Suppr超能文献

免疫信息学——初来乍到的新事物。

Immunoinformatics--the new kid in town.

作者信息

Brusic Vladimir, Petrovsky Nikolai

机构信息

Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.

出版信息

Novartis Found Symp. 2003;254:3-13; discussion 13-22, 98-101, 250-2.

Abstract

The astounding diversity of immune system components (e.g. immunoglobulins, lymphocyte receptors, or cytokines) together with the complexity of the regulatory pathways and network-type interactions makes im munology a combinatorial science. Currently available data represent only a tiny fraction of possible situations and data continues to accrue at an exponential rate. Computational analysis has therefore become an essential element of immunology research with a main role of immunoinformatics being the management and analysis of immunological data. More advanced analyses of the immune system using computational models typically involve conversion of an immunological question to a computational problem, followed by solving of the computational problem and translation of these results into biologically meaningful answers. Major immunoinformatics developments include immunological databases, sequence analysis, structure modelling, mathematical modelling of the immune system, simulation of laboratory experiments, statistical support for immunological experimentation and immunogenomics. In this paper we describe the status and challenges within these sub-fields. We foresee the emergence of immunomics not only as a collective endeavour by researchers to decipher the sequences of T cell receptors, immunoglobulins, and other immune receptors, but also to functionally annotate the capacity of the immune system to interact with the whole array of selfand non-self entities, including genome-to-genome interactions.

摘要

免疫系统组成部分(如免疫球蛋白、淋巴细胞受体或细胞因子)的惊人多样性,连同调节途径和网络型相互作用的复杂性,使得免疫学成为一门组合科学。目前可得的数据仅代表了可能情况中的极小一部分,而且数据仍在以指数速度不断积累。因此,计算分析已成为免疫学研究的一个基本要素,免疫信息学的主要作用是管理和分析免疫学数据。使用计算模型对免疫系统进行更高级的分析通常包括将免疫学问题转化为计算问题,接着解决该计算问题,并将这些结果转化为具有生物学意义的答案。免疫信息学的主要进展包括免疫学数据库、序列分析、结构建模、免疫系统的数学建模、实验室实验模拟、免疫学实验的统计支持以及免疫基因组学。在本文中,我们描述了这些子领域的现状和挑战。我们预见免疫组学的出现,它不仅是研究人员为破译T细胞受体、免疫球蛋白和其他免疫受体序列而进行的集体努力,而且还包括对免疫系统与包括基因组与基因组相互作用在内的所有自身和非自身实体相互作用能力进行功能注释。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验