The Center for Reproducible Biomedical Modeling is excited to announce a new monthly online seminar on cell modeling! The goals of the seminar are to foster discussion about the challenges to cell modeling and to encourage collaborations. The seminars will be held at 3 pm EDT on the first Tuesday of each month via Zoom [...]
We are excited to announce that the NIBIB and NIGMS have committed to fund the center through 2023 to develop technologies for scalable and reproducible modeling, provide free services to the community, advocate for reproducible modeling, and train researchers how to conduct modeling scalably and reproducibly. More info: EurekAlert Icahn School of Medicine [...]
The new website features an overview of the goals, challenges, plans, and methods of whole-cell modeling, as well as links to whole-cell models and whole-cell modeling tools, training materials, events, and research groups.
Jonathan Karr contributed a perspective on modeling and simulating to the standards panel at the 2018 GP-Write meeting.
The Karr Lab joined the GP-Write Standards Working Group and helped write a white paper on the standard protocols and formats that are needed for genome design and writing.
The Karr Lab published a perspective on how researchers are beginning to leverage recent progress in measurement technology, bioinformatics, data sharing, rule-based modeling, and multi-algorithmic simulation to build the first whole-cell models.
The Karr Lab proposed a plan for a project, termed the Human Whole-Cell Modeling Project, to achieve human whole-cell models. The foundations of the plan include technology development, standards development, and interdisciplinary collaboration.
To develop a plan for achieving human whole-cell models, the Karr Lab analyzed the existing models of individual cellular pathways, surveyed the biomodeling community, and reflected on theirr experience developing whole-cell models of bacteria.
Prof. Karr has his team have released an early version of their kinetic_datanator software tool for finding experimental data for building and calibrating dynamical models of cellular biochemistry. kinetic_datanator helps users find data such as metabolite, RNA, and protein abundances; protein complex compositions; transcription factor binding motifs; and kinetic parameters. kinetic_datanator is particularly useful for building large models, [...]
We released a new version (4.0) of the SemGen platform that includes a new user interface and new model merging capabilities.