Update readme

README.md

@@ -4,9 +4,9 @@
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-    <a href="https://huggingface.co/spaces/TornikeO/simms" rel="nofollow"><img src="https://camo.githubusercontent.com/5762a687b24495afb299c2c0bc68674a2a7dfca9bda6ee444b9da7617d4223a6/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565" alt="Hugging Face Spaces" data-canonical-src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue" style="max-width: 100%;"></a>
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+  <td>
+    <a href="https://huggingface.co/spaces/TornikeO/simms" rel="nofollow"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Spaces-Demo-blue" alt="Hugging Face Spaces" style="max-width: 100%;"></a>
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@@ -39,7 +39,7 @@ Calculate similarity between large number of mass spectra using a GPU. SimMS aim
 
 ![alt text](assets/visual_guide.png)
 
-Comparing large sets of mass spectra can be done in parallel, since scores can be calculated independent of the other scores. By leveraging a large number of threads in a GPU, we created a GPU program (kernel) that calculates a 4096 x 4096 similarity matrix in a fraction of a second. By iteratvely calculating similarities for batches of spectra, SimMS can quickly process datasets much larger than the GPU memory. For details, visit the [preprint](https://www.biorxiv.org/content/biorxiv/early/2024/07/25/2024.07.24.605006.full.pdf).
+Comparing large sets of mass spectra can be done in parallel, since scores can be calculated independent of the other scores. By leveraging a large number of threads in a GPU, we created a GPU program (kernel) that calculates a 4096 x 4096 similarity matrix in a fraction of a second. By iteratively calculating similarities for batches of spectra, SimMS can quickly process datasets much larger than the GPU memory. For details, visit the [preprint](https://www.biorxiv.org/content/biorxiv/early/2024/07/25/2024.07.24.605006.full.pdf).
 
 # Quickstart
 
@@ -164,3 +164,19 @@ ref_id, query_id, scores = scores_cu.data['sparse_score']
 ref_id, query_id, matches = scores_cu.data['sparse_matches']
 ```
 
+
+# Citing SimMS  
+
+If you want to cite SimMS in your research, you can use the following BibTeX entry:
+
+```bibtex
+@article{Onoprishvili2024,
+	title = {SimMS: A GPU-Accelerated Cosine Similarity implementation for Tandem Mass Spectrometry},
+	author = {Onoprishvili, Tornike and Yuan, Jui-Hung and Petrov, Kamen and Ingalalli, Vijay and Khederlarian, Lila and Leuchtenmuller, Niklas and Chandra, Sona and Duarte, Aurelien and Bender, Andreas and Gloaguen, Yoann},
+	journal = {bioRxiv},
+	elocation-id = {2024.07.24.605006},
+	URL = {https://www.biorxiv.org/content/early/2024/07/25/2024.07.24.605006},
+	year = {2024},
+	doi = {10.1101/2024.07.24.605006}
+}
+```