Genetic Algorithms Select Protein Features Most Predictive of Enzyme Function
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Genetic Algorithms Select Protein Features Most Predictive of Enzyme Function Andrew Kernytsky, Burkhard Rost Columbia University
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Genetic Algorithms Select Protein Features Most Predictive of Enzyme Function. Andrew Kernytsky, Burkhard Rost Columbia University. Enzyme function prediction. Given protein sequence predict Enzyme Commission (EC) number. Ligases. Isomerases. Oxidoreductases. Lyases. Transferases. - PowerPoint PPT Presentation
Transcript of Genetic Algorithms Select Protein Features Most Predictive of Enzyme Function
Genetic Algorithms Select Protein Features Most Predictive of Enzyme
Function
Andrew Kernytsky, Burkhard Rost
Columbia University
Enzyme function predictionGiven protein sequence predict Enzyme Commission (EC) number
NC-IUBMB (1992) Recommendations of the International Union of Biochemistry on the Nomenclature and Classification of Enzymes. In, Enzyme Nomenclature. Academic Press, New York.
EC Wheel Figure: Porter CT, Bartlett GJ, Thornton JM. Nucleic Acids Res. 2004 January 1; 32: D129–D133.
OxidoreductasesOxidoreductases
TransferasesTransferasesHydrolasesHydrolases
LyasesLyases
IsomerasesIsomerasesLigasesLigases
TAGHCVNYDYGAGCQSGSPVbbbbbieeeiibbieeeeee..|....|......||....
AAAccCons
Intersection properties capture local information
20%
10%
5%
HHHEEEEELLEEEEELLLLLiiibbbbbbboooobbbbbb36788842100000000123
Feat 4Feat 5Feat 6
1%
0.1%
0.01%
All All GlobalGlobal
All All IntersectiIntersecti
onon
Limited local information
Significant risk of overfitting during training103+ features > 102 positive samples
Algorithm overview
Proteinsequence
MSNLLKDFEVAQC
AA
AA×sec
sec AA×sec
Inner Learning Algorithm
SVM
Neural Network
OR
0.635
0.688
0.677
Fitness Assesed
SelectionCrossoverMutation
AA×sec
AA AA×secsec AA×sec
2nd GenerationGenome Pop.
3rd GenerationGenome Pop.
GA Evolution
Genetic Algorithm
1st 2nd 3rd 4th Generation Populations
AAsecAA×secAA secAA AA×secsec AA×secAA sec AA×sec
All possible combinations
of feature classes [genomes]
AAsecAA×sec
All intersection and global
feature classes
GA improves performance
EC Level
Balance between intersection and global features gives best performance
AA, acc, sec, htm, cons-95
AA, acc, sec, cons-95
AA, acc, acc×sec, htm, cons-95
AA, sec, cons-97
AA, acc×sec, sec, cons-95
AA, acc, acc×sec×cons-94, sec
AA, AA×acc×sec×cons-95, sec, cons-95
AA, secAA, acc, sec×cons-94, cons-83×cons-94
AA, acc×sec×cons-89, cons-95
AA, acc×sec×cons-84×cons-94, sec
AA×acc×htm×cons-84×cons-95, acc, cons-94
AAAA, acc×cons-96, sec×cons-91
AA, acc×sec×cons-94, acc×cons-94
AA, acc×sec×cons-84×cons-94
AA, acc×sec×cons-88×cons-91×cons-95
AA×cons-94, acc×cons-94
AA×cons-82, acc×sec×cons-94
AA×cons-82, acc×sec×cons-94×cons-96
AA×sec×htm×cons-95×cons-96
