DYNSTOC: a tool for simulating large-scale rule-based models
Joshua Colvin, Michael I. Monine, James R. Faeder, William S. Hlavacek, Daniel Von Hoff, Richard G. Posner
Summary:
DYNSTOC implements a null-event kinetic Monte Carlo method for simulating chemical reactions in a homogenous reaction compartment.
The method can be used to simulate a large-scale biochemical reaction network, provided reaction rules are used to represent the
reactions in the network. DYNSTOC reads reaction rules written in the BioNetGen language (BNGL), which is useful, among other
purposes, for modeling protein-protein interactions involved in signal transduction. The simulation method does not require that
a network be specified explicitly but rather takes advan-tage of the availability of the reaction rules in a rule-based specification
of a network to determine if a randomly selected set of molecules participates in a reaction during a time step. Time is advanced
regardless of whether a reaction or null event occurs after selection of a set of potential reactants. The method of DYNSTOC is
closely related to that of STOCHSIM. DYNSTOC differs from STOCHSIM by allowing for model specification in terms of BNGL, which extends
the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be
simulated by conventional methods.
Availability:
DYNSTOC is Copyright 2008 Northern Arizona University and Copyright 2008-2009 The Translational Genomics Research Institute, All Rights Reserved.
For further details Click here!
Contact:
dynstoc@tgen.org
Cancer researchers are currently generating heterogeneous genomic data sets containing mRNA expression,
comparative genomic hybridization (CGH), and other information from multiple patients. In the near future, data sets will likely
include proteomics, methylomics, and high throughput sequencing data. Analytical tools that integrate these different data types
to prioritize genes for further study have lagged, however. With this in mind, we have implemented a standalone software
application that integrates the CGH and mRNA expression data generated as part of the Pancreas P01 project. This application
implements several different methods to generate ranked lists of genes and genomic regions based on breakpoint frequency,
aberration frequency, and the impact of copy number changes on mRNA expression.
Download:
CGH_Java_App.rar
is a Java based application for the analysis of gene expression data.
Working on the principles of cellular context mining, ExPattern
extracts statistically significant contexts: sub-groups of genes and
samples from the data.
is a stand-alone application which uses Gene Ontology information as
priors in the fuzzy-based clustering of gene expression data. Again
this application was developed in Java.
Please click on the links on the right side to read more about and download the software developed at our lab.
For further details Click here!
Purpose: This script makes chromosome plots showing expression values
on one or more epxpression arrays of pancreatic cancer tissues
which generates normalized M and A values for each probe
Written by: David W. Mount, Arizona Cancer Center, 2009
Download:
Chrom plots
Purpose: R script to find probes that have significantly altered expression
in xenografts of 21 pancreatic cancer tissues.
Written by: David W. Mount, Arizona Cancer Center, 2009
PLEASE NOTE: before the following analysis, we examine data quality of each array
and also correlation plots to look for arrays with abnormal distributions
cancer tissues are labeled red (psi5)
a reference commercial pool of normal acinar tissue is labeled green (psi3)
removed spaces in file and directory names and replaced with underscores
The agilent txt files have columns showing median red and green foreground values
and median red and green background values
these are read in below and backgrounds are subtracted
Agilent also includes annotation data and these are read in
all of the array files are in one directory.
# setwd sets the directory to the array file location on a particular machine
Download:
Limma Analysis