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The Challenge of Predicting Gene Function
Published on Feb 25, 20073664 Views
The biological sciences are undergoing an explosion in the amount of available data. New data analysis methods are needed to deal with the data. A central problem in bioinformatics is the assignment
Chapter list
The Challenge of Predicting Gene Function00:00
Gene Function Prediction01:39
Data Mining Prediction02:54
Predicting Gene Function in Yeast03:36
We Want to Map From Sequence to Function Class04:44
Classification Schemes 106:34
Classification Schemes 208:29
Classification Schemes 308:47
Sequence Data09:31
Homology data10:19
Predicted Secondary Structure Data12:13
Expression Data13:14
Phenotype Data13:40
What are the Machine Learning Issues15:08
Relational vs Propositional17:38
Data Mining Prediction (DMP) pt 118:28
Warmr19:08
PolyFARM20:44
Propositionalisation22:24
Dichotomic Search 123:18
Dichotomic Search 223:43
Data Mining Prediction (DMP) pt 224:48
C4.525:03
Data Mining Prediction (DMP) pt 2 (a)25:42
Results pt 126:01
Accuracy Table26:30
Expression Data Rule26:52
Structure Rule27:30
Alignment pt 128:29
Alignment pt 228:34
Homology Rule28:46
Application of DMP to Bacterial Genomes29:16
Example Rule (level 2 E. coli)30:22
Experimental Conformation31:42
“Wet” Biology Conformation32:14
Confirmation of “Wet” Predictions32:39
Extension to Arabidopsis Genome32:46
Results pt 234:32
Gibberellin Biosynthesis Prediction pt 134:45
Gibberellin Biosynthesis Prediction pt 235:55
Leaf Number35:59
Average Leaf Number at 21 Days Expt 436:26
Availability36:59
ILP 2005 Challenge 137:44
ILP 2005 Challenge 238:08
Propositional Approach38:31
Conclusions38:48
Acknowledgements39:52
PolyFARM (a)40:47