Added info on recent changes and how to cite paper

Author: ryanemenecker

README.md

@@ -28,6 +28,12 @@ https://metapredict.readthedocs.io/en/latest/getting_started.html
 For disorder predictions using our server, please see:
 https://metapredict.net
 
+## How to cite metapredict
+
+If you use metapredict for your work, please cite the metapredict paper - 
+ 
+*Emenecker RJ, Griffith D, Holehouse AS, metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure, Biophysical Journal (2021), doi: https:// doi.org/10.1016/j.bpj.2021.08.039.*
+
 
 ## Installation:
 
@@ -645,6 +651,13 @@ Example data that can be used with metapredict can be found in the metapredict/d
 
 This section is a log of recent changes with metapredict. My hope is that as I change things, this section can help you figure out why a change was made and if it will break any of your current work flows. The first major changes were made for the 0.56 release, so tracking will start there. Reasons are not provided for bug fixes for because the reason can assumed to be fixing the bug...
 
+#### V1.5
+
+Changes:
+Fixed bug causing some functions to fail when getting sequences from Uniprot.
+Added information on citing metapredict because the final publication went live.
+
+
 #### V1.4
 
 Change:

docs/changes.rst

@@ -6,6 +6,13 @@ About
 
 This section is a log of recent changes with metapredict. My hope is that as I change things, this section can help you figure out why a change was made and if it will break any of your current work flows. The first major changes were made for the 0.56 release, so tracking will start there.
 
+V1.5
+-----
+Changes:
+Fixed bug causing some functions to fail when getting sequences from Uniprot.
+Added information on citing metapredict because the final publication went live.
+
+
 V1.4
 -----
 Change:

docs/getting_started.rst

@@ -35,6 +35,14 @@ Consensus disorder scores are really useful as they distribute the biases and un
 The major advantages that **metapredict** offers over existing predictors is performance, ease of use, and ease of installation. Given **metapredict** uses a pre-trained bidirectional recurrent neural network, on hardware we've tested **metapredict** gives ~10,000 residues per second prediction power. This means that predicting disorder across entire proteomes is accessible in minutes - for example it takes ~20 minutes to predict disorder for every human protein in the reviewed human proteome (~23000 sequences). We provide **metapredict** as a simple-to-use Python library to integrate into existing Python workflows, and as a set of command-line tools for the stand-alone prediction of data from direct input or from FASTA files.
 
 
+How to cite metapredict
+===========================
+
+If you use metapredict for your work, please cite the metapredict paper - 
+ 
+Emenecker RJ, Griffith D, Holehouse AS, metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure, Biophysical Journal (2021), doi: https:// doi.org/10.1016/j.bpj.2021.08.039.
+
+
 Installation
 ==============
 **metapredict** is available through GitHub or the Python Package Index (PyPI). To install through PyPI, run

docs/how_to_cite.rst

@@ -0,0 +1,6 @@
+How to cite metapredict
+===========================
+
+If you use metapredict for your work, please cite the metapredict paper - 
+ 
+Emenecker RJ, Griffith D, Holehouse AS, metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure, Biophysical Journal (2021), doi: https:// doi.org/10.1016/j.bpj.2021.08.039.

docs/index.rst

@@ -17,6 +17,7 @@ Welcome to metapredict's documentation!
    usage/acknowledgements
    usage/troubleshooting
    changes
+   how_to_cite