Prediction of high-risk types of human papillomaviruses using statistical model of protein ``sequence space

DOI10.1155/2015/756345zbMath1344.92081OpenAlexW2026789136WikidataQ35564165 ScholiaQ35564165MaRDI QIDQ308843

Nanfang Liu, Yabing Hai, Qi Dai, Yuhua Yao, Cong Wang, Xiaoqing Liu, Ping-an He

Publication date: 6 September 2016

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/756345

zbMATH Keywords

cervical cancerhuman papillomavirusesmutation matrices

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) Medical applications (general) (92C50)

Cites Work

• Normalized Lempel-Ziv complexity and its application in bio-sequence analysis
• Database and expert systems applications. 14th international conference, DEXA 2003, Prague, Czech Republic, September 1--5, 2003. Proceedings
• Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
• Invariants of DNA sequences based on 2DD-curves
• Statistical Measures of DNA Sequence Dissimilarity under Markov Chain Models of Base Composition
• A measure of the similarity of sets of sequences not requiring sequence alignment.
• A Measure of DNA Sequence Dissimilarity Based on Mahalanobis Distance between Frequencies of Words

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