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Soft computing para clasificación de series dinámicas en perfiles de expresión genética

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOES20171107005
Publicado:
20/11/2017
Caducidad:
20/11/2018
Resumen:
Un centro tecnológico español ha desarrollado y patentado una nueva solución de soft computing que engloba varios algoritmos para la agrupación de genes coexpresados en microarrays de análisis de datos (MDA). El software incluye métodos de fusión que combinan en una sola agrupación las agrupaciones creadas a partir de cada serie temporal de los datos de microarrays generada de forma independiente. La detección de los clústeres más relevantes entre los posibles se realiza utilizando varias medidas sobre los genes, como el coeficiente de correlación de la información (ICC), el coeficiente de correlación de Pearson (PCC) y las medidas shape increase. El centro tecnológico busca instituciones y empresas con el fin de establecer acuerdos de comercialización con asistencia técnica y licencia y probar el software experimental.

Details

Tittle:
Soft computing for dynamic series classification in gene expression profiling
Summary:
A Spanish technology centre has developed and protected a new soft computing solution that comprises several algorithms for co-expressed genes grouping in data analysis microarrays (MDA). The software includes fusion methods that combine in just one group, every grouping created from each of the independently generated temporal series of microarray data. R-Y-D institutions and companies are sought for commercial with technical assistance, or license agreement to test the experimental software.
Description:
The identification of coexpressed genes from microarray data is a challenging problem in bioinformatics and computational biology. The technological center has developed this experimental software based on previous research work: shape-based clustering models were developed using the pattern of gene expression values over time and further incorporating knowledge about the correlation between the change in the gene expression level and the output value.
Consequently, the centre has developed a new soft computing system that comprises several algorithms for co-expressed genes grouping in data analysis microarrays (MDA).
Some of the included algorithms are:
· Shape index (SC). Grouping dismissing the output of each sample.
· Output shape index (SOC). Grouping according to the gene correlation with the output.
· Dynamic shape index (DSC). Dynamic version of SC.
· Output dynamic shape index (DSOC). Dynamic version of SOC.
· Relaxed shape index (RSC). SOC method enhancement.
The software includes fusion methods that combine in just one group every grouping created from each of the independently generated temporal series of microarray data.
The most relevant clusters detection among the available ones is performed by using several measurements on the genes, such as information correlation coefficient (ICC), Pearson correlation coefficient (PCC) and shape increase measures.
The software is suitable for researchers trying to determine relevant genes and their co-expressed relations for large dynamic data sets so that an output feature can be optimised. This new soft computing solution has proven to be useful for experimenting with time-series microarray of bacteria.
The technology centre is seeking for R-Y-D groups and companies, working in the industrial microbiology and biotechnology areas and in the field of bioinformatics, for commercial and license agreements.

Example Cluster of genes obtained by the software.
Advantages and Innovations:
The obtained results of the first testing activities confirmed the existence of relationships between output variables and gene expressions.
Moreover, the shape-based clustering methods showed promising results, being able to guide metabolic engineering actions with the identification of potential targets. As a result of this own research project, a specific experimental software was developed and recently protected.
The use of this new soft computing solution allows a shorter time for the development of new drugs.
Stage of Development:
Available for demonstration
IPs:
Secret Know-how,Exclusive Rights

Partner sought

Type and Role of Partner Sought:
The center is looking for:
-R-Y-D groups and companies working in the industrial microbiology and biotechnology areas, for testing activities and commercial agreements with technical assistance (help desk).
-Companies in the field of bioinformatics to better bring this software to market, through license agreements.

Client

Type and Size of Client:
R&D Institution
Already Engaged in Trans-National Cooperation:
Si
Languages Spoken:
English
French
Spanish

Keywords

Technology Keywords:
06003001 Bioinformática