A New Hybrid Model to find The Dominant Pattern of Amino Acid Sequence to using Data mining

  • Unique Paper ID: 144398
  • PageNo: 6-14
  • Abstract:
  • Data Mining is the process of extracting or mining the patterns from very large amount of biological datasets. Utilization of Data mining algorithms can reveal biological relevant associations between different genes and gene expression. In Data Mining, several techniques are available for predicting frequent patterns. One among the technique is association rule mining algorithm; which can be applied for solving the crucial problems faced in the field of biological science. From the literature, various algorithms have been employed in generating frequent patterns for distinct application. These algorithms have some limitations in predicting frequent patterns, such as space, time complexity and accuracy. We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Bioinformatics is an interdisciplinary research area that is the interface between the biological and computational sciences. Bioinformatics deals with algorithms, databases and information systems, web technologies, artificial intelligence and information and computation theory, structural biology, software engineering, data mining, image processing, modeling and simulation, discrete mathematics, control and system theory, circuit theory, and statistics.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{144398,
        author = {Dimpal Prajapati and Prof. Riya Parmar},
        title = {A New Hybrid Model to find The Dominant Pattern of Amino Acid Sequence to using Data mining},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {11},
        pages = {6-14},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144398},
        abstract = {Data Mining is the process of extracting or mining the patterns from very large amount of biological datasets. Utilization of Data mining algorithms can reveal biological relevant associations between different genes and gene expression. In Data Mining, several techniques are available for predicting frequent patterns. One among the technique is association rule mining algorithm; which can be applied for solving the crucial problems faced in the field of biological science. From the literature, various algorithms have been employed in generating frequent patterns for distinct application. These algorithms have some limitations in predicting frequent patterns, such as space, time complexity and accuracy. We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Bioinformatics is an interdisciplinary research area that is the interface between the biological and computational sciences. Bioinformatics deals with algorithms, databases and information systems, web technologies, artificial intelligence and information and computation theory, structural biology, software engineering, data mining, image processing, modeling and simulation, discrete mathematics, control and system theory, circuit theory, and statistics.},
        keywords = {Data mining, Bioinformatics, Partition Method, Apriori, Genetic Algorithm},
        month = {},
        }

Cite This Article

Prajapati, D., & Parmar, P. R. (). A New Hybrid Model to find The Dominant Pattern of Amino Acid Sequence to using Data mining. International Journal of Innovative Research in Technology (IJIRT), 3(11), 6–14.

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