Current challenges and approaches for the synergistic use of systems biology data in the scientific community.

EXS Pub Date : 2007-01-01 DOI:10.1007/978-3-7643-7439-6_12
Christian H Ahrens, Ulrich Wagner, Hubert K Rehrauer, Can Türker, Ralph Schlapbach
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引用次数: 10

Abstract

Today's rapid development and broad application of high-throughput analytical technologies are transforming biological research and provide an amount of data and analytical opportunities to understand the fundamentals of biological processes undreamt of in past years. To fully exploit the potential of the large amount of data, scientists must be able to understand and interpret the information in an integrative manner. While the sheer data volume and heterogeneity of technical platforms within each discipline already poses a significant challenge, the heterogeneity of platforms and data formats across disciplines makes the integrative management, analysis, and interpretation of data a significantly more difficult task. This challenge thus lies at the heart of systems biology, which aims at a quantitative understanding of biological systems to the extent that systemic features can be predicted. In this chapter, we discuss several key issues that need to be addressed in order to put an integrated systems biology data analysis and mining within reach.

当前的挑战和方法的协同使用系统生物学数据在科学界。
今天,高通量分析技术的快速发展和广泛应用正在改变生物学研究,并提供了大量的数据和分析机会,以了解过去几年无法想象的生物过程的基本原理。为了充分挖掘海量数据的潜力,科学家必须能够以综合的方式理解和解释这些信息。虽然每个学科内技术平台的数据量和异质性已经构成了重大挑战,但跨学科平台和数据格式的异质性使得数据的综合管理、分析和解释变得更加困难。因此,这一挑战是系统生物学的核心,其目的是对生物系统进行定量理解,以达到可以预测系统特征的程度。在本章中,我们讨论了需要解决的几个关键问题,以便将集成的系统生物学数据分析和挖掘置于触手可及的范围内。
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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