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Title: :  PREDICTING GENETIC VARIANTS PATHOGENECITY
PaperId: :  26481
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 3 2025
DUI:    16.0415/IJARIIE-26481
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Syed Arbeena KausarVidya Vikas Institute of Engineering & Technology
Venkatesh IVidya Vikas Institute of Engineering & Technology
Vijay HVidya Vikas Institute of Engineering & Technology
Yamuna PVidya Vikas Institute of Engineering & Technology
Mahesh C RVidya Vikas Institute of Engineering & Technology

Abstract

Computer Engineering
Single Nucleotide Polymorphism (SNP), Phenotypic Traits, Predictive Modeling, Logistic Regression, Parental Origin, Environmental Factors, Mutation Score, Genetic Data Analysis
Single Nucleotide Polymorphism (SNP) detection plays a pivotal role in understanding the intricacies of genetic inheritance and its influence on phenotypic traits. This project focuses on developing a predictive model that analyzes and determines the parental origin of specific SNPs in a child’s DNA. By leveraging genetic data from both parents, we aim to gain deeper insights into hereditary patterns and how they contribute to observable characteristics. To accomplish this, we implemented a logistic regression model that integrates not only genetic information but also lifestyle and environmental factors such as smoking, alcohol consumption, radiation exposure, and mutation scores. These factors were included to examine their potential impact on SNP expression and inheritance. The model was trained and tested on a dataset composed of these variables, resulting in an overall accuracy of 58%, an ROC AUC of 0.604, a recall of 63.27%, and a precision of 56.36%. These metrics suggest the model has moderate predictive capabilities but also emphasize the need for more sophisticated feature selection and machine learning algorithms to enhance performance. In conclusion, this project underlines the multifaceted nature of genetic prediction and the influence of environmental variables on genetic traits. While the logistic regression model provides a foundational approach to SNP inheritance analysis, future work will explore advanced models and deeper biological data integration to improve accuracy and practical applicability in genetic research and personalized medicine.

Citations

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IJARIIE Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. "PREDICTING GENETIC VARIANTS PATHOGENECITY" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 3 2025 Page 445-450
MLA Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. "PREDICTING GENETIC VARIANTS PATHOGENECITY." International Journal Of Advance Research And Innovative Ideas In Education 11.3(2025) : 445-450.
APA Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, & Mahesh C R. (2025). PREDICTING GENETIC VARIANTS PATHOGENECITY. International Journal Of Advance Research And Innovative Ideas In Education, 11(3), 445-450.
Chicago Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. "PREDICTING GENETIC VARIANTS PATHOGENECITY." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 3 (2025) : 445-450.
Oxford Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. 'PREDICTING GENETIC VARIANTS PATHOGENECITY', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 3, 2025, p. 445-450. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/PREDICTING_GENETIC_VARIANTS_PATHOGENECITY_ijariie26481.pdf (Accessed : ).
Harvard Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. (2025) 'PREDICTING GENETIC VARIANTS PATHOGENECITY', International Journal Of Advance Research And Innovative Ideas In Education, 11(3), pp. 445-450IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/PREDICTING_GENETIC_VARIANTS_PATHOGENECITY_ijariie26481.pdf (Accessed : )
IEEE Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R, "PREDICTING GENETIC VARIANTS PATHOGENECITY," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 3, pp. 445-450, May-Jun 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/PREDICTING_GENETIC_VARIANTS_PATHOGENECITY_ijariie26481.pdf [Accessed : ].
Turabian Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. "PREDICTING GENETIC VARIANTS PATHOGENECITY." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 3 ().
Vancouver Syed Arbeena Kausar, Venkatesh I, Vijay H, Yamuna P, and Mahesh C R. PREDICTING GENETIC VARIANTS PATHOGENECITY. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(3) : 445-450. Available from: https://ijariie.com/AdminUploadPdf/PREDICTING_GENETIC_VARIANTS_PATHOGENECITY_ijariie26481.pdf
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