******************************************************************************* * * 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/>. * ******************************************************************************* 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 fot his 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-Perez - 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/). This is used during the curve-fitting process. Previous verisons of this software used MATLAB for this task, but we have replace it with R, which produces the same result with improved performance. In adittion, 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 libary. - src and bin directories: They contain the Java sorice 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 user 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 molecues per square micron. - [T] : Transporter concentration, in molecues per square micron. - Ls : Synapse length, in nm. - Hc : Synapse height, in nm. - E : Side of total apposition lenght, relative factor to Ls Fo example, running the following command: $ ./ML-AMPA.sh 2000 1600 500 16 1.5 Would predict the AMPA receptor activation curve of a syanpse with 2000 AMPA receptors per square micrion, 1600 transporters per square micron, 500 nm of synaptic length, 16 nm of synaptic height and a total apposition lenght 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. ******************************************************************************* *******************************************************************************