Browsing by Author "USAMA SIDDIQUE"

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    Classifiction of antibiotic resistance genes using position relative statistical moments through machine learning techniques
    (UMT Lahore, 2022) USAMA SIDDIQUE
    Antibiotics bacterial resistant genes can be produced through microorganisms and feature the ability to inhibit the boom of different microorganisms that extra often cause illness. Such resistant genes are very challenging in today era because it creates a barrier to modern antibiotics; therefore it reduces the ability of treatment from bacterial infections. They may cause dangerous effects by transferring between human, bacteria and surrounding environment. Classification of resistant gene is very important and crucial task. Previously several methods are proposed to predict antibiotic resistant bacterial gene However, they were an expensive and time-consuming process. As a result, proposed a classifier that predicts ARG’s by calculating different features and position relative statistical moments. Our classifier computes statistical instants and position based on structures of the resistant genes by using Chou’s 5-step rules, XGBoost is there used as a classifier for the accurateness of this model to identify the best results. The process was authenticated by using the Self-consistency, independence, K-Fold test and Jackknife test giving 99.15%, 99.75%, 99.15%, and 99.5% precise outcomes respectively. These outcomes describe that the recommended classifier can play a vital part in the estimate of antibiotic resistance genes