site updates: fix some usage informations, make authorship clear, add…

… logo (#212) * add name to copyright * remove sticky tabs and add small icon * fix typo * update citation and statement about authors * actually include the logo with the repo * update usage page and FAQ (about reconstruction methods) * remove old link * switch back to sticky tabs
SBC-Utrecht · Aug 7, 2024 · 1d7d238 · 1d7d238
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diff --git a/README.md b/README.md
@@ -2,10 +2,11 @@
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10728422.svg)](https://doi.org/10.5281/zenodo.10728422)
 
 
-# pytom-match-pick: GPU template matching for cryo-ET
+# pytom-match-pick
 
-GPU template matching, originally developed in [PyTom](https://github.com/SBC-Utrecht/PyTom), as a standalone python package that is run from the command 
-line.
+GPU-accelerated template matching for cryo-electron tomography, originally developed in [PyTom](https://github.com/SBC-Utrecht/PyTom), as a standalone Python package that is run from the command line. 
+
+This software is developed by Marten L. Chaillet ([@McHaillet](https://github.com/McHaillet)) and Sander Roet ([@sroet](https://github.com/sroet)) in the group of Friedrich Förster at Utrecht University.
 
 ![cover_image](docs/images/tomo200528_100_illustration.png)
 
@@ -141,23 +142,7 @@ Contributions to the project are very welcome! Feel free to make a pull request
 
 ## Citation
 
-For a reference on GPU accelerated template matching in tomograms please see the [IJMS publication](https://www.mdpi.com/1422-0067/24/17/13375).
-
-
-```
-@Article{ijms241713375,
-    AUTHOR = {Chaillet, Marten L. and van der Schot, Gijs and Gubins, Ilja and Roet, Sander and Veltkamp, Remco C. and Förster, Friedrich},
-    TITLE = {Extensive Angular Sampling Enables the Sensitive Localization of Macromolecules in Electron Tomograms},
-    JOURNAL = {International Journal of Molecular Sciences},
-    VOLUME = {24},
-    YEAR = {2023},
-    NUMBER = {17},
-    ARTICLE-NUMBER = {13375},
-    URL = {https://www.mdpi.com/1422-0067/24/17/13375},
-    ISSN = {1422-0067},
-    DOI = {10.3390/ijms241713375}
-}
-```
+Chaillet, M. L., van der Schot, G., Gubins, I., Roet, S., Veltkamp, R. C., & Förster, F. (2023). Extensive angular sampling enables the sensitive localization of macromolecules in electron tomograms. _International Journal of Molecular Sciences_, 24(17), 13375. <https://doi.org/10.3390/ijms241713375>
 
 <!--
 This ends the block for the website

diff --git a/docs/Frequently-asked-questions-(FAQ).md b/docs/Frequently-asked-questions-(FAQ).md
@@ -31,4 +31,8 @@ ax.set_xlabel('Particle index')
 ax.set_ylabel('LCCmax')
 ax.legend()
 plt.show()
-```
+```
+
+## What tomogram reconstruction method should I use?
+
+Have a look at this thread on our Discussions page: <https://github.com/SBC-Utrecht/pytom-match-pick/discussions/206>! Feel free to join in with the disucssion if you have another opinion or questions.
diff --git a/docs/Usage.md b/docs/Usage.md
@@ -17,15 +17,16 @@ Using template matching in this software consists of the following steps:
 
 ## 1. Creating a template and mask
 
-**Important**:
-- The template and mask need to have the same box size.
-- The template needs to have the same contrast as the tomogram (e.g. the particles 
+Keep in mind:
+
+* The template and mask need to have the same box size.
+* The template needs to have the same contrast as the tomogram (e.g. the particles 
   are black in both the tomogram and template). Contrast can be adjusted with the 
   `--invert` option.
 
