Iterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equations

Handle URI:
http://hdl.handle.net/10754/623640
Title:
Iterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equations
Authors:
Gomez-Cabrero, David; Tegner, Jesper ( 0000-0002-9568-5588 )
Abstract:
The rise and growth of Systems Biology following the sequencing of the human genome has been astounding. Early on, an iterative wet-dry methodology was formulated which turned out as a successful approach in deciphering biological complexity. Such type of analysis effectively identified and associated molecular network signatures operative in biological processes across different systems. Yet, it has proven difficult to distinguish between causes and consequences, thus making it challenging to attack medical questions where we require precise causative drug targets and disease mechanisms beyond a web of associated markers. Here we review principal advances with regard to identification of structure, dynamics, control, and design of biological systems, following the structure in the visionary review from 2002 by Dr. Kitano. Yet, here we find that the underlying challenge of finding the governing mechanistic system equations enabling precision medicine remains open thus rendering clinical translation of systems biology arduous. However, stunning advances in raw computational power, generation of high-precision multi-faceted biological data, combined with powerful algorithms hold promise to set the stage for data-driven identification of equations implicating a fundamental understanding of living systems during health and disease.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Gomez-Cabrero D, Tegnér J (2017) Iterative Systems Biology for Medicine – Time for advancing from network signature to mechanistic equations. Current Opinion in Systems Biology. Available: http://dx.doi.org/10.1016/j.coisb.2017.05.001.
Publisher:
Elsevier BV
Journal:
Current Opinion in Systems Biology
Issue Date:
9-May-2017
DOI:
10.1016/j.coisb.2017.05.001
Type:
Article
ISSN:
2452-3100
Sponsors:
J.T. was supported by a CERIC (Center of Excellence for Research on Inflammation and Cardiovascular disease) grant, Vetenskapsrådet Medicine and Health (Dnr 2011-3264), Torsten Söderberg Foundation, FP7 STATegra, and AFA Insurance and Stockholm County Council. The authors would like to acknowledge helpful comments from Drs. Narsis Kiani and Saeed Shoiaie.
Additional Links:
http://www.sciencedirect.com/science/article/pii/S2452310017300057
Appears in Collections:
Articles; Biological and Environmental Sciences and Engineering (BESE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorGomez-Cabrero, Daviden
dc.contributor.authorTegner, Jesperen
dc.date.accessioned2017-05-17T07:41:40Z-
dc.date.available2017-05-17T07:41:40Z-
dc.date.issued2017-05-09en
dc.identifier.citationGomez-Cabrero D, Tegnér J (2017) Iterative Systems Biology for Medicine – Time for advancing from network signature to mechanistic equations. Current Opinion in Systems Biology. Available: http://dx.doi.org/10.1016/j.coisb.2017.05.001.en
dc.identifier.issn2452-3100en
dc.identifier.doi10.1016/j.coisb.2017.05.001en
dc.identifier.urihttp://hdl.handle.net/10754/623640-
dc.description.abstractThe rise and growth of Systems Biology following the sequencing of the human genome has been astounding. Early on, an iterative wet-dry methodology was formulated which turned out as a successful approach in deciphering biological complexity. Such type of analysis effectively identified and associated molecular network signatures operative in biological processes across different systems. Yet, it has proven difficult to distinguish between causes and consequences, thus making it challenging to attack medical questions where we require precise causative drug targets and disease mechanisms beyond a web of associated markers. Here we review principal advances with regard to identification of structure, dynamics, control, and design of biological systems, following the structure in the visionary review from 2002 by Dr. Kitano. Yet, here we find that the underlying challenge of finding the governing mechanistic system equations enabling precision medicine remains open thus rendering clinical translation of systems biology arduous. However, stunning advances in raw computational power, generation of high-precision multi-faceted biological data, combined with powerful algorithms hold promise to set the stage for data-driven identification of equations implicating a fundamental understanding of living systems during health and disease.en
dc.description.sponsorshipJ.T. was supported by a CERIC (Center of Excellence for Research on Inflammation and Cardiovascular disease) grant, Vetenskapsrådet Medicine and Health (Dnr 2011-3264), Torsten Söderberg Foundation, FP7 STATegra, and AFA Insurance and Stockholm County Council. The authors would like to acknowledge helpful comments from Drs. Narsis Kiani and Saeed Shoiaie.en
dc.publisherElsevier BVen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S2452310017300057en
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Current Opinion in Systems Biology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Current Opinion in Systems Biology, [, , (2017-05-09)] DOI: 10.1016/j.coisb.2017.05.001 . © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.titleIterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equationsen
dc.typeArticleen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalCurrent Opinion in Systems Biologyen
dc.eprint.versionPost-printen
dc.contributor.institutionUnit of Computational Medicine, Department of Medicine, Karolinska Institutet, Stockholm, 171 77, Swedenen
dc.contributor.institutionCenter for Molecular Medicine, Karolinska Institutet, Stockholm, 171 77, Swedenen
dc.contributor.institutionUnit of Clinical Epidemiology, Department of Medicine, Karolinska University Hospital, Stockholm, L8, 17176, Swedenen
dc.contributor.institutionScience for Life Laboratory, Solna, 17121, Swedenen
dc.contributor.institutionMucosal and Salivary Biology Division, King’s College London Dental Institute, London, SE1 9RT, United Kingdomen
dc.contributor.institutionUnit of Bioinformatics, NavarraBiomed, Departamento de Salud-Universidad Pública de Navarra, Pamplona-31008, Navarra, Spainen
kaust.authorTegner, Jesperen
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