A Comparative Study of Gene Co-Expression Thresholding Algorithms.

IF 1.4 4区生物学 Q4 BIOCHEMICAL RESEARCH METHODS

Journal of Computational Biology Pub Date : 2024-06-01 Epub Date: 2024-05-23 DOI:10.1089/cmb.2024.0509

Carissa Bleker, Stephen K Grady, Michael A Langston

引用次数: 0

Abstract

The thresholding problem is studied in the context of graph theoretical analysis of gene co-expression data. A number of thresholding methodologies are described, implemented, and tested over a large collection of graphs derived from real high-throughput biological data. Comparative results are presented and discussed.

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基因共表达阈值算法比较研究

在对基因共表达数据进行图论分析的背景下研究了阈值问题。介绍、实施并测试了从真实高通量生物数据中提取的大量图谱中的一些阈值计算方法。比较结果将被展示和讨论。

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

Journal of Computational Biology 生物-计算机：跨学科应用

CiteScore

3.60

自引率

5.90%

发文量

113

审稿时长

6-12 weeks

期刊介绍： Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics. Journal of Computational Biology coverage includes: -Genomics -Mathematical modeling and simulation -Distributed and parallel biological computing -Designing biological databases -Pattern matching and pattern detection -Linking disparate databases and data -New tools for computational biology -Relational and object-oriented database technology for bioinformatics -Biological expert system design and use -Reasoning by analogy, hypothesis formation, and testing by machine -Management of biological databases