 ### pytom_create_template.py
 
-Using an EM map as a reference structure generally leads to the best results. Alternatively a structure from the PDB can be converted in Chimera(X) using the molmap command to create an MRC file that models the electrostatic potential.
+Using an EM map as a reference structure generally leads to the best results. Alternatively a structure from the PDB can be converted in Chimera(X) using the molmap command to create an MRC file that models the electrostatic potential. A good ballpark for the box size of the template is 2 or 3 times the particle diameter (along its longest axis). 
 
 ```python exec="on" result="ansi" 
 import argparse

diff --git a/docs/images/60S_masked.png b/docs/images/60S_masked.png
diff --git a/docs/index.md b/docs/index.md
@@ -1,8 +1,8 @@
-# pytom-match-pick: GPU template matching for cryo-ET
+# pytom-match-pick
 
-GPU template matching, originally developed in [PyTom](https://github.
-com/SBC-Utrecht/PyTom), as a standalone python package that is run from the command 
-line.
+GPU-accelerated template matching for cryo-electron tomography, originally developed in [PyTom](https://github.com/SBC-Utrecht/PyTom), as a standalone Python package that is run from the command line. 
+
+This software is developed by Marten L. Chaillet ([@McHaillet](https://github.com/McHaillet)) and Sander Roet ([@sroet](https://github.com/sroet)) in the group of Friedrich Förster at Utrecht University.
 
 ![cover_image](images/tomo200528_100_illustration.png)
 

diff --git a/docs/tutorials/Tutorial.md b/docs/tutorials/Tutorial.md
@@ -100,7 +100,7 @@ pytom_match_template.py \
  -g 0
 ```
 
-A low-pass filter of 40 Å is set to prevent bias. Then, the angular search is calculated from the Crowther criterion using a diameter $d$ of 300 Å and a $r_{max}$ of 1/(40 Å) (due to the low-pass filter), which results in a roughly 7° increment ([see this wiki page for more info on the required sampling](https://github.com/SBC-Utrecht/pytom-template-matching-gpu/wiki/template-matching)). Here, the program was started on the system GPU with index 0. If you have more GPU's available for the tutorial you can simply add them and pytom-match-pick will automatically distribute the angular search, e.g. `-g 0 1 2 3` will run on the first 4 GPU's in the system.
+A low-pass filter of 40 Å is set to prevent bias. Then, the angular search is calculated from the Crowther criterion using a diameter $d$ of 300 Å and a $r_{max}$ of 1/(40 Å) (due to the low-pass filter), which results in a roughly 7° increment. Here, the program was started on the system GPU with index 0. If you have more GPU's available for the tutorial you can simply add them and pytom-match-pick will automatically distribute the angular search, e.g. `-g 0 1 2 3` will run on the first 4 GPU's in the system.
 
 **Out of memory!** Although unlikely to happen during the tutorial, in later usage of the software your GPUs might run out of memory. This is especially likely for 4x or lower binned tomograms. If this happens, you can use the `--split` option to tile the tomogram into multiple sections. You need to specify the number of splits along each dimension, for example `--split 2 1 1` will split into 2 sections along the x-axis, `--split 2 2 1` will split once in x and once in y, resulting in 4 subvolumes!
 

diff --git a/mkdocs.yml b/mkdocs.yml
@@ -3,7 +3,7 @@ site_url: https://SBC-Utrecht.github.io/pytom-match-pick
 site_author: Marten Chaillet
 repo_name: pytom-match-pick
 repo_url: https://github.com/SBC-Utrecht/pytom-match-pick
-copyright: Copyright &copy; 2024
+copyright: Copyright &copy; 2024 Marten L. Chaillet
 
 nav:
   - Home:
@@ -12,12 +12,13 @@ nav:
     - Timings: Timings.md
     - FAQ: Frequently-asked-questions-(FAQ).md
     - For developers: Developers.md
-  - Tutorial:
+  - Tutorials:
     - Ribosomes on ER microsomes: tutorials/Tutorial.md
   - Discussions: https://github.com/SBC-Utrecht/pytom-match-pick/discussions
   - Report a bug: https://github.com/SBC-Utrecht/pytom-match-pick/issues
 
 theme:
+  logo: images/60S_masked.png
   name: material
   features:
     - navigation.instant