Create README.md

README.md

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+---
+license: lgpl-3.0
+language:
+- en
+tags:
+- chemistry
+- biology
+---
+
+# NucleoFind
+
+Nucleic acid electron density interpretation remains a difficult problem for computer programs to deal with. Programs tend to rely on exhaustive searches to recognise characteristic features. NucleoFind is a deep-learning-based approach to interpreting and segmenting electron density. Using a crystallographic map, the positions of the phosphate group, sugar ring and nitrogenous base group are able to be predicted with high accuracy.
+## Model Details
+
+### Model Description
+
+NucleoFind is based on a 3D-UNet architecture.
+
+
+- **Developed by:** Jordan Dialpuri, Jon Agirre, Kathryn Cowtan and Paul Bond, York Structural Biology Laboratory, University of York
+- **Funded by [optional]:** BBSRC
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** Python
+- **License:** LGPL-3
+
+## Model Card Authors [optional]
+
+Jordan Dialpuri
+
+## Model Card Contact
+
+Jordan Dialpuri - jordan.dialpuri (at) york.ac.uk