Eu, biólogo? A vingança de Roberto Takata

Minha produção bibliográfica está ficando cada vez mais biológica. Depois do PloS Computational Biology Active dendrites enhance neuronal dynamic range, com Leonardo Gollo e Mauro Copelli, agora um BMC Bioinformatics. Já me chamaram de neurocientista e de estatístico, daqui a pouco vão acabar me chamando de "biólogo"... E eu vou ter que retirar todas as provocações que fiz ao Roberto Takata!

Um artigo feito em colaboração com minha ex-orientada de doutorado, Mônica Campiteli, e o grupo da Farmácia onde ela faz o pós-doutorado.

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks.

Monica G Campiteli , Frederico M Soriani , Iran Malavazi , Osame Kinouchi , Carlos A B Pereira and Gustavo H Goldman

BMC Bioinformatics 2009, 10:270doi:10.1186/1471-2105-10-270

Published:	28 August 2009

Abstract (provisional)

Background

Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges.

Results

The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions.

Conclusions

Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

Foto: The single-celled fungus Saccharomyces cerevisiae, also known as brewer's yeast. Image courtesy David Byres, Florida Community College at Jacksonville.

Space: A bad influence on microbes?

Brewer's yeast itself is not pathogenic. Nevertheless, "yeast cells make a great 'model organism' for this research because they're easily handled, thoroughly studied, and their genome has been completely mapped," says Nickerson, the principal investigator of Yeast GAP. Furthermore, brewer's yeast shares much of its DNA with infectious species of microscopic fungi and protozoans. "Also, the yeast's genome is relatively simple, which makes the results easier to analyze," she says.

Still, the challenge is formidable. The brewer's yeast genome contains 6,312 genes, each of which produces one of the proteins that constitute the molecular machinery of the cell. To get a grip on this immense complexity, the researchers will send up 6,312 variants of the single-celled yeast. Each variant has a different gene "knocked out" and replaced with a unique "barcode" pattern of custom-made DNA. This barcode DNA does not encode a protein; it merely serves as a tag distinguishing that particular variant from all the others.

Apenas por associação de idéias... micróbios, espaço, virulência. A foto mostra que a dinâmica de colonização feita pelo fungo não é uniforme, mas produz buracos de ocupação bastante grandes. Lembra o meu modelo de colonização galáctica (as civilizações tecnológicas são os fungos do universo?), onde a presença desse tipo de buraco colonizatório explica o Paradoxo de Fermi: nós estariamos dentro de um deles, e portanto não adianta procurar civilizações ou mesmo planetas similares à Terra nas proximidades do sistema solar.