@inproceedings{868978d9c92749b6972faadf8c56c0f4,
title = "In vitro-in silico interface platform: Bridging the gap between experiment and theory by information system to elucidate cellular behavior system",
abstract = "A multicellular organization is a complex system which is poorly understood. The mathematical model could provide a powerful tool for elucidating the mechanism, but the model evaluation has not been established. Here, we have achieved to establish the assessment system “in vitro-in silico interface platform”, which performs repetitive feedbacks of in vitro results and in silico results quantitatively. Controlling the initial conditions in vitro can improve the reproducibility of the developed pattern formation. By feature extraction, a large amount of these reproducible data are converted into the meaningful information. Comparing these features with in silico results repetitively, the mathematical model can be validated and optimized.",
keywords = "Collective cell migration, Feature extraction, Machine learning, Pattern formation",
author = "Asuka Yamaguchi and Masakazu Akiyama and Ikuhiko Nakase and Masaya Hagiwara",
note = "Publisher Copyright: {\textcopyright} 2019 CBMS-0001.; 23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019 ; Conference date: 27-10-2019 Through 31-10-2019",
year = "2019",
language = "英語",
series = "23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019",
publisher = "Chemical and Biological Microsystems Society",
pages = "340--341",
booktitle = "23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019",
}