The Scientific Machine Learning (SciML) ecosystem is rapidly gaining momentum within the field of systems biology. With this birds of feather discussion we want to bring the international community of systems biology tool developers and users at one table to (a) brainstorm promising routes for future developments, and (b) facilitate collaborative projects.
Purpose: The Scientific Machine Learning (SciML) ecosystem in Julia holds great potential for applications in the field of systems biology. Much of this potential can be attributed to fast ODE solvers and parameter estimation packages, and convenient interface with neural differential equations and systems biology standards/formats. While an increasing number of systems biology groups are starting to use Julia to address biological questions, many existing systems biology tools are not yet available in Julia.
In this Birds of Feather discussion we want to address the following questions:
Significance: Bringing key players in the field of open-source systems biology tool development at one table to discuss the above questions will facilitate a flourishing ecosystem of systems biology tools and pipelines in Julia, and increase the uptake of the language by the community as a consequence.
Agenda: the following points will be on the agenda.
A short document summarizing the Birds of Feather discussion may be published on Twitter, Discourse and the sysbio-sciml Slack channel on the Julia workspace for the broader community by the end of August.
Moderators: Paul Lang and Anand Jain