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MATLAB programs for Microarray



MATLAB Mfiles/tools for microarray analysis (in alphabetical order)
  

M-file/tools Author Features Version Date Licence Remarks
Dimension reduction methods for tumor classification Antoniadis A, Lambert-Lacroix S, Leblanc F. Laboratoire IMAG-LMC, University Joseph Fourier, Dimension reduction statistical techniques in conjunction with nonparametric discriminant procedures for classification
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-
Free
Reference [PubMed]
Fuzzy C-Means for Clustering
Doulaye Dembélé and Philippe Kastner

IGBMC CNRS-INSERM-ULP,

Fuzzy C-Means for Clustering Microarray Data
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-
Free?
Download; Reference [PubMed]
F-scan P. J. Munson, V. V. Prabhu, L. Young; Analytical Biostatistics Section; Mathematical and Statistical Computing Laboratory; Center for Information Technology; National Institutes of Health Quantification and analysis of fluorescently probed microarrays; scatterplots; multiple image comparison; data merging and web links.  1.3 2001/07/30 Free for academic Download available upon registration; Manual; sample images for testing [pc][mac][unix]; reference [PubMed]
Greedy mixture learning for multiple motif discovery Blekas K, Fotiadis DI, Likas A. Department of Computer Science, University of Ioannina Discovering probabilistic motifs in a set of biological sequences by learning a mixture of motifs model through likelihood maximization.
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Free
Download; Reference [PubMed]
MA-ANOVA Gary Churchill's Statistical Genetics Group, The Jackson Laboratory MA-ANOVA is a set of functions written in Matlab for the analysis of variance on microarray data.  1.2 2002/03/20 free for academic registration before download; available in both windows and linux format; sample data 1; sample data 2; Readme;release notes; reference 1[pdf]; reference 2[pdf]; 
MatArray toolbox David Venet, Its main features are: Advanced normalization schemes; Very efficient implementation of hierarchical clustering, with leaf ordering and export to TreeView; Efficient implementation of K-means clustering.  ? Free start-up guide; reference;Toolbox (binaries non compiled); Toolbox (compiled for win32); Help files; Reference [PubMed]
MGraph
Wang J, Myklebost O, Hovig E.

Department of Tumour Biology, Norwegian Radium Hospital, Norway

applies graphical models as a natural environment to formulate and solve problems in microarray data analysis; allows the user to predict genetic regulatory networks by a graphical gaussian model (GGM), and to quantify the effects of different experimental treatment conditions on gene expression profiles by a graphical log-linear model (GLM). ?
?
Free
Reference [PubMed]
P-scan (Peak quantification using Statistical Comparative ANalysis) P. J. Munson, V. V. Prabhu, L. Young; Analytical Biostatistics Section; Mathematical and Statistical Computing Laboratory; Center for Information Technology; National Institutes of Health Quantification and analysis membrane cDNA array; scatterplots; multiple image comparison; data merging and web links. 1.2 2001/06/26 Free for academic registration before download; manual; samples images available; reference [PubMed]
PCA disjoint models for multiclass cancer analysis
Bicciato S, Luchini A, Di Bello C. Department of Chemical Process Engineering, University of Padova A computational procedure for marker identification and for classification of multiclass gene expression data through the application of disjoint principal component models -
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?
source codes are available from the authors. Reference [PubMed]
Quantum Clustering
David Horn, Assaf Gottlieb and Inon Axel Performing and evaluating the Quantum Clustering

method for data in arbitrary number of dimensions

?
?
Free?
Reference 1 [PubMed][ps]; Reference 2 [PubMed][ps];

Reference 3 [ps];

 



F-scan : Quantification and analysis of fluorescently probed microarrays

P-scan : Quantification and analysis membrane cDNA array

matarray : Matlab tools designed for the analysis of microarray data

mcgh : Analysing microarray-based CGH experiments 

Adjustment of Systematic Microarray Data Biases :


MANOVA :


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