Refine documentation (dptech-corp#1)

* readme

* add contributing and dco

CONTRIBUTING.md

@@ -0,0 +1,11 @@
+# How to Contribute
+
+Uni-Fold is an ongoing project. Our target is to develop better protein folding models and to apply them in real scenarios together with the entire community. We welcome all contributions to this repository, including but not limited to 1) reports and fixes of bugs, 2) new features and 3) accuracy and efficiency improvements.
+
+## Developer Certificate of Origin
+
+Contributions to this project must be accompanied by a [Developer Certificate of Origin](DCO.txt). You (or your employer) retain the copyright to your contribution. The certificate only restrict you to use the same license in your contribution.
+
+## Code review
+
+All submissions, including submissions by project members, require review. We use GitHub pull requests for this purpose. Consult [GitHub Help](https://help.github.com/articles/about-pull-requests/) for more information on using pull requests.

DCO.txt

@@ -0,0 +1,21 @@
+                      Developer Certificate of Origin
+
+By making a contribution to this project, the contributor(“I”) certify that:
+
+  (1) The contribution was created in whole or in part by me, and I have the 
+  right to submit it under the open source license indicated in the file; or
+
+  (2) The contribution is based upon previous work which is covered under an 
+  appropriate open source license and I have the right under that license to 
+  submit that work with modifications, whether created in whole or in part by 
+  me, which are under the same open source license (unless I am permitted to 
+  submit under a different license); or
+
+  (3) The contribution was provided directly to me by some other person who 
+  certified (1), (2) or (3),  and I have not modified it.
+
+  (4) I understand and agree that this project and the contribution are 
+  public, and that a record of the contribution (including all personal 
+  information I submit with it, including my sign-off) is maintained 
+  indefinitely and may be redistributed consistent with this project or the 
+  open source license(s) involved.

README.md

@@ -15,6 +15,8 @@ The name Uni-Fold is inherited from Uni-Fold-JAX. First released on Dec 8 2021,
 
 ## Installation
 
+[Instructions on installation]
+
 
 ## Preparing the datasets
 
@@ -39,19 +41,19 @@ Parameters are coming soon :)
 
 ## Running Uni-Fold
 
-After properly configurating the environment and databases, run the following command to predict the structure of the input fasta:
+After properly configurating the environment and databases, run the following command to predict the structure of the target fasta:
 
 ```bash
 bash run_unifold.sh \
-    path/to/the/input.fasta \           # fasta_path
-    path/to/the/output/directory/ \     # output_dir_base
-    path/to/the/databases \             # database_dir
-    2020-05-01 \                        # max_template_date
-    model_2_af2 \                       # model_name
-    path/to/model_parameters.pt         # param_path
+    /path/to/the/input.fasta \        # target fasta file
+    /path/to/the/output/directory/ \  # output directory
+    /path/to/database/directory/ \    # directory of databases
+    2020-05-01 \                      # use templates before this date
+    model_2_af2 \                     # specify model name
+    /path/to/model_parameters.pt      # model parameters
 ```
 
-[More descriptions for model names and ckp names]
+For monomer prediction, each fasta file shall contain only one sequence; for multimer prediction, the input fasta file shall contain all sequences of the target complex, **with duplicated homologous sequences**.
 
 ## Uni-Fold outputs
 
@@ -61,8 +63,11 @@ bash run_unifold.sh \
 
 ### Monomer Model
 
+[Train monomer code]
+
 ### Multimer Model
 
+[Train multimer code]
 
 ## Citing this work
 
@@ -81,10 +86,15 @@ Our training framework is based on [Uni-Core](https://github.com/dptech-corp/Uni
 ## License and Disclaimer
 
 Copyright 2022 DP Technology.
+
 ### Uni-Fold Code License
 
-Follow AlphaFold, Uni-Fold is licensed under permissive Apache Licence, Version 2.0.
+Uni-Fold is licensed under permissive Apache Licence, Version 2.0.
 
 ### Model Parameters License
 
-The Uni-Fold parameters are made available under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You can find details at: https://creativecommons.org/licenses/by/4.0/legalcode
+The Uni-Fold parameters are made available under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You can find details at: https://creativecommons.org/licenses/by/4.0/legalcode
+
+### Contributing to Uni-Fold
+
+Uni-Fold is an ongoing project. Our target is to develop better protein folding models and to apply them in real scenarios together with the entire community. We welcome all contributions to this repository, including but not limited to 1) reports and fixes of bugs, 2) new features and 3) accuracy and efficiency improvements. Please refer to [CONTRIBUTING.md](CONTRIBUTING.md) for more information.