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The Challenge of Predicting Gene Function
Published on 2007-02-253667 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
Presentation
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