one type of species to another. If the gene sequence is similar to the other species, then by doing some rearrangements in the sequence, even one species can be converted to other. That’s why this career includes a lot of scope such as industry, education, research and experiments for future investigation in medical. Information is very important aspect for analyzing human behavior. So, analysis of information in genomics field may lead your career towards the bioinformatics scientist, research scientist, microbiologist, agriculture scientist, molecular biologist, wild zoologist etc. Bioinformatics provide universally accessible database, from where several scientists extract the gene sequence data.

There are mainly three basic research areas in bioinformatics: Genetics or genomics, computational biology and system biology. As the name specifies, genetics or genomics mainly deals with the structuring or rearrangement of gene sequence or DNA strand. Whereas the field system biology includes functioning and evolution of molecules, species, tissues, cells, organism etc. by using the statistics and big data in information technology. This field works in the research of different drugs necessary for the evolution of new medicines. The last area i.e. bioinformatics and computational biology include mathematical computation of structuring of any genome sequence. It also includes statistical analysis or simulation of gene matching. 

Apart from the above fields in bioinformatics, some specializations are also available, such as: 

Computational genomics: This is a universal problem-solving specialization, deal with the human gene sequencing or we can say it is a study of analysis of genomic information related to humans. Research here include computational programing may be related to coding or non-coding. It also includes the networking and disease related problem solving to a particular field. If anyone is really interested for working in cancer genomics, then this is the area where one can research on disease causing cancer. There are various faculties working on the field from various countries. This is a diverse stream related to various sub domains also like networking, big data, statistics etc. 

System immunology: It includes the mathematical modelling and various techniques in statistics and development of various methods related to bioinformatics. During Covid, this field actually related to evolution of new vaccine because this field works in the area of immune system. Immune system is a combination of thousands and thousands of cells and connected each other via molecular pathways. Various misfunctioning of human body parts or any sort of allergy or any infection related issues, are probably solved by finding vaccine to that issue. Immune cells are those cells that are the building blocks of the human, if immune system is week, means it can be affected at any point of time. So here those immune cells are extracted from a healthy human being and reinserted or replaced the damaged immune cells of other human body. 

Artificial Intelligence & Machine learning technique: Machine learning technique is an efficient method for improved and better result in any field. When these techniques are applied to bioinformatics, where generation and processing of lots and lots of data are available, can’t be a better option than this. It includes deep learning process for the high-performance computing of rearrangement of data. This method is applied over the simulation field, where filtering and extraction of data from the thousands of long gene sequence. 

DNA – RNA structure analysis:  A, C, T, G are the four nucleotides works as a bases for DNA molecule. Adenine, cytosine, guanine and thymine form a double helix structure bond with hydrogen to form a DNA molecule. Gene is combination of different sequence of nucleotides, that combines together to form a chromosome. Nucleotides are the building blocks of nucleic acid such as hydrogen, carbon and oxygen. Chromosomes are the combination of various gene sequence, comprised together as a packed together to form DNA molecule. These ordered combinations of chromosomes are called genome. There are 4 types of chromosomes: metacentric, sub metacentric, acrocentric and telocentric chromosomes. Metacentric chromosomes have the centromere in the center, where the chromosomes are of equal length. Sub metacentric chromosomes have centromere slightly apart from the center. Here chromosome 4 and 12 are considered as sub metacentric. Acrocentric chromosomes have one strand very long and other is short. In human chromosome 13, 15, 21 and 22 are considered as acrocentric. Last one telocentric have the centromere at the end of the chromosome sequence. Telocentric chromosome is found in mice but not in humans and this becomes the research area where human gene sequence is found to be almost identical with the mice. For solving various diseases in humans, some features from mice are extracted.

So finally, I can say that there is a broad perspective both in research and job field. One can pursue this area to expertise their knowledge confined not only to a particular field but also to a combined interest in artificial intelligence, machine learning, big data, information technology, biology etc. Latest technology machine learning approach improves the research interest of researchers to this field. This are after pandemic have become more approachable and diversity field of research for the evolution of new vaccine or solution to the problems similar found in humans. 

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