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Introduction to multi-algorithm whole-cell modeling


Jonathan Karr of Icahn School of Medicine at Mount Sinai
E-mail: karr@mssm.edu


The objective of this course is to provide an overview of multi-algorithm whole-cell modeling, discuss open questions in the field, and give students the tools to implement such models.


Whole-cell models are computational models which describe how cellular phenotypes arise from genotype by accounting for every gene function and predicting the dynamics of every molecular species over the entire cell cycle. Whole-cell models can be constructed by combining multiple sub-models of individual pathways (e.g. transcription, translation, metabolism), each described using different mathematics (e.g. differential equations, Boolean rules, flux balance analysis) and trained using different experimental data (RNA-seq, mass-spectrometry, kinetic assays), into a single model, enabling modelers to take advantage of existing, heterogeneous pathway models and experimental data. Whole-cell models have the potential to enable engineers to rationally design microorganisms and enable clinicians to tailor medical therapy to individual patients.

This course will introduce students to whole-cell modeling including the theory of multi-algorithm modeling, how to construct whole-cell models, and the existing software tools for whole-cell modeling. In addition, the course will outline the major open challenges in whole-cell modeling. The course will focus on concepts and tools which are important to whole-cell modeling.


The course will begin with interactive lectures which will introduce students to the main concepts in whole-cell modeling. Next, the course will have two hands-on tutorials on multi-algorithm modeling and how to use a published whole-cell model of Mycoplasma genitalium. In the first tutorial students will construct a model composed of sub-models of metabolism, transcription, translation, and RNA degradation. The course will conclude with an open discussion on the state and future of whole-cell modeling.

An introductory lecture will be given on the Friday prior to the course during the Interdisciplinary Friday seminar time.

Recommended Prerequisites:

  • Knowledge of systems biology
  • Knowledge of dynamical modeling including ordinary differential equations, logical modeling, and flux balance analysis
  • Knowledge of MATLAB


Dates: Intro lecture on Friday 25 March 18:00-19:00 and the 2 day workshop on 29-30 March 09:30-17:30
Location: TBA
Credits: 14 hours (2 full days)
Validation: Up to 14 hours based on approval from instructor


Enroll on Google Classroom

  • Log in with you cri-paris.org email address
  • Click the + in the top right corner of the screen and click Join class
  • Enter registration code: jk7odxz