Biocharts: Unifying biological hypotheses with models and experiments

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Understanding how biological systems develop and function remains one of the main open scientific challenges of our times. An improved quantitative understanding of biological systems, assisted by computational models is also important for future bioengineering and biomedical applications. We present a computational approach aimed towards unifying hypotheses with models and experiments, allowing to formally represent what a biological system does (specification) how it does it (mechanism) and systematically compare to data characterizing system behavior (experiments). We describe our Biocharts framework geared towards supporting this approach and illustrate its application in several biological domains including bacterial colony growth, developmental biology, and stem cell population dynamics.

Original languageEnglish
Title of host publicationProceedings - IEEE 9th International Conference on e-Science, e-Science 2013
PublisherIEEE Computer Society
Pages317-325
Number of pages9
ISBN (Print)9780768550831
DOIs
StatePublished - 2013
Externally publishedYes
Event9th IEEE International Conference on e-Science, e-Science 2013 - Beijing, China
Duration: 22 Oct 201325 Oct 2013

Publication series

NameProceedings - IEEE 9th International Conference on e-Science, e-Science 2013

Conference

Conference9th IEEE International Conference on e-Science, e-Science 2013
Country/TerritoryChina
CityBeijing
Period22/10/1325/10/13

Keywords

  • Computational systems biology
  • Developmental biology
  • Stem cells
  • Temporal logic
  • Visual formalisms

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