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\begin{document}

\title{Identification of Diseases caused by non-Synonymous Single Nucleotide
Polymorphism using Machine Learning Algorithms}



\author[1]{Muhammad Junaid Anjum}%
\author[2]{Fatima Tariq}%
\author[3]{Khadeeja Anjum}%
\author[4]{Hameed ur Rahman}%
\author[5]{Faizan Ahmad}%
\author[6]{Momina Shaheen}%
\affil[1]{COMSATS University Islamabad - Lahore Campus}%
\affil[2]{Lahore College for Women University}%
\affil[3]{CMH Lahore Medical College and Institute of Dentistry}%
\affil[4]{Air University}%
\affil[5]{Cardiff Metropolitan University School of Technologies}%
\affil[6]{University of Roehampton School of Arts}%


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  \date{June 17, 2024}


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\begin{abstract}
The production of vaccines for diseases depends entirely on its
analysis. However, to test every disease extensively is costly as it
would involve the investigation of every known gene related to a
disease. This issue is further elevated when different variations of
diseases are considered. As such the use of different computational
methods are considered to tackle this issue. This research makes use of
different machine learning algorithms in the identification and
prediction of Single Nucleotide Polymorphism. This research presents
that Gradient Boosting algorithm performs better in comparison to other
algorithms in genic variation predictions with an accuracy of 70\%.%
\end{abstract}%



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\textbf{Hosted file}

\verb`Identification of Diseases caused by non-Synonymous Single Nucleotide Polymorphism using Machine Learning Algorithms.docx`  available at \url{https://authorea.com/users/753597/articles/912354-identification-of-diseases-caused-by-non-synonymous-single-nucleotide-polymorphism-using-machine-learning-algorithms}

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