Welcome to the Systems Biology web-based platform KiMoSys, a web application for quantitative KInetic MOdels of biological SYStems. Kinetic models, with the aim to understand and subsequently design the metabolism of organism of interest are constructed iteratively and require accurate experimental data for both the generation and verification of hypotheses. Therefore, there is a growing requirement for exchanging experimental data and models between the systems biology community, and to automate as much as possible the kinetic model building, editing, simulation and analysis steps.
What is KiMoSys?
KiMoSys is a freely accessible web site that combines tasks for experimental data-store, search and share,
and tools in order to build ODE-based kinetic models into a single platform. It is intended to
support the systems biology community when doing experimental and computational research.
The future goal of KiMoSys is to provide an integrated platform that enables users to access experimental data and supports for the overall kinetic modeling tasks, so that tools that are used at different stages of the computational workflow can be easily used together.
♦ Allows to use the platform freely.
♦ Public repository of published data to ensure high accessibility and reuse.
♦ Capability to associate kinetic models with data; supports upload of intermediate versions of the final model.
♦ Invites the community to: experimental data and model files submissions. Submit your own data or from older articles whether or not you are an author.
♦ All data are citable.
♦ Upload facility to share data & associated models in a secure manner.
♦ Integrate tools to help the kinetic models construction process of metabolic networks.
♦ Facilitates its users even with little background in informatics.
Assistance in annotation
♦ Metadata collection to establish standards.
♦ Store essential properties about the data (conditions under which were obtained).
♦ Links to external databases.
Support standard formats
♦ CopasiML (COPASI models).
♦ BioSharing entry.
♦ Keep data and models private, share with specific users or the global community.
♦ Receive a stable and unique accession number that can be used as a publication reference.
♦ Based on Ruby on Rails. Facilitate the addition of other tools in the future.