minor doc changes

docs/source/installation.rst

@@ -7,4 +7,30 @@ To use SENSE-PPI, install it using pip:
 
 .. code-block:: bash
 
-   pip install senseppi
\ No newline at end of file
+   $ pip install senseppi
+
+SENSE-PPI can also be installed from source:
+
+.. code-block:: bash
+
+   $ git clone http://gitlab.lcqb.upmc.fr/Konstvv/SENSE-PPI.git
+   $ cd SENSE-PPI
+   $ python setup.py build; python setup.py install
+
+SENSE-PPI requires Python 3.9 or later.
+Additionally, required packages include:
+
+- numpy
+- pandas
+- wget
+- scipy
+- networkx
+- torch>=1.12
+- matplotlib
+- seaborn
+- tqdm
+- scikit-learn
+- pytorch-lightning==1.9.0
+- torchmetrics
+- biopython
+- fair-esm
\ No newline at end of file

docs/source/usage.rst

@@ -6,14 +6,14 @@ Usage
 Quick start
 ------------
 
-SENSE-PPI can be used to predict pairwise interactions between proteins. The input is a FASTA file with protein sequences.
-The output is a .tsv file with predictions as well as a secondary .tsv file with only positive interactions. By default, the predictions are made in "all vs all" manner: all possible protein pairs are considered.
+SENSE-PPI can be used to predict pairwise physical interactions between proteins. The simplest input is single a FASTA file with protein sequences.
+The output is a .tsv file with all predictions as well as a secondary .tsv file that contains only positive interactions. By default, the predictions are made in "all vs all" manner: all possible protein pairs from the input file are considered.
 
 In order to copmute the predictions for all possible pairs from FASTA file, the following command can be used:
 
 .. code-block:: bash
 
-    senseppi predict proteins.fasta
+    $ senseppi predict proteins.fasta
 
 By default, if no model is provided, the pre-trained model on human PPIs is used.