Making the most out of biological images
Since around the turn of this century, the volume and quality of numerical data have literally geometrically grown in biology as every where else.
Yet, passing from raw information to the human readable and convincing evidence of a biological phenomenon is far from trivial. We try to help biologists in this task, through automated image analysis and annotation, mathematical description of dynamic phenotypes and simulations.
Our approach to this problem can be qualified as systemic, as the quantification and formalization of observed phenotypes is considered an essential step in systems biology research . We provide tools to “bridge the gaps” between the various levels of organization and observation of a biological object, from the single protein to the phenotype.
Tools of the trade: scientific python
Each problem is unique, yet many share common grounds. This simple observation is at the root of the free software philosophy of open, reusable, shared software. We adhere entirely to this philosophy.
In practice, this means that once our results are published, the source code of our analysis becomes public. This has several virtues:
- The quality of our analysis can be vetted by the community
- Our collaborators are free to keep using the tools we developed together. : We are actually very welcoming to contributors!
- Free software and freedom of information is generally good for every body.
We rely on the marvellous scientific python ecosystem.