DocumentCode :
653992
Title :
Biocharts: Unifying Biological Hypotheses with Models and Experiments
Author :
Kugler, Hillel
fYear :
2013
fDate :
22-25 Oct. 2013
Firstpage :
317
Lastpage :
325
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.
Keywords :
biology computing; optimisation; bacterial colony growth; biocharts framework; bioengineering applications; biological hypotheses; biomedical applications; computational models; data characterizing system behavior; developmental biology; stem cell population dynamics; Biological system modeling; Computational modeling; Microorganisms; Object oriented modeling; Semantics; Computational Systems Biology; Developmental Biology; Stem Cells; Temporal Logic; Visual Formalisms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
eScience (eScience), 2013 IEEE 9th International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/eScience.2013.41
Filename :
6683923
Link To Document :
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