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Integrating Bioinformatics and Computational Biology: Perspectives and Possibilities for In Silico Network Reconstruction in Molecular Systems Biology

机译:整合生物信息学与计算生物学:分子系统生物学中计算机网络重构的前景与可能性

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摘要

There is a flood of molecular data about many aspects of cellular functioning. This data ranges from sequence and structural data to gene and protein regulation data, including time dependent changes in the concentration. Integration of the different datasets through computational methods is required to extract biological information that is relevant from a systems biology perspective.nnIn this paper we discuss how different computational tools and methods can be made to work together integrating different types of data, mining these data for biological information, and assisting in pathway reconstruction and biological hypotheses generation. We review the recent body of literature where such integrative approaches are used and discuss automation of data integration and model building to generate testable biological hypotheses. We analyze issues regarding the design of such automated tools and discuss what limitations and pitfalls can be foreseen for the automation and what solutions can computer science and biologists provide to overcome them.
机译:关于细胞功能许多方面的分子数据泛滥。该数据范围从序列和结构数据到基因和蛋白质调控数据,包括浓度随时间的变化。需要通过计算方法对不同数据集进行集成,以提取从系统生物学的角度来看相关的生物学信息。在本文中,我们讨论了如何利用不同的计算工具和方法来共同集成不同类型的数据,并将这些数据挖掘出来。生物信息,并协助途径重建和生物学假设的产生。我们回顾了使用此类集成方法的最新文献,并讨论了数据集成和模型构建的自动化以生成可检验的生物学假设。我们分析了有关此类自动化工具设计的问题,并讨论了可以预见的自动化限制和陷阱,以及计算机科学和生物学家可以提供哪些解决方案来克服这些问题。

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