add citations.md

rdk · Nov 12, 2024 · c054385 · c054385
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@@ -1,30 +1,33 @@
 
 # Publications
 
+### 
+
 If you use P2Rank, please cite relevant papers: 
 
+
 * [Software article](https://doi.org/10.1186/s13321-018-0285-8) about P2Rank pocket prediction tool  
  Krivak R, Hoksza D. ***P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure.*** Journal of Cheminformatics. 2018 Aug.  
 ~~~bibtex
 @article{p2rank,
-  title={{P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure}},
-  author={Kriv{\'a}k, Radoslav and Hoksza, David},
-  journal={Journal of cheminformatics},
-  volume={10},
-  number={1},
-  pages={39},
-  year={2018},
-  publisher={Nature Publishing Group},
-  doi={10.1186/s13321-018-0285-8}
+    title={{P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure}},
+    author={Kriv{\'a}k, Radoslav and Hoksza, David},
+    journal={Journal of cheminformatics},
+    volume={10},
+    number={1},
+    pages={39},
+    year={2018},
+    publisher={Nature Publishing Group},
+    doi={10.1186/s13321-018-0285-8}
 }
 ~~~
 
 * [A new web-server article](https://doi.org/10.1093/nar/gkac389) about updates in the web interface [prankweb.cz](https://prankweb.cz)  
  Jakubec D, Skoda P, Krivak R, Novotny M, Hoksza D. ***PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures.*** Nucleic Acids Research, Volume 50, Issue W1, 5 July 2022, Pages W593–W597  
 ~~~bibtex
 @article{prankweb3,
-    author = {Jakubec, David and Skoda, Petr and Krivak, Radoslav and Novotny, Marian and Hoksza, David},
     title = "{PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures}",
+    author = {Jakubec, David and Skoda, Petr and Krivak, Radoslav and Novotny, Marian and Hoksza, David},
     journal = {Nucleic Acids Research},
     volume = {50},
     number = {W1},
@@ -41,48 +44,47 @@ If you use P2Rank, please cite relevant papers:
  Jendele L, Krivak R, Skoda P, Novotny M, Hoksza D. ***PrankWeb: a web server for ligand binding site prediction and visualization.*** Nucleic Acids Research, Volume 47, Issue W1, 02 July 2019, Pages W345-W349 
 ~~~bibtex
 @article{prankweb,
-  Author="Jendele, L.  and Krivak, R.  and Skoda, P.  and Novotny, M.  and Hoksza, D. ",
-   Title="{{P}rank{W}eb: a web server for ligand binding site prediction and visualization}",
-   Journal="Nucleic Acids Res.",
-   Year="2019",
-   Volume="47",
-   Number="W1",
-   Pages="W345-W349",
-   Month="Jul",
-   doi={10.1093/nar/gkz424}
+    title="{{P}rank{W}eb: a web server for ligand binding site prediction and visualization}",
+    author="Jendele, L.  and Krivak, R.  and Skoda, P.  and Novotny, M.  and Hoksza, D. ",
+    journal="Nucleic Acids Res.",
+    year="2019",
+    volume="47",
+    number="W1",
+    pages="W345-W349",
+    month="Jul",
+    doi={10.1093/nar/gkz424}
 }
 ~~~
 
 * [Conference paper](https://doi.org/10.1007/978-3-319-21233-3_4) introducing P2Rank prediction algorithm  
  Krivak R, Hoksza D. ***P2RANK: Knowledge-Based Ligand Binding Site Prediction Using Aggregated Local Features.*** International Conference on Algorithms for Computational Biology 2015 Aug 4 (pp. 41-52). Springer
 ~~~bibtex
 @inproceedings{p2rank-alcob,
-	title={{P2RANK: Knowledge-Based Ligand Binding Site Prediction Using Aggregated Local Features}},
-	author={Kriv{\'a}k, Radoslav and Hoksza, David},
-	booktitle={International Conference on Algorithms for Computational Biology},
-	pages={41--52},
-	year={2015},
-	organization={Springer},
-	doi={10.1007/978-3-319-21233-3_4}
+    title={{P2RANK: Knowledge-Based Ligand Binding Site Prediction Using Aggregated Local Features}},
+    author={Kriv{\'a}k, Radoslav and Hoksza, David},
+    booktitle={International Conference on Algorithms for Computational Biology},
+    pages={41--52},
+    year={2015},
+    organization={Springer},
+    doi={10.1007/978-3-319-21233-3_4}
 }
 ~~~
 
 * [Research article](https://doi.org/10.1186/s13321-015-0059-5) about PRANK rescoring algorithm (now included in P2Rank)  
  Krivak R, Hoksza D. ***Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features.*** Journal of Cheminformatics. 2015 Dec.
 ~~~bibtex
-@Article{prank,
-	author={Kriv{\'a}k, Radoslav
-	and Hoksza, David},
-	title={Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features},
-	journal={Journal of Cheminformatics},
-	year={2015},
-	month={Apr},
-	day={01},
-	volume={7},
-	number={1},
-	pages={12},
-	abstract={Protein-ligand binding site prediction from a 3D protein structure plays a pivotal role in rational drug design and can be helpful in drug side-effects prediction or elucidation of protein function. Embedded within the binding site detection problem is the problem of pocket ranking -- how to score and sort candidate pockets so that the best scored predictions correspond to true ligand binding sites. Although there exist multiple pocket detection algorithms, they mostly employ a fairly simple ranking function leading to sub-optimal prediction results.},
-	issn={1758-2946},
-	doi={10.1186/s13321-015-0059-5}
+@article{prank,
+    author={Kriv{\'a}k, Radoslav and Hoksza, David},
+    title={Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features},
+    journal={Journal of Cheminformatics},
+    year={2015},
+    month={Apr},
+    day={01},
+    volume={7},
+    number={1},
+    pages={12},
+    abstract={Protein-ligand binding site prediction from a 3D protein structure plays a pivotal role in rational drug design and can be helpful in drug side-effects prediction or elucidation of protein function. Embedded within the binding site detection problem is the problem of pocket ranking -- how to score and sort candidate pockets so that the best scored predictions correspond to true ligand binding sites. Although there exist multiple pocket detection algorithms, they mostly employ a fairly simple ranking function leading to sub-optimal prediction results.},
+    issn={1758-2946},
+    doi={10.1186/s13321-015-0059-5}
 }
 ~~~