Systems and methods for reconstructing gene networks in segregating populations
US8185367B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 2, 2005 |
| Grant date | May 22, 2012 |
| Priority date | — |
| Expiry date | Oct 1, 2027 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B40/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The reconstruction of genetic networks in mammalian systems is one of the primary goals in biological research, especially as such reconstructions relate to elucidating not only common, polygenic human disease, but living systems more generally. The present invention provides novel gene network reconstruction algorithms that utilize naturally occurring genetic variations as a source of perturbations to elucidate the networks. The algorithms incorporate relative transcript abundance and genotypic data from segregating populations by employing a generalized scoring function of maximum likelihood commonly used in Bayesian network reconstruction problems. The utility of these novel algorithms can be demonstrated via application to gene expression data from a segregating mouse population. The network derived from such data using the novel network reconstruction algorithm is able to capture causal associations between genes that result in increased predictive power, compared to more classically reconstructed networks derived from the same data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.