Autocorrelation module¶
This module is used for computing the Autocorrelation descriptors based different
properties of AADs.You can also input your properties of AADs, then it can help you
to compute Autocorrelation descriptors based on the property of AADs. Currently, You
can get 720 descriptors for a given protein sequence based on our provided physicochemical
properties of AADs. You can freely use and distribute it. If you hava any problem,
you could contact with us timely!
References:
[1]: http://www.genome.ad.jp/dbget/aaindex.html
[2]:Feng, Z.P. and Zhang, C.T. (2000) Prediction of membrane protein types based on
the hydrophobic index of amino acids. J Protein Chem, 19, 269-275.
[3]:Horne, D.S. (1988) Prediction of protein helix content from an autocorrelation
analysis of sequence hydrophobicities. Biopolymers, 27, 451-477.
[4]:Sokal, R.R. and Thomson, B.A. (2006) Population structure inferred by local
spatial autocorrelation: an Usage from an Amerindian tribal population. Am J
Phys Anthropol, 129, 121-131.
Authors: Zhijiang Yao and Dongsheng Cao.
Date: 2016.06.04
Email: gadsby@163.com
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Autocorrelation.
CalculateAutoTotal
(ProteinSequence)[source]¶ A method used for computing all autocorrelation descriptors based on 8 properties of AADs.
Usage:
result=CalculateGearyAutoTotal(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30*8*3=720 normalized Moreau Broto, Moran, and Geary
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Autocorrelation.
CalculateEachGearyAuto
(ProteinSequence, AAP, AAPName)[source]¶ you can use the function to compute GearyAuto
descriptors for different properties based on AADs.
Usage:
result=CalculateEachGearyAuto(protein,AAP,AAPName)
Input: protein is a pure protein sequence.
AAP is a dict form containing the properties of 20 amino acids (e.g., _AvFlexibility).
AAPName is a string used for indicating the property (e.g., ‘_AvFlexibility’).
Output: result is a dict form containing 30 Geary autocorrelation
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Autocorrelation.
CalculateEachMoranAuto
(ProteinSequence, AAP, AAPName)[source]¶ you can use the function to compute MoranAuto
descriptors for different properties based on AADs.
Usage:
result=CalculateEachMoranAuto(protein,AAP,AAPName)
Input: protein is a pure protein sequence.
AAP is a dict form containing the properties of 20 amino acids (e.g., _AvFlexibility).
AAPName is a string used for indicating the property (e.g., ‘_AvFlexibility’).
Output: result is a dict form containing 30 Moran autocorrelation
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Autocorrelation.
CalculateEachNormalizedMoreauBrotoAuto
(ProteinSequence, AAP, AAPName)[source]¶ you can use the function to compute MoreauBrotoAuto
descriptors for different properties based on AADs.
Usage:
result=CalculateEachNormalizedMoreauBrotoAuto(protein,AAP,AAPName)
Input: protein is a pure protein sequence.
AAP is a dict form containing the properties of 20 amino acids (e.g., _AvFlexibility).
AAPName is a string used for indicating the property (e.g., ‘_AvFlexibility’).
Output: result is a dict form containing 30 Normalized Moreau-Broto autocorrelation
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Autocorrelation.
CalculateGearyAuto
(ProteinSequence, AAProperty, AAPropertyName)[source]¶ A method used for computing GearyAuto for all properties
Usage:
result=CalculateGearyAuto(protein,AAP,AAPName)
Input: protein is a pure protein sequence.
AAProperty is a list or tuple form containing the properties of 20 amino acids (e.g., _AAProperty).
AAPName is a list or tuple form used for indicating the property (e.g., ‘_AAPropertyName’).
Output: result is a dict form containing 30*p Geary autocorrelation
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Autocorrelation.
CalculateGearyAutoAvFlexibility
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
AvFlexibility.
Usage: result=CalculateGearyAutoAvFlexibility(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoFreeEnergy
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
FreeEnergy.
Usage:
result=CalculateGearyAutoFreeEnergy(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoHydrophobicity
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
hydrophobicity.
Usage:
result=CalculateGearyAutoHydrophobicity(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoMutability
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
Mutability.
Usage:
result=CalculateGearyAutoMutability(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoPolarizability
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
Polarizability.
Usage:
result=CalculateGearyAutoPolarizability(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoResidueASA
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
ResidueASA.
Usage:
result=CalculateGearyAutoResidueASA(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoResidueVol
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
ResidueVol.
Usage:
result=CalculateGearyAutoResidueVol(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoSteric
(ProteinSequence)[source]¶ Calculte the GearyAuto Autocorrelation descriptors based on
Steric.
