Call for Papers:Vol.11 Issue.4

Submission
Last date		 28-Aug-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-4. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

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

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

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, http://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: http://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: http://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: http://ijariie.com/AdminUploadPdf/PREDICTING_GENETIC_VARIANTS_PATHOGENECITY_ijariie26481.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Analyzing Member Engagement through Business Intelligence: A Metabase-Driven Dashboard for Registrations, Redemptions, and TransactionsData AnalyticsAnusha S Download
Detection of fake news using Machine Learning techniquesComputer ApplicationsJanani S R Download
MACHINE LEARNING-BASED STRESS DETECTION USING PHYSIOLOGICAL SIGNALS FROM WEARABLE SENSORSComputer Science and EngineeringAkash S K Download
Optimizing Resource Allocation and Task Offloading for Real-Time IoT ApplicationsComputer ApplicationsDhanush M Download
Examining Human-Computer Interaction in Social Media PlatformsComputer ApplicationsTanuja A Download
Interpretable Multimodal Machine Learning for Early Stroke Risk‬ ‭ Prediction in Atrial Fibrillation PatientsComputer Science and EngineeringAnand Hadapad Download
5G and IoT Integration for Smart CitiesComputer EngineeringYathish K J Download
Design and Development of Automated User Responsive Assistant (AURA) or Kinetically Responsive Intelligent Assistant (KRIA) RobotArtificial IntelligenceChandana S Download
Ethical Hacking: Proactive Security Against Cybercrimecomputer engineeringShahapuram Ritika Download
Cyber Security For Wearable Health Devicescomputer Engineering Jenitha H S Download
Artificial Intelligence in Integrated Circuit Design: Revolutionizing Productivity Amidst Practical ChallengesTechnologyKhanh Pham Duy Download
Real-Time Hand Gesture Recognition with Finger Counting (Using OpenCV and Mediapipe)Computer scienceBhumika Sahu Download
Diffie Hellman Key Exchange Algorithm with Man in the middle attack (MITM)Computer Science EngineeringMahesh Purushottam Gajbhiye Download
AN IMPROVED ATTRIBUTE BASED ACCESS CONTROL IN PERSONAL HEALTH RECORDS USING CLOUD WITH CONSTANT CIPHERTEXT LENGTHScience and TechBitrus Isahaka Dzarma Download
Driver Drowsiness Detection System By Measuring EAR and MARComputer Engineering Zoya Fatema Khan Download
12