Autocorrelation module

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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)

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

Autocorrelation.CalculateEachGearyAuto(ProteinSequence, AAP, AAPName)

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

Autocorrelation.CalculateEachMoranAuto(ProteinSequence, AAP, AAPName)

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

Autocorrelation.CalculateEachNormalizedMoreauBrotoAuto(ProteinSequence, AAP, AAPName)

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

Autocorrelation.CalculateGearyAuto(ProteinSequence, AAProperty, AAPropertyName)

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

Autocorrelation.CalculateGearyAutoAvFlexibility(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoFreeEnergy(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoHydrophobicity(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoMutability(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoPolarizability(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoResidueASA(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoResidueVol(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoSteric(ProteinSequence)

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

Autocorrelation.CalculateGearyAutoTotal(ProteinSequence)

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

Autocorrelation.CalculateMoranAuto(ProteinSequence, AAProperty, AAPropertyName)

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

Autocorrelation.CalculateMoranAutoAvFlexibility(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoFreeEnergy(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoHydrophobicity(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoMutability(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoPolarizability(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoResidueASA(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoResidueVol(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoSteric(ProteinSequence)

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

Autocorrelation.CalculateMoranAutoTotal(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAuto(ProteinSequence, AAProperty, AAPropertyName)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoAvFlexibility(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoFreeEnergy(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoHydrophobicity(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoMutability(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoPolarizability(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoResidueASA(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoResidueVol(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoSteric(ProteinSequence)

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

Autocorrelation.CalculateNormalizedMoreauBrotoAutoTotal(ProteinSequence)

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

Autocorrelation.NormalizeEachAAP(AAP)

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