Collect all Casanovo references on a dedicated citation page

README.md

@@ -4,13 +4,16 @@
 
 ![image](https://user-images.githubusercontent.com/32707537/152622912-ca87da20-a64c-4e3f-9ca1-721c6b0d9c64.png)
 
-If you use Casanovo in your work, please cite the following publications:
+Casanovo is a state-of-the-art deep learning tool designed for _de novo_ peptide sequencing.
+Powered by a transformer neural network, Casanovo "translates" peaks in MS/MS spectra into amino acid sequences with remarkable precision.
+Achieving state-of-the-art performance, Casanovo is a versatile and powerful tool for discovery, with impactful applications in bottom-up proteomics, immunopeptidomics, metaproteomics, and beyond.
 
-- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. *De novo* mass spectrometry peptide sequencing with a transformer model. in *Proceedings of the 39th International Conference on Machine Learning - ICML '22* vol. 162 25514–25522 (PMLR, 2022). [https://proceedings.mlr.press/v162/yilmaz22a.html](https://proceedings.mlr.press/v162/yilmaz22a.html)
-- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Melendez, C.F., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *Nature Communications* **15**, 6427 (2024). [doi:10.1038/s41467-024-49731-x](https://doi.org/10.1038/s41467-024-49731-x)
+Why choose Casanovo?
 
-## Documentation
-
-#### https://casanovo.readthedocs.io/en/latest/
+- Unmatched accuracy: Cutting-edge AI ensures precise and reliable peptide sequencing, even in challenging datasets.
+- Open-source innovation: Freely available and easy to integrate into existing visualization workflows.
+- Actively maintained: Join a growing network of researchers and developers to stay at the forefront of technology.
 
+## [Documentation](https://casanovo.readthedocs.io/en/latest/)
 
+## [Citation information](https://casanovo.readthedocs.io/en/latest/cite.html)

casanovo/casanovo.py

@@ -95,20 +95,24 @@ def __init__(self, *args, **kwargs) -> None:
 def main() -> None:
     """# Casanovo
 
-    Casanovo de novo sequences peptides from tandem mass spectra using a
-    Transformer model. Casanovo currently supports mzML, mzXML, and MGF files
-    for de novo sequencing and annotated MGF files, such as those from
-    MassIVE-KB, for training new models.
+    Casanovo is a state-of-the-art deep learning tool designed for de
+    novo peptide sequencing. Powered by a transformer neural network,
+    Casanovo "translates" peaks in MS/MS spectra into amino acid
+    sequences.
 
     Links:
     - Documentation: [https://casanovo.readthedocs.io]()
     - Official code repository: [https://github.com/Noble-Lab/casanovo]()
 
     If you use Casanovo in your work, please cite:
-    - Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. De novo
-    mass spectrometry peptide sequencing with a transformer model. Proceedings
-    of the 39th International Conference on Machine Learning - ICML '22 (2022)
-    doi:10.1101/2022.02.07.479481.
+    - Yilmaz, M., Fondrie, W. E., Bittremieux, W., Melendez, C.F.,
+    Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence
+    translation from mass spectra to peptides with a transformer model.
+    in Nature Communications 15, 6427 (2024).
+    doi:10.1038/s41467-024-49731-x
+
+    For more information on how to cite different versions of Casanovo,
+    please see [https://casanovo.readthedocs.io/en/latest/cite.html]().
 
