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ProBic: identification of overlapping biclusters usinf Probabilistic Relational Models, applied to simulated gene expression data
Published on 2007-09-073732 Views
Biclustering is an increasingly popular technique to identify regulatory modules that are linked to biological processes. A bicluster is defined as a subset of genes which have a similar expression
Presentation
Identification of overlapping biclusters using Probabilistic Relational Models00:00
Overview00:06
Overview - Biclustering and biology00:37
Biclustering and biology - part 100:39
Biclustering and biology - part 201:03
Overview - Probabilistic Relational Models 02:05
Probabilistic Relational Models (PRMs) - part 102:06
Probabilistic Relational Models (PRMs) - part 202:48
Overview - ProBic biclustering model03:33
ProBic biclustering model: notation03:34
ProBic biclustering model - part 104:20
ProBic biclustering model - part 205:30
ProBic biclustering model - part 307:18
Overview - Algorithm07:53
Algorithm: choices07:55
ProBic biclustering model09:22
Algorithm: example - part 109:53
Algorithm: example - part 210:37
Overview - Results10:46
Results: noise sensitivity - part 110:48
Results: noise sensitivity - part 211:19
Results: bicluster shape independence - part 112:47
Results: bicluster shape independence - part 212:59
Results: 9 bicluster dataset (15 genes x 80 conditions)13:03
Overlap examples13:22
Missing values - part 114:44
Missing values - part 214:55
Conclusion15:17
Acknowledgements16:12