1. Using k-Mer's aggregation analysis and conscience projection to identify LCSS in normal human genomics and malaria-infected genes.
- Author
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Vats, Prashant, Saini, Ashok Kumar, and Upadhyay, Govind Murari
- Subjects
MALARIA ,COMPUTATIONAL biology ,NUCLEOTIDE sequence ,GENOMICS ,HUMAN genome ,GENES - Abstract
Combining biomedical and programming for computer studies, the area of computational biology is a significant field of study. The discovery of individual human Deoxyribose Nucleotide (DNA) polymorphisms that cause illness is one of the most important applications of bio knowledge. Prevalence and fatality rates for Plasmodium malaria are already increasing in India. For early identification and life-saving protection, it is crucial to investigate the collection of occurrences associated with pathogens. It encompasses a variety of methods for diagnosing illnesses. This research proposal intends to investigate the DNA sequence of an infected person and to identify the prevalent patterns subgroups in the uninfected individual and Pathogenic Malaria parasite protozoan organism which leads to malaria in human beings. The British Medical Research Council's library of sequences of nucleotides is where the human genome sequences of genes have been identified. Using the k-Mer dissociation technique, each person's sequence of DNA is separated as a k-mer. The self-organized map of features (SOM) approach is then used to aggregate all segregating k-mers. When clustering k-mers, the average, indicate, and variance of the sample are employed as characteristics. The Long Common Subsequence (LCSS) algorithm is used to find comparable sub-strings of the larger lengths that exist across every one of the k-mers clusters using the acquired k-mers ensembles. The investigation is conducted into the time required to evaluate LCSS in DNA from healthy and unhealthy DNA infected with parasites such as the malaria virus. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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