diff --git a/Readme.md b/Readme.md index bac603e5f1ed322ed61c6256b51121227bb1b679..7bd7205a26087e874365e72db3d04fba9234dff7 100644 --- a/Readme.md +++ b/Readme.md @@ -13,7 +13,7 @@ You don't need to install anything on your computer to interactively run the not ## Data -In this course, we are trying to reproduce a workflow used in other contexts, in particular Fiji, so that you can compare different approaches. For example you can check the excellent introduction to Fiji Macro programming by Anna Klemm [here](https://github.com/ahklemm/ImageJMacro_Introduction). We use images from [Cell Atlas](https://www.proteinatlas.org/humanproteome/cell) of the Human Protein Atlas (HPA) project where a large collection of proteins have been tagged and imaged to determine their cellular location. Specifically, we downloaded a series of [images](images) from the Atlas, with some cells showing nucleplasm localization and some nuclear membrane localization. The idea of the workflow is to compare the signal within the nucleus with that on its edge to determine for each image whether the protein is membrane bound or not. +In this course, we are trying to reproduce a workflow used in other contexts, in particular Fiji, so that you can compare different approaches. For example you can check the excellent introduction to Fiji Macro programming by Anna Klemm [here](https://github.com/ahklemm/ImageJMacro_Introduction). We use images from the [Cell Atlas](https://www.proteinatlas.org/humanproteome/cell) of the Human Protein Atlas (HPA) project where a large collection of proteins have been tagged and imaged to determine their cellular location. Specifically, we downloaded a series of [images](images) from the Atlas, with some cells showing nucleoplasm localization and some nuclear membrane localization. The idea of the workflow is to compare the signal within the nucleus with that on its edge to determine for each image whether the protein is membrane bound or not. The images in the [images](images) folder all come from the [Cell Atlas](https://www.proteinatlas.org/humanproteome/cell). For more information see the publication of Thul PJ et al., A subcellular map of the human proteome. **Science**. (2017) DOI: [10.1126/science.aal3321](https://doi.org/10.1126/science.aal3321). All images are covered by a [Creative Commons Attribution-ShareAlike 3.0 International License](https://creativecommons.org/licenses/by-sa/3.0/).