Whole-cell models are promising tools for predicting phenotype from genotype by accounting for every individual gene and cell function. Whole-cell modeling has the potential to enable rational bioengineering and precision medicine. However, significant work remains to develop fully complete and accurate whole-cell models. The goal of the 2016 Whole-Cell Modeling Summer School is to provide young investigators cutting-edge training in large-scale dynamical modeling and model integration.
The course will be the first course focused on multi-algorithm whole-cell modeling. It will teach strategies for building and managing large models which aren't covered by any other course including multi-algorithm modeling, model organism database curation, surrogate modeling, and software development. The five-day course will feature didactic lectures, interactive hands-on tutorials, and student research talks. The mornings will feature lectures on modeling individual pathways. The afternoons will feature interactive hands-on tutorials on building and analyzing multi-algorithm models to generate and evaluate hypotheses. Throughout the course, students will work toward building a small whole-cell model. In addition, the course will include student talks to enable students to share their own research.
Who is the course for?
The course is designed for PhD students and postdoctoral scholars who wish to gain training in large-scale dynamical modeling. Students should already have a strong foundation in computational systems biology including dynamical modeling and scientific programming. See the pre-requesites section below for more information.
Extracted from Whole Cell 2016 website.