Presentation on Spot Characterization in Proteomics

7/29/2019 Presentation on Spot Characterization in Proteomics

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Spot Characterization in Proteomics

andJet Analysis in Heavy Ion Collision

B.Tech. Project Stage 1 Presentation

Nikhil Prakash 09026015

Department Of Physics,IIT Bombay

November 28,2012


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Outline

Proteomics Introduction

Heavy Ion Collisions

Wavelet Neural Networks Mathematical Morphology

Conclusions


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Proteomics

Protein + Genome = Proteome

Total Number of Proteins in a Cell at a given

Time are called Proteome.

Analysis of this Proteome Proteomics.

Analysis includes Identification and

Sequencing of Proteins.


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Two Dimensional Electrophoresis Gel Image

Used as Separation Tool of Proteins inProteomics.

Separation Parameters Used

Molecular Mass

Isoelectric Point

Contains 2000+ Protein Spots

Digital Analysis of these gels are used forIdentification of the Protein Spots


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Principle of Two-Dimensional

Gel Electrophoresis :

A Extraction Of ProteinsB1 Sample Loaded on pH

Gradient

B2 Sample is Neutralized

C Strip is then Equilibrated in a

SDS(sodium dodecyl sulfate)

D This is then loaded on top of a

SDS PAGE (Polyacrylamide Gel

Electrophoresis) gel and Proteins

gets separated on the basis oftheir molecular masses.

Image from [1]


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A Typical Two Dimensional Electrophoresis Image (2DGE)

with red circles showing few Protein Spots

Image Courtesy: http://www.pierroton.inra.fr/genetics/2D/


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A Typical Protein Spot in 2DGE Image


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Challenges in 2DGE Image Analysis

Background contains Horizontal and Vertical

Streaks and is highly varying.

Faint and Weak Protein Spots

Overlapping Spots


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Heavy Ion Collisions

It is proposed that a Hot, Dense medium

Quark Gluon Plasma is Formed in Relativistic

Heavy Ion Collisions.[8] QGP Consists of Elementary Particles.

QGP Transitions are probed to Understand the

Dynamics of the Universe.


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http://en.wikipedia.org/wiki/File:Standard_Model_of_Elementary_Particles.svg


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Jet Analysis

In QGP, Particle like Hadrons cannot exist inFree Form.

Become Clusters of Particles known as Jets

Energy and Momentum of these Jets areCorrelated.

Clustering Algorithms are Used to Study these

Jets. Analyzing these Clusters are sub-images in the

whole Detected Image


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Jets Detected by ALICE(A Large Ion Collider Experiment)

Image from :

http://news.discovery.com/space/in-the-beginning-the-universe-was-a-liquid.html


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Wavelet Neural Networks

Feed-Forward (1+1/2) Architecture Network.

Hidden Layer Activation Functions derived

from Orthonormal Wavelet Family.

Proved to be Best Estimators for Learning

Dynamic Systems[14][15]


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A Typical Wavelet Neural Network


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WNN Learning

Wavelet Network is Defined as

Parameters are Learned by followingEquations:


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Mathematical Morphology

Set Method of Image Analysis to get

Quantitative Description of Geometrical

Structures developed by Serra[20] and

Matheron[21]

Tool for Extracting Useful Knowledge from the

Image.

Generally, Used for Binary Images but recently

Extended for Gray-Scale Images


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Structuring Element (SE)

Basic sub-image used in MathematicalMorphology to Probe the Image.

Structuring Elements with circled pixels as Origin


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Basic Operations in MM

Operations are based on Expanding and

Shrinking the Images.

Basic Operation Dilation

Erosion


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Dilation

Dilation can be viewed as a set of locus of theall points covered by center of the structuring

element B in the image set A.

Mathematically, Dilation is defined as


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Image A is dilated by Structuring Element B

Image from [22]


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Erosion

Erosion can be viewed as a set of locus of the

points of the origin of structuring element

covered by the B inside the image set A.

Mathematically, Erosion is defined as


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Image A is eroded by Structuring Element B

Image from [22]


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Hit and Miss Transformation

Hit and Miss Transformation(HMT) extractsthe information of a particular shape in theImage.

Uses Two SEs For Matching Foreground of the Shape

For Matching Background of the Shape

Mathematically, HMT is defined as

or


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Position of Subset D is Extracted

in Image using Hit and Miss

Transformation [22]


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Pattern Matching using HMT and WNN

Modeling the Structuring Elements using

WNNs for detecting the sub-images

Using these SEs, detecting the patterns in the

Image.

A Similar Technique is used for Detecting Stars

from the Astronomical Data


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Structuring Elements used in detection of Stars in Low Brightness Galaxies

Image Courtesy:

http://www.sciencedirect.com/science/article/pii/S003132030900082X


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Conclusions

From the Success of detection of Stars from

Astronomical data, We can say that the

technique will work in Proteomics as Spots in

2DGE Image and Stars in Galaxies have similardifficulties in Analysis.


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Thank You


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References

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Presentation on Spot Characterization in Proteomics

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