Reverse engineering and identification in systems biology: strategies, perspectives and challenges | Zendy

Alejandro F. Villaverde | Zendy; Julio R. Banga | Zendy

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Reverse engineering and identification in systems biology: strategies, perspectives and challenges

Author(s) -

Alejandro F. Villaverde,

Julio R. Banga

Publication year - 2013

Publication title -

journal of the royal society interface

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.655

H-Index - 139

eISSN - 1742-5689

pISSN - 1742-5662

DOI - 10.1098/rsif.2013.0505

Subject(s) - reverse engineering , systems biology , identification (biology) , mathematical and theoretical biology , synthetic biology , computer science , management science , modelling biological systems , biology , data science , computational biology , biochemical engineering , ecology , engineering , bioinformatics , programming language

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

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