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The Present and the Future Perspectives of Biological Network Inference
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Author(s): Paola Lecca (The Microsoft Research – University of Trento, Centre for Computational and Systems BiologyThe Microsoft Research – University of Trento, Centre for Computational and Systems Biology, Trento, Italy)and Alida Palmisano (The Microsoft Research – University of Trento, Centre for Computational and Systems Biology, Trento, Italy)
Copyright: 2012
Pages: 23
Source title:
Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances
Source Author(s)/Editor(s): Paola Lecca (The Microsoft Research – University of Trento, Centre for Computational and Systems Biology, Italy), Dan Tulpan (National Research Council of Canada, Canada)and Kanagasabai Rajaraman (Institute for Infocomm Research, Singapore)
DOI: 10.4018/978-1-61350-435-2.ch006
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Abstract
Biological network inference is based on a series of studies and computational approaches to the deduction of the connectivity of chemical species, the reaction pathway, and the reaction kinetics of complex reaction systems from experimental measurements. Inference for network structure and reaction kinetics parameters governing the dynamics of a biological system is currently an active area of research. In the era of post-genomic biology, it is a common opinion among scientists that living systems (cells, tissues, organs and organisms) can be understood in terms of their network structure as well as in term of the evolution in time of this network structure. In this chapter, the authors make a survey of the recent methodologies proposed for the structure inference and for the parameter estimation of a system of interacting biological entities. Furthermore, they present the recent works of the authors about model identification and calibration.
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