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Integrating Bioinformatics and Computational Biology: Perspectives and Possibilities for In Silico Network Reconstruction in Molecular Systems Biology
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BibTeX
@MISC{Alves_integratingbioinformatics,
author = {Rui Alves and Ester Vilaprinyo and Albert Sorribas},
title = {Integrating Bioinformatics and Computational Biology: Perspectives and Possibilities for In Silico Network Reconstruction in Molecular Systems Biology},
year = {}
}
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Abstract
Abstract: 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. In 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.
Keyphrases
computational biology silico network reconstruction molecular system biology biological information time dependent change pathway reconstruction recent body many aspect automated tool biological hypothesis generation molecular data cellular functioning different computational tool computational method model building system biology perspective integrative approach different datasets protein regulation data discus automation structural data testable biological hypothesis different type computer science data integration
