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Journals / Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi / 2012 / Cilt: 28 - Sayı: 1

Proteomic analysis of HIV-1 protease specificity with a new feature encoding method

HIV-1 Proteaz Özgünlüğünün Yeni Bir Öznitelik Temsili Yöntemi ile Proteomik Analizi

Murat GÖK
Ahmet Turan ÖZCERİT
Pages
23–28
Publication Date
2012-02-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to empirical results, FTKY has been performed better prediction of accuracy 95.21 % on PR-1625 according to best 10-pc and accuracy 94.37 % when using PR-3261 according to best 30-pc on a standalone classifier.

📌 3 Key Takeaways

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Objective & Hypothesis:In this study a new feature encoding scheme named FTKY (Physicochemical Based Encoding Method) has been developed for HIV-1 protease site prediction.
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Key Findings & Data:FTKY has been tested according to selected best 10-pc(physicochemical), 20-pc, 30-pc, 40-pc and 50-pc by means of accuracy, specificity and AUROC (Area Under Receiver Operating Charecteristic Curve) on Linear Support Vector Machines.
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Conclusion & Impact:According to empirical results, FTKY has been performed better prediction of accuracy 95.21 % on PR-1625 according to best 10-pc and accuracy 94.37 % when using PR-3261 according to best 30-pc on a standalone classifier.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:HIV-1 Proteaz Özgünlüğü · Öznitelik Temsili · Peptit Sınıflandırma

Abstract

In this study a new feature encoding scheme named FTKY (Physicochemical Based Encoding Method) has been developed for HIV-1 protease site prediction. FTKY has been tested according to selected best 10-pc(physicochemical), 20-pc, 30-pc, 40-pc and 50-pc by means of accuracy, specificity and AUROC (Area Under Receiver Operating Charecteristic Curve) on Linear Support Vector Machines. Tests have been conducted on two up-to-date HIV-1 protease datasets, PR-1625 and PR-3265. According to empirical results, FTKY has been performed better prediction of accuracy 95.21 % on PR-1625 according to best 10-pc and accuracy 94.37 % when using PR-3261 according to best 30-pc on a standalone classifier.

Özet

Bu çalışmada HIV-1 proteaz enzimi bölünme kısımlarının tahmini için Fizikokimyasal Tabanlı Kodlama Yöntemi (FTKY) adı verilen yeni bir öznitelik kodlama yöntemi uygulandı. FTKY, seçilen en iyi 10-fk (fizikokimyasal), 20-fk, 30-fk, 40-fk ve 50-fk özelliğe göre sınıf doğruluğu, duyarlık ve Alıcı İşletim Karakteristiği Eğrisi Altında Kalan Alan (AİKAA) değerleri bakımından Doğrusal Destek Vektör Makineleri (DDVM) yöntemi kullanılarak test edilmiştir. Testlerde güncel iki HIV-1 proteaz veri seti, PR-1625 ve PR-3261 kullanılmıştır. Elde edilen deneysel sonuçlara göre 10-fk’ya göre yapılan kodlamalarda, PR-1625 veri seti üzerinde en yüksek performans elde edilirken PR-3261’de ise en düşük performans elde edilmiştir. Elde edilen deneysel sonuçlara göre FTKY, tek sınıflandırıcı üzerinde PR-1625 üzerinde en yüksek sınıf doğruluğunu % 95,21 ile en iyi 10-fk, PR-3261 üzerinde ise % 94,37 sınıf doğruluğu ile en iyi 30-fk vermiştir.

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Cite This Article

GÖK, M., ÖZCERİT, A. T. (2012). Proteomic analysis of HIV-1 protease specificity with a new feature encoding method. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, Cilt: 28 - Sayı: 1, 23–28. https://ajindex.com/articles/253482

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