Mining amino acid association patterns in class B GPCRs

Q4 Health Professions

International Journal of Bioinformatics Research and Applications Pub Date : 2015-05-01 DOI:10.1504/IJBRA.2015.069193

Tannu Kumari, K. Pardasani

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引用次数: 3

Abstract

Class B GPCR family is a small group of receptors which are activated by peptides of intermediate length that range from 30 to 40 amino acid residues including hormones, neuropeptides and autocrine factors that mediate diverse physiological functions. They are involved in physiological processes like glucose homeostasis (glucagon and glucagon-like peptide-1), calcium homeostasis and bone turnover (parathyroid hormone and calcitonin), and control of the stress axis (corticotropin-releasing factor). Most of the GPCR structures and their functions are still unknown. Thus, the study of amino acid association patterns can be useful in prediction of their structure and functions. In view of above, in this paper, an attempt has been made to explore amino acid association patterns in class B GPCRs and their relationships with secondary structures and physiochemical properties. The fuzzy association rule mining is employed to take care of uncertainty due to variation in length of sequences. The association rules have been generated with the help of patterns discovered in the sequences.

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B类gpcr中氨基酸结合模式的挖掘

B类GPCR家族是由30 - 40个氨基酸残基的中间长度肽激活的一小群受体，包括激素、神经肽和自分泌因子，介导多种生理功能。它们参与葡萄糖稳态(胰高血糖素和胰高血糖素样肽-1)、钙稳态和骨转换(甲状旁腺激素和降钙素)以及应激轴(促肾上腺皮质激素释放因子)的控制等生理过程。大部分GPCR的结构和功能尚不清楚。因此，对氨基酸缔合模式的研究有助于预测其结构和功能。鉴于此，本文尝试探索B类gpcr中氨基酸的结合模式及其与二级结构和理化性质的关系。采用模糊关联规则挖掘方法，解决了序列长度变化带来的不确定性。关联规则是通过在序列中发现的模式生成的。

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

International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management

CiteScore

0.60

自引率

0.00%

发文量

期刊介绍： Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.