A new approach to detect similar proteins from 2D gel electrophoresis images

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A new approach to detect similar proteins from 2D
gel electrophoresis images

• Nawaz Khan and Shahedur Rahman
• Proceedings of the Third IEEE Symposium on
  BioInformations and BioEngineering(BIBE03), 2003
• Speaker Ho, Yu An(???)
• Date 2004/6/3

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Outline

• Introduction
• Methodology
• Experiments and results
• Conclusion

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Introduction (1/4)

• GELLAB system (1981)
• Uses the point pattern comparison.
• MELANIE (1997)
• Compares spot clusters.
• Panek and Vohradsky (1999)
• Use the