Usage:
result=CalculateGearyAutoSteric(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Geary Autocorrelation
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Autocorrelation.
CalculateGearyAutoTotal
(ProteinSequence)[source]¶ A method used for computing Geary autocorrelation descriptors based on 8 properties of AADs.
Usage:
result=CalculateGearyAutoTotal(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30*8=240 Geary
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Autocorrelation.
CalculateMoranAuto
(ProteinSequence, AAProperty, AAPropertyName)[source]¶ A method used for computing MoranAuto for all properties
Usage:
result=CalculateMoranAuto(protein,AAP,AAPName)
Input: protein is a pure protein sequence.
AAProperty is a list or tuple form containing the properties of 20 amino acids (e.g., _AAProperty).
AAPName is a list or tuple form used for indicating the property (e.g., ‘_AAPropertyName’).
Output: result is a dict form containing 30*p Moran autocorrelation
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Autocorrelation.
CalculateMoranAutoAvFlexibility
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
AvFlexibility.
Usage:
result=CalculateMoranAutoAvFlexibility(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoFreeEnergy
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
FreeEnergy.
Usage:
result=CalculateMoranAutoFreeEnergy(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoHydrophobicity
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on hydrophobicity.
Usage:
result=CalculateMoranAutoHydrophobicity(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoMutability
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
Mutability.
Usage:
result=CalculateMoranAutoMutability(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoPolarizability
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
Polarizability.
Usage:
result=CalculateMoranAutoPolarizability(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoResidueASA
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
ResidueASA.
Usage:
result=CalculateMoranAutoResidueASA(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoResidueVol
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
ResidueVol.
Usage:
result=CalculateMoranAutoResidueVol(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoSteric
(ProteinSequence)[source]¶ Calculte the MoranAuto Autocorrelation descriptors based on
AutoSteric.
Usage:
result=CalculateMoranAutoSteric(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Moran Autocorrelation
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Autocorrelation.
CalculateMoranAutoTotal
(ProteinSequence)[source]¶ A method used for computing Moran autocorrelation descriptors based on 8 properties of AADs.
Usage:
result=CalculateMoranAutoTotal(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30*8=240 Moran
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Autocorrelation.
CalculateNormalizedMoreauBrotoAuto
(ProteinSequence, AAProperty, AAPropertyName)[source]¶ A method used for computing MoreauBrotoAuto for all properties.
Usage:
result=CalculateNormalizedMoreauBrotoAuto(protein,AAP,AAPName)
Input: protein is a pure protein sequence.
AAProperty is a list or tuple form containing the properties of 20 amino acids (e.g., _AAProperty).
AAPName is a list or tuple form used for indicating the property (e.g., ‘_AAPropertyName’).
Output: result is a dict form containing 30*p Normalized Moreau-Broto autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoAvFlexibility
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on
AvFlexibility.
Usage:
result=CalculateNormalizedMoreauBrotoAutoAvFlexibility(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoFreeEnergy
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on
FreeEnergy.
Usage:
result=CalculateNormalizedMoreauBrotoAutoFreeEnergy(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoHydrophobicity
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on
hydrophobicity.
Usage:
result=CalculateNormalizedMoreauBrotoAutoHydrophobicity(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoMutability
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on Mutability.
Usage:
result=CalculateNormalizedMoreauBrotoAutoMutability(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoPolarizability
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on
Polarizability.
Usage:
result=CalculateNormalizedMoreauBrotoAutoPolarizability(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoResidueASA
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on
ResidueASA.
Usage:
result=CalculateNormalizedMoreauBrotoAutoResidueASA(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoResidueVol
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on
ResidueVol.
Usage:
result=CalculateNormalizedMoreauBrotoAutoResidueVol(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoSteric
(ProteinSequence)[source]¶ Calculte the NormalizedMoreauBorto Autocorrelation descriptors based on Steric.
Usage:
result=CalculateNormalizedMoreauBrotoAutoSteric(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30 Normalized Moreau-Broto Autocorrelation
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Autocorrelation.
CalculateNormalizedMoreauBrotoAutoTotal
(ProteinSequence)[source]¶ A method used for computing normalized Moreau Broto autocorrelation descriptors based
on 8 proterties of AADs.
Usage:
result=CalculateNormalizedMoreauBrotoAutoTotal(protein)
Input: protein is a pure protein sequence.
Output: result is a dict form containing 30*8=240 normalized Moreau Broto
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Autocorrelation.
NormalizeEachAAP
(AAP)[source]¶ All of the amino acid indices are centralized and
standardized before the calculation.
Usage:
result=NormalizeEachAAP(AAP)
Input: AAP is a dict form containing the properties of 20 amino acids.
Output: result is the a dict form containing the normalized properties