Topics and projects

The key goal of systems biology is to achieve a system-level understanding of complex biological processes. The BMBF-funded project INCOME contributes to this by providing tools and workflows for a modular approach to understand cellular processes. Together, we aim at harmonizing and integrating models contributed by a variety of research groups into one comprehensive model. To achieve this, we address the following topics at the hackathon:

 

Topic 1: Implementation of import functionality for modeling tools

For the benchmark collection a combined model and dataset format has been established which provides all required information for model simulation, parameter estimation and uncertainty analysis. The benchmark collection was published in 2018 and collects 25 benchmark models. The format simplifies the communication of models and dataset and the evaluation of methods.

As part of the previous hackathon, we worked on import functions for established modeling tools, e.g.

• AMICI/ pyPESTO 
• AMIGO2
• Data2Dynamics

Here, we want to extend the work and implement additional functionalities. In addition, we hope that interfaces to additional tools can be established, e.g. COPASI , dMod and PyBioNetFit .

 

Topic 2: Development of a format validation tool

For the streaming of the modeling process, it would be important to have a format validator. A first version has been implemented at the previous hackathon. Here, we want to extend it, e.g. by adopting ISA Tools, and improve it further.

 

Topic 3: Extension of model and data repository

To improve the reuse of models and datasets, we want to extend our benchmark model repository. The benchmark collection was published in 2018 and collects 20 benchmark models. Additional published models should be included. For this the SBML files and the data have to be parsed into a specific format.

 

Topic 4: Development of comprehensive mechanistic model for cellular signaling

To facilitate the study of cellular processes in a larger context, we want to develop a modular, high-quality mechanistic description of signaling, gene regulation and metabolic processes. Instead of looking at individual pathways, the model will provide a comprehensive picture. The model will facilitate the integration of different datasets as various biological components (genes,transcripts, proteins, metabolites) can be integrated with different types of regulations. Here, we want to start establishing the modular mechanistic model based on established researches, including the model & data repository (Topic 3), the BioModels database and disease maps. For the model development, we will employ the model merging tool developed within INCOME.

 

Topic 5: Evaluation of supervised model merging

The model merging tool developed within INCOME will be evaluated on the models in the benchmark collection and additional models provided by participants.

 

Requirements to contribute to the hackathon: The topics covered by the hackathon are broad and allow for the contribution of persons with different backgrounds. Ideally, participants have programming experience (MATLAB, Python, R, etc.) or experience with mechanistic modeling. Furthermore, we invite users of the different software tools for the testing of the functionalities, the contribution of models to the model and data repository, and development of the comprehensive model of the cellular processes.