Prediction of binding peptides to class I Major Histocompatibility Complex using modified scoring matrices and data splitting strategies

• Autorzy: Salem D. A. , Seoud R. A. A. , Kadah Y. M.

Identyfikatory

DOI

10.1016/j.bbe.2016.04.003

• Języki publikacji: EN

Abstrakty

EN

Predicting peptides that can bind to MHC class I molecules is an important step in the vaccine design process. Computational approaches have potential to provide good predictive models that save both time and cost of the process. Position Specific Scoring Matrix (PSSM) is a reliable approach when dealing with amino acid sequences. PSSM formation involves carefully selecting its constructing data and parameters. In this work, we apply three different data splitting strategies and propose alternative values for the embedded PSSM parameters. The basic principle of data splitting is to choose train data that is able to represent the whole data. We propose using the Kennard–Stone algorithm to highlight the importance of choosing the data constituting the PSSM. Furthermore, this work proposes modifications to PSSM parameters and studies the model behavior in response to each change. The model is applied to experimental data for the Major Histocompatibility Complex of class I. Performance of modified parameters show either comparable or better results to conventional parameters. Moreover, Kennard–Stone data splitting algorithm contributed to significant model performance enhancement.

Słowa kluczowe

EN

data splitting; epitope prediction; Major Histocompatibility Complex; position specific scoring matrix; vaccine design

PL

dzielenie danych; główny układ zgodności tkankowej; szczepionka

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2016
• Tom: Vol. 36, no. 3
• Strony: 509--520
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wykr.

Twórcy

autor

Salem D. A.

• Computer Department, Faculty of Engineering, Misr University for Science and Technology, Giza, Egypt

autor

Seoud R. A. A.

• Department of Electronics and Communication, Faculty of Engineering, Fayoum University, Fayoum, Egypt

autor

Kadah Y. M.

• Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.