AgentCell

File Release Notes and Changelog

Release Name: AgentCell 2.0

Notes:
AgentCell is now fully compatible with the latest version of StochSim (StochSim-1.6_core_2007JUL05.tar.gz NOT to be mixed up with the 1.6beta version of StochSim). 

Our changes to StochSim have now been merged into the main development trunck of StochSim. The latest version of 
StochSim on the sourceforge server is now fully compatible with this new version of AgentCell. StochSim is not distributed with AgentCell anymore. It is available on sourceforge. We still provide the StochSim file here for convenience.

AgentCell uses parts of Repast as a layer to provide agent-based capabilities. Repast is distributed under a BSD license and is included in the AgentCell distribution. AgentCell is distributed under the GPL license. AgentCell includes Xerces XML software developed by the Apache
Software Foundation (http://www.apache.org/). Please see the "licenses" directory for the licensing details of AgentCell and the software distributed with AgentCell.


Changes:


Ver 2.0 (LATEST VERSION):
========================
This new version of AgentCell can now handle many cells in the same VM. It is also fully compatible with the latest version of StochSim that can be found on sourceforge.


Ver 1.2:
=======
BUGS FIXED: (as of Feb 22, 2006) 1) Fixed the time counter overflow: Due to use of double in stochsim to store the time and convertion between double and long, the time variable was overflowing at some point causing the cells to become "blind" or insensitive after about 400 seconds of simulation. The sudden change in the slope of the
chemotactic response of wild type cells in figure 4 of Bioinformatics, 21, 2714-2721 (2005) at time t=400 secs is not due to the saturation of the receptors but is an artefact. With this bug fixed the wild type cells continue their strong chemotactic response until the end of the
simulation at 1000 sec, which is good news. If you were using agentcell for simulations shorter than 400 seconds or without ligand in the external medium your result should not be affected. This bug has been fixed using a quick fix. A more permanent solution is being implemented in stochsim: use of exact integer arithmetic to keep track of the number of time steps. 2) When defining more that 2 states for
the receptors the updating of receptor states as the cell was moving was being ignored. That was a bug in the wrapping of stochsim. Now one can define receptors with as many states as wanted. Notice that the simulations in the examples and in the Bioinformatics 21, 2714-2721
(2005) paper only used 2 receptors with two states (number of dynamic values defined in Stochsim) and therefore these results were not affected by this bug.


Ver 1.0:
=======
Unfortunately, because of the use of global variables in StochSim 1.4, only one instance of StochSim 1.4.1 can be used in each Java VM. In practice we run many independent AgentCells on a cluster, one AgentCell per node (see explanations in the above cited paper). Our goal however is
to have cells interacting with each other. To that end Tom Shimizu and Michael North have modified StochSim 1.4.1, removing all global variables and therefore allowing many instances of the StochSim class within one
AgentCell simulation. This new version of StochSim is currently being tested and will be released with the next version of AgentCell.


USAGE ON LINUX:
==============

we assume here that you unpack everything in a directory of your choice that we will call ROOT

A) download and install StochSim
===============================
0) download the latest version of stochsim (1.6, NOT 1.6beta) 
1) unpack everything inside of ROOT
2) cd stochsim/src
3) if on a 32 bit linux box:
		cp makefile.libstochsim.linux32 makefile
   if on a 64 bits linux box:
		cp makefile.libstochsim.linux64amd makefile
4) compile and install
		make
		make install
		 

B) Download and install AgentCell:
================================
0) download agentcell.2.??.tgz
1) unpack everything in ROOT.
2) cd agentcell
3) chmod +x run* javacompile cleanoutput
4) if on a 32 bits linux box:
		cd lib
		cp -f linux32/*.jar linux32/*.so .
		cd ..
   if on a 64 bits linux box:
   		cd lib
   		cp -f linux64amd/lib/*.jar .
   		cp -f linux64amd/lib/linux/*.so .
   		cp -f linux64amd/lib/ext/*.jar .
   		cd ..
5) ./javacompile
6) prepare the example:
		cd example/136_CHER/cpu001/cell1/network1
		ls
   if Output dir does not exist, create it: mkdir Output
		cd ../../
		cp -r cell1 cell2
		cd ..
		cp -r cpu001 cpu002
		cd ../..
7) run the example:
		./submitrun example/136_CHER
8) to locate the output files of the run 
		./printrun example/136_CHER
9) to see the data look at the VAR.OUT.gz or the CELL.hdf files
10) to clean and start from scratch
		./cleanrun example/136_CHER


C) To create your own run
========================
Modify:
	 	edu/uchicago/agentcell/runs/Example.java

	 	create a directory structure similar to the one in example/136_CHER