     """
     return

docs/cite.md

@@ -0,0 +1,35 @@
+# How to Cite Casanovo
+
+When using Casanovo in your research, please cite the relevant scientific publications to acknowledge the work and contributions behind the tool.
+Below, you will find detailed information on how to cite Casanovo, including citations for its various versions and functionalities.
+
+### Main Reference: Casanovo v4.x
+
+For general use of Casanovo, please cite the following paper:
+
+Yilmaz, M., Fondrie, W. E., Bittremieux, W., Melendez, C.F., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *Nature Communications* **15**, 6427 (2024). [doi:10.1038/s41467-024-49731-x](https://doi.org/10.1038/s41467-024-49731-x)
+
+### Casanovo v2.x: Spectrum Transformer Neural Network
+
+For research involving the spectrum transformer neural network architecture introduced in Casanovo v2.x:
+
+Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. *De novo* mass spectrometry peptide sequencing with a transformer model. in *Proceedings of the 39th International Conference on Machine Learning - ICML '22* vol. 162 25514–25522 (PMLR, 2022). [https://proceedings.mlr.press/v162/yilmaz22a.html](https://proceedings.mlr.press/v162/yilmaz22a.html)
+
+### Casanovo v4.2.x: Accounting for Digestion Enzyme Bias
+
+For work involving Casanovo's enhanced performance on tryptic and non-tryptic data:
+
+Melendez, C., Sanders, J., Yilmaz, M., Bittremieux, W., Fondrie, W. E., Oh, S. & Noble, W. S. Accounting for digestion enzyme bias in Casanovo. in *Journal of Proteome Research* **23**, 4761–4769 (2024). [doi:10.1021/acs.jproteome.4c00422](https://doi.org/10.1021/acs.jproteome.4c00422)
+
+### Casanovo for Database Searching
+
+For using Casanovo as a learned score function for sequence database searching:
+
+Ananth, V., Sanders, J., Yilmaz, M., Wen, B., Oh, S. & Noble, W. S. A learned score function improves the power of mass spectrometry database search. in *Bioinformatics* **40**, i410–i417 (2024). [doi:10.1093/bioinformatics/btae218](https://doi.org/10.1093/bioinformatics/btae218)
+
+## Notes for Citation
+
+- Always ensure you are citing the correct version or functionality of Casanovo relevant to your use case.
+- If you have questions about how to cite Casanovo in specific scenarios, feel free to reach out to the Casanovo community or maintainers.
+
+By citing Casanovo appropriately, you help support the ongoing development and innovation of this open-source tool. Thank you for contributing to the community!

docs/index.md

@@ -4,10 +4,15 @@
 
 ![image](https://user-images.githubusercontent.com/32707537/152622912-ca87da20-a64c-4e3f-9ca1-721c6b0d9c64.png)
 
-If you use Casanovo in your work, please cite the following publications:
+Casanovo is a state-of-the-art deep learning tool designed for _de novo_ peptide sequencing.
+Powered by a transformer neural network, Casanovo "translates" peaks in MS/MS spectra into amino acid sequences with remarkable precision.
+Achieving state-of-the-art performance, Casanovo is a versatile and powerful tool for discovery, with impactful applications in bottom-up proteomics, immunopeptidomics, metaproteomics, and beyond.
 
-- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Oh, S. & Noble, W. S. *De novo* mass spectrometry peptide sequencing with a transformer model. in *Proceedings of the 39th International Conference on Machine Learning - ICML '22* vol. 162 25514–25522 (PMLR, 2022). [https://proceedings.mlr.press/v162/yilmaz22a.html](https://proceedings.mlr.press/v162/yilmaz22a.html)
-- Yilmaz, M., Fondrie, W. E., Bittremieux, W., Melendez, C.F., Nelson, R., Ananth, V., Oh, S. & Noble, W. S. Sequence-to-sequence translation from mass spectra to peptides with a transformer model. in *Nature Communications* **15**, 6427 (2024). [doi:10.1038/s41467-024-49731-x](https://doi.org/10.1038/s41467-024-49731-x)
+Why choose Casanovo?
+
+- Unmatched accuracy: Cutting-edge AI ensures precise and reliable peptide sequencing, even in challenging datasets.
+- Open-source innovation: Freely available and easy to integrate into existing visualization workflows.
+- Actively maintained: Join a growing network of researchers and developers to stay at the forefront of technology.
 
 ```{toctree}
 ---
@@ -17,6 +22,7 @@ maxdepth: 1
 Getting Started <getting_started.md>
 File Formats <file_formats.md>
 FAQs <faq.md>
+Citing <cite.md>
 Contributing <CONTRIBUTING.md>
 Code of Conduct <CODE_OF_CONDUCT.md>
 Changelog <CHANGELOG.md>