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