Identification of Better Gene Expression Data for Mosquito Species Classification Using Radial Basis Function Network Methodology

Q3 Computer Science

Open Bioinformatics Journal Pub Date : 2018-04-30 DOI:10.2174/1875036201811010038

J. Eswari, C. Venkateswarlu

引用次数: 1

Abstract

Investigation in bioinformatics has developed promptly in latest years owing to improvements in sequence excavating techniques. Gene sequences in DNA are supplemented with great extent of information, but the intricacy and complexity of this information causes difficulty in analyzing it by using standard classical methods of classification. In this work, a Radial Basis Function Network (RBFN) methodology with self-network arrangement is presented for identification of mosquito species based on the genetic design content of ITS2 ribosomal DNA sequences.

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基于径向基函数网络方法的蚊虫物种分类基因表达数据筛选

近年来，由于序列挖掘技术的进步，生物信息学研究迅速发展。DNA中的基因序列补充了大量的信息，但这些信息的复杂性和复杂性导致难以使用标准的经典分类方法进行分析。本文基于ITS2核糖体DNA序列的遗传设计内容，提出了一种自网络排列的径向基函数网络（RBFN）方法来识别蚊子物种。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Open Bioinformatics Journal Computer Science-Computer Science (miscellaneous)

CiteScore

2.40

自引率

0.00%

发文量

期刊介绍： The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.