IMfig was developed to be a program that generates a figure (in an ecapsulated postscript – eps – file) of an Isolation w/ Migration model that has been estimated from a data set. IMfig reads an output file generated with the IMa2 program. IM is a program, for the fitting of an isolation model with migration to haplotype data drawn from two closely related species or populations. IM is based on a method originally developed by Rasmus Nielsen and John Wakeley. Large numbers of loci can be studied simultaneously, and different mutation models can be used. IMa implements the same Isolation with Migration model, but does so using a new method that provides estimates of the joint posterior probability density of the model parameters. IMa also allows log likelihood ratio tests of nested demographic models.

IMfig takes as input a data set in fasta format (see below for details) along with the name of an output file generated by IMa. It reads the output file produced by IMa2 and creates a figure (eps format). The figure can be saved to a file, or imported into other programs. IMfig can also read an eps file produced with IMa from a data set.  The following types of data can be used: The output from a run of IM2. The output from a run of IMa with the -f0 or -f2 option, that is, with no input data sets. If input data sets are supplied, the locations of the data sets are indicated on the figure (see “Figure Description” section below for details). IMfig is written in Fortran, and was tested on Windows platforms only. IMfig requires that the JRE is installed. See also IM References IMa Manual. Wakeley, J. & Chan, M. (2002) Isolation with migration modelling using IMa and IMa2. Proceedings of the Royal Society B: Biological Sciences 269: 2239-2245. doi:10.1098/rspb.2002.1673 Wakeley, J. & Hey, J. (2003) Isolation with migration: the importance of the migration rate. Journal of Evolutionary Biology 16: 801–812. Wakeley, J. & Boyko, A. (2007) Simultaneous analysis of large numbers of loci using Isolation with migration: Methods and applications. Philosophical Transactions of the Royal Society B: Biological Sciences 362: 1459-1471. Wakeley, J. (2007) Isolation with migration: a Review. Evolutionary Applications 7: 1-19. Wakeley, J. (2007) Bayesian statistical methods for estimating divergence times and population sizes in island models. BioSystems 88: 53-61. Wakeley, J. (2011) Isolation with Migration and other demographic models. PLoS ONE 6(10): e24829. doi:10.1371/journal.pone.0024829 Wakeley, J. (2016) Isolation with Migration: Theory and Practice. Academic Press. Category:Bioinformatics software

Loads (and creates if necessary) data in memory from a file. Fit an Isolation with Migration model to the data. Reports parameters, log likelihoods, and graphic outputs. References External links IMa2 site Category:Bioinformatics softwareUnsuccessful microalgal-bacterial fuel cell applications. Several attempts were made to apply microalgal-bacterial systems in fuel cells. The principle of such systems is that microalgae grow by photosynthesis in a liquid culture containing an electron donor (such as acetate or methanol) in an anode compartment, while exoelectrogenic bacteria use the electron released by microalgae to oxidize the organic substrate. In this study, the microbial fuel cell (MFC) potential was measured and current densities were obtained. The maximum current was obtained at an external resistance of 3000 omega. Unsaturated air was fed to the anode compartment of the MFC. The maximum current obtained was 0.5-0.6 A for acetate (6.0 mM). When the cells were fed with methanol (4.4 mM) as the sole substrate, the MFC current was as low as 0.15 A. The anode potential was -200 mV, and the cathode potential was between -200 and -400 mV. In another experiment, the anode was inoculated with acetate-consuming bacteria and the current density was measured. These experiments revealed that the maximum current was obtained when the anode contained a population of exoelectrogenic bacteria. In a third experiment, microalgal cells were grown in a stirred tank reactor, containing acetate and biomass was separated from the broth by flocculation. The obtained biomass was used as a substrate in the MFC. There was a maximum current density of 0.2 A. The anode potential was -400 mV and the cathode potential was between -200 and -400 mV. A comparison of these results with similar results obtained with other systems indicated that MFCs have potential as power generation devices.[Analysis of influence factors of immunological tolerance induction in heart transplantation: experimental results]. The study aimed to explore the mechanism of immunological tolerance induced by heart transplantation. Totally, 45 Wistar rats were divided into groups as the following: 1. Allogeneic group of 2edc1e01e8

IMa is a package of programs that implements the IMa2 model of Isolation with Migration, which estimates demographic parameters from multilocus haplotype data. The model is equivalent to a continuous-time Markov model with two alleles at each of a large number of unlinked loci (including, for example, neutral loci). It is thus implemented by a computationally efficient Metropolis-Hastings Markov chain Monte Carlo sampler. IMa may be used to fit an Isolation with Migration model to data from a single population, to data from closely related populations, or to data from different populations across a species range. IMa can also be used to make approximate Bayesian computation (ABC) inference on parameters and parameter spaces. Documentation: See the documentation in the readme file for IMa2 for details of the commands and the program. A Tutorial Sample data This tutorial uses simulated data with a simple population history.  The data and the results from fitting the model to the data, with a modified mutation model, are shown in the following figure. Input file The input file for IMa2 is IMa_data_input.m.  A template input file is included in the IMa distribution, and this is updated for the simulated data. See the documentation for IMa2 for details of the format of the input file. Usage Assuming that an IMa program is called with the name IM, use the following command lines: IM ig dataInputFile > output.eps   Command-line arguments: See the documentation for IMa2 for details of the command-line arguments.   Programming language: C++   Date: Version 1.00, dated:

IM is a program for fitting an Isolation with Migration model to the data obtained from the analysis of a biallelic locus. IM is based on a method originally developed by Rasmus Nielsen and John Wakeley. The program implements a new method for the parameter estimation of the IM model, which allows the use of this model on large numbers of loci simultaneously, and also allows for nested models. Modules: IMa is composed of the following modules: imaData: Data handler for the input data. imaModel: Fitting of the Isolation with migration model. imaAnalysis: Fitting of the Isolation with migration model. imaMetaData: Fitting of the Isolation with migration model. imaResolve: Fitting of the Isolation with migration model. imaQMap: Fitting of the Isolation with migration model. Usage: 1. install with:./configure; make 2. Run: IM a.out -n l -c 1 -l 3. Eg.: Example 1: Execute with: ./configure; make; then Run: IMfig -n imgir -c 1 -l iml_log -l “1” -e “A.fig” -b “B.fig” Example 2: Run: IMfig -n iml_log -c 1 -l iml_log -l “1” -e “A.fig” -b “B.fig” -r imt Run with: ./configure; make; then Run: IMa -n imt -c 1 -l iml_log -l “1” -e “A.fig” -b “B.fig” Example 3: Run: IMa -n iml_log -c 1 -l iml_log -l “1” -e “A.fig” -b “B.fig” -r imt TODO: 1. Cross post 2. Add some documentation 3. Add some examples 4. Run with “./configure; make; ” first 5. Make some tests, which use model ms (mismatch swarms) and models ms_sc and ms_ps 6. Run IMa with ms_ps 7. Run IMa with no cross-migration 8. Adapt the QMap module to use some if-else statement, where option 4 in ima.f is to be implemented (Last updated: 1.0.0-8 – 20.03.2011 – 13

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