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+# A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses
+
+Copyright (C) 2013 J. Montes, E. Gomez, A. Merchan-Perez, J. DeFelipe, J. M. Peña
+
+This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+
+This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
+
+You should have received a copy of the GNU Lesser General Public License along with this program. If not, see [http://www.gnu.org/licenses/](http://www.gnu.org/licenses/).
+
+---
+
+## DISCLAIMER
+
+This is a lab development, intended for use only in experiments and not for full distribution. Familiarity with UNIX-like systems (Linux, Mac, etc.) command line operation is required for its use. An improved, more user-friendly version for this software is in development.
+
+---
+
+## TOOL
+
+A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses
+
+---
+
+## AUTHORS
+
+- J. Montes  
+- E. Gomez  
+- A. Merchán-Pérez  
+- J. DeFelipe  
+- J. M. Peña  
+
+---
+
+## VERSION
+
+1.0 alpha (pre-release)
+
+---
+
+## DESCRIPTION
+
+This is an implmentation of our machine-learning-based AMPA receptor activation prediction model.
+
+---
+
+## SYSTEM REQUIREMENTS
+
+- UNIX-like command line environment (Linux, MacOS X or similar). Windows is not directly supported. This software could be executed in Windows using cygwin, or other tool capable of creating a Linux-like environment.  
+- Java 1.6 or higher.  
+- The R statistical tool ([http://www.r-project.org/](http://www.r-project.org/)). This is used during the curve-fitting process. Previous versions of this software used MATLAB for this task, but we have replaced it with R, which produces the same result with improved performance. In addition, R is free, like the rest of this program requirements.  
+
+---
+
+## COMPONENTS
+
+- **ML-AMPA.sh:** This is the main program file. It is a bash shell script that performs the basic curve prediction tasks.  
+- **AMPA.O_model_M5P.bin:** This is the machine-learning model. It has been previously trained using a synapse dataset including 1000 different synapse configurations.  
+- **weka.jar:** The machine learning library.  
+- **src and bin directories:** They contain the Java source code and binary files of the AMPA receptor activation prediction model.  
+
+---
+
+## CONFIGURATION
+
+Before using this software, it has to be properly configured. To do so, the ML-AMPA.sh file must be edited. More specifically, the R_HOME variable inside this script has to be correctly set to the system path where R is installed. Without R the program cannot perform the final curve-fitting stage of the AMPA receptor activation prediction.
+
+---
+
+## USAGE
+
+To use this software, just change into the directory where the component files are and run the ML-AMPA.sh script. This script requires a set of 5 arguments to operate. These are the values of the synapse parameters:
+
+- **[AMPA]:** AMPA concentration, in molecules per square micron.  
+- **[T]:** Transporter concentration, in molecules per square micron.  
+- **Ls:** Synapse length, in nm.  
+- **Hc:** Synapse height, in nm.  
+- **E:** Side of total apposition length, relative factor to Ls  
+
+For example, running the following command:
+
+$ ./ML-AMPA.sh 2000 1600 500 16 1.5
+
+Would predict the AMPA receptor activation curve of a synapse with 2000 AMPA receptors per square micron, 1600 transporters per square micron, 500 nm of synaptic length, 16 nm of synaptic height and a total apposition length of 1.5 times Ls, that is 750 nm in total.
+
+Running this script will generate a csv file containing the predicted AMPA activation curve, sampled in 0.05 ms intervals. The results file is called result.csv.
+
+---
+
+2025-07-09: Converted README to Markdown.