update docs

README.md

@@ -8,21 +8,8 @@ CarveMe is a python-based tool for genome-scale metabolic model reconstruction.
 
 ### Documentation
 
-For more details please check: http://carveme.readthedocs.io/
+For instructions on installation and usage please check: http://carveme.readthedocs.io/
 
-### Installation
-
-Can be easily installed using **pip**:
-```
-pip install carveme
-```
-
-Additionally, you must install:
-   - diamond (conda install -c bioconda diamond)
-   - SCIP solver [optional] (conda install --c conda-forge pyscipopt)
-   - IBM CPLEX or Gurobi solver [recommended] (full version with academic license)
-
-
 ### Credits and License
 
 For citation purposes please refer to our paper:

docs/installation.rst

@@ -10,21 +10,32 @@ CarveMe can be easily installed using the **pip** package manager:
 
     $ pip install carveme
 
-Additionally, you must manually install these dependencies:
+Additionally, you must manually install the diamond_ sequence aligner:
 
-- diamond_ (conda install -c bioconda diamond)
-- SCIP_ solver [optional] (conda install --c conda-forge pyscipopt)
-- IBM CPLEX_ or Gurobi_ optimizer [recommended] (full version with academic license)
+.. code-block:: console
+
+    $ conda install -c bioconda diamond
+
+
+
+Solver
+------
+
+You also need an optimization solver. The recommended option is to install either IBM CPLEX_ or Gurobi_.
+You need a full version with the respective academic license (demo version will not work). 
+
+After installing CPLEX, **do not forget** to install the CPLEX python API.
+
+**Alternatively**, you can use the open source SCIP_ solver. This will be slower (expect at least 10 min per execution).
+
+.. code-block:: console
+
+    $ conda install --c conda-forge pyscipopt
 
 .. _diamond: https://github.com/bbuchfink/diamond
 .. _SCIP: https://scipopt.org
 .. _CPLEX: https://www.ibm.com/analytics/cplex-optimizer
 .. _Gurobi: https://www.gurobi.com/downloads/gurobi-software
-
-Note that you will need to register with IBM to obtain an `academic license for CPLEX <https://www.ibm.com/academic/home>`_.
-
-**IMPORTANT:** After installing CPLEX, do not forget to install the CPLEX python API (see the CPLEX documentation_ for details).
-
 .. _documentation: https://www.ibm.com/support/knowledgecenter/SSSA5P_12.7.1/ilog.odms.cplex.help/CPLEX/GettingStarted/topics/set_up/Python_setup.html
 
 Everything should be ready now! See the next section for instructions on how to start *carving*.