## ViDaExpert |

Development of ViDaExpert software is a continuous process which was started in 2000 by Dr. Andrei Zinovyev for his PhD thesis at the Institute Of Computational Modeling of Russian Academy of Science, was continued at IHES and moved to Bioinformatics service of Institut Curie. For the moment, it is actively used by researchers of Institut Curie for exploratory data analysis (mainly, microarray data).

ViDaExpert implements a number of methods for exploratory data analysis:

- Principal Components Analysis
- Weighted Principal Components Analysis
- Method of Elastic Maps for construction of Non-linear Principal Manifolds with Different Topologies
- PCA-based bi-plots
- Visualization of Functions by Coloring (non-linear analogue of bi-plots and visualization of density estimations)
- K-means clustering
- Hierarchical clustering
- Linear discriminant analysis
- Linear regression analysis
- Linear desicion tree construction machine

In ViDaExpert there is a well-developed set of tools to browse, annotate and mark datapoints with colors, shapes and sizes.

ViDaExpert is equiped with fast and convenient OpenGL-based 3D-viewer, which creates an integrative environment for exploratory data analysis.

ViDaExpert was shown to be a useful tool, in particular, in analysis of microarray data. There are special panels integrated to support analysis of microarray data (for example, dot-plots).

In the nearest future we plan to integrate into ViDaExpert several data analysis techniques, including a version of Independent Component Analysis.

- Gorban A.N., Pitenko A., Zinovyev A. ViDaExpert: user-friendly tool for nonlinear visualization and analysis of multidimensional vectorial data. ArXiv:1406.5550
- Gorban A.N., Zinovyev A. 2010. Principal manifolds and graphs in practice: from molecular biology to dynamical systems.
*Int J Neural Syst***20**(3):219-32. PDF - Gorban A.N. and Zinovyev A.
*Principal Graphs and Manifolds*. In*Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods and Techniques*(eds. Olivas E.S., Guererro J.D.M., Sober M.M., Benedito J.R.M., Lopes A.J.S.). Information Science Reference, September 4, 2009. PDF - Gorban A.N,, Zinovyev A. Elastic Principal Graphs and Manifolds and their Practical Applications.
*Computing, 2005*(PDF) - Zinovyev A.. Method And Software For Fast Construction Of Principal Manifolds Approximations. (PDF)
- Gorban A.N., Zinovyev A. Visualization of Data by Method of Elastic Maps and Its Applications in Genomics, Economics and Sociology. (PDF)
- Gorban A.N., Zinovyev A. and Wunsch D. Application of the method of elastic maps in analysis of genetic texts. (PDF)
- Zinovyev A.
*Visualization of Multidimensional Data*(in Russian). Krasnoyasrk: KGTU Publ., 2000, 168 p. PDF

- Non-linear Principal Manifolds - elastic maps approach. (PPT)

- Boss, G.J. and Kozloski, J.R. and Pickover, C.A. and Sand, A.R. (2014) Multi-dimensional channel directories. US Patent App. 14/030,521.
- Zinovyev A. (2011) Data visualization in political and social sciences.
*International Encyclopedia of Political Science (eds. Badie, B., Berg-Schlosser, D., Morlino, L. A.), SAGE Publications*, arXiv:1008.1188 - Resta M. (2010) Portfolio optimization through elastic maps: Some evidence
from the Italian stock exchange. Knowledge-Based Intelligent Information and
Engineering Systems, B. Apolloni, R.J. Howlett and L. Jain (eds.), Lecture Notes in
Computer Science
**4693**, Springer: Berlin – Heidelberg, 635-641. - Gorban A., Popova T., Zinovyev A. Four basic symmetry types in the universal 7-cluster structure of microbial genomic sequences.
*In Silico Biology, 2005*(HTML) - Carbone A., Kepes F., Zinovyev A. Codon Bias Signatures, Organization of Microorganisms in Codon Space, and Lifestyle.
*Mol.Biol.Evol., 2005*(PDF) - Carbone A., Zinovyev A., Kepes F. Codon Adaptation Index as a measure of dominating codon bias.
*Bioinformatics, 2003*(PDF) - Gorban A., Zinovyev A., Popova T. Seven Clusters In Genomic Triplet Distributions.
*In Silico Biology, 2003*(PDF)

- ViDaExpert 1.0 Overview
- ViDaExpert 1.0: Creating dataset
- ViDaExpert 1.0: Data visualization
- ViDaExpert 1.0: Data analysis

Look also at the description of elmap method.

- VidaExpert v1.2 executable (only Windows)

- VidaExpert v1.1 executable (only Windows)

- Special edition of ViDaExpert: visualization of Political Atlas of the World data

Note: no installation is required. Save the file and run it - Iris test data

The most famous dataset (flower dimensions) to test clustering algorithms - Files with public microarray data

Examples of microarray data analysis, public data.

Dr. Andrei Zinovyev