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ProBic: identification of overlapping biclusters usinf Probabilistic Relational Models, applied to simulated gene expression data
Published on Sep 07, 20073720 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
Chapter list
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