Name
Title | ||
|---|---|---|
Genome segmentation using piecewise constant intensity models and reversible jump MCMC. |
Abstract | ||
|---|---|---|
The existence of whole genome sequences makes it possible to search for global structure in the genome. We consider modeling the occurrence frequencies of discrete patterns (such as starting points of ORFs or other interesting phenomena) along the genome. We use piecewise constant intensity models with varying number of pieces, and show how a reversible jump Markov Chain Monte Carlo (RJMCMC) method can be used to obtain a posteriori distribution on the intensity of the patterns along the genome. We apply the method to modeling the occurrence of ORFs in the human genome. The results show that the chromosomes consist of 5-35 clearly distinct segments, and that the posteriori number and length of the segments shows significant variation. On the other hand, for the yeast genome the intensity of ORFs is nearly constant. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1093/bioinformatics/18.suppl_2.S211 | BIOINFORMATICS |
Keywords | Field | DocType |
genome sequence,human genome | Genome,Data mining,Mathematical optimization,Markov chain Monte Carlo,Segmentation,Computer science,Algorithm,Jump,Piecewise | Conference |
Volume | Issue | ISSN |
18 | SUPnan | 1367-4803 |
Citations | PageRank | References |
9 | 0.87 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marko Salmenkivi | 1 | 161 | 13.42 |
| Juha Kere | 2 | 57 | 5.66 |
| Heikki Mannila | 3 | 6595 | 1495.69 |