AI in Bioinformatics

Authors

  • Muhammad Noman Akhtar Bahaudin Zakeria University Multan
  • Gohar Abbas Institute of Southern Punjab
  • Mohsin Ali Khan University of Engineering and Technology Taxila

Keywords:

intelligent bioinformatics system, AI tools in bioinformatics

Abstract

In bioinformatics science and computational molecular biology, artificial intelligence (AI) has rapidly gained interest. With the availability of numerous types of AI algorithms, it has become prevalent for researchers to use off-shelf programmes to identify their datasets and mine them. At present, researchers are facing difficulties in selecting the right approach that could be extended to a given data collection, with numerous intelligent approaches available in the literature. Researchers need instruments that present the data in an intuitive manner, annotated with meaning, precision estimates, and description. In the fields of bioinformatics and computational molecular biology (DNA sequencing), this article seeks to review the use of AI. These fields have evolved from the needs of biologists to use the large volumes of data continuously obtained in genomic science and to better understand them. For several approaches to bioinformatics and DNA sequencing, the fundamental impetus is the evolution of species and the difficulty of dealing with incorrect results. The type of software programmes developed by the scientific community to search, identify and mine numerous usable biological databases are also mentioned in this article, simulating biological experiments with and without mistakes. The review of antibody-antigen interactions and their diversity, and the study of epidemiological evidence that can help forecast antibody-antigen interactions and the induction of broadly neutralising antibodies are important questions to be answered in the field of vaccinology.

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Published

2021-02-27

How to Cite

Akhtar, M. N. ., Abbas, G. ., & Khan, M. A. . (2021). AI in Bioinformatics . International Journal of Sciences: Basic and Applied Research (IJSBAR), 56(1), 301–311. Retrieved from https://www.gssrr.org/index.php/JournalOfBasicAndApplied/article/view/12325

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Articles