title: An evolving neural network for the interpretation of gene expression patterns.
abstract: It is of central interest in biology to understand how gene activity networks are coordinated and integrated in the cell. Within the field of genomics, microarray technologies have become a powerful technique for monitoring simultaneously the expression patterns of thousands of genes under different sets of conditions. A main task now is to propose analytical methods that can suggest which groups of genes are activated by similar conditions. We review several techniques based on self-organizing map and clustering algorithms but implemented through a network of units controlled by biologically inspired functions (see Table 1). The computer tool, named NBIA, permits a categorization that generates a set of gene groups with coordinated expression patterns.
authors.affiliation: Instituto de Investigación en Matematicas Aplicadas, Universidad Nacional Autonoma de Mexico (UNAM) Circuito Interior, Coyoacan, Mexico City, Mexico.
authors.forename: Maria del Carmen
authors.initials: Mdel C
authors.lastname: Marquez
authors.forename: Pedro Pablo Gonzalez
authors.initials: PP
authors.lastname: Perez
authors.forename: Jaime
authors.initials: J
authors.lastname: Lagunez-Otero
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D010363:Pattern Recognition, Automated / Q000706:statistics & numerical data; D012984:Software; D014584:User-Computer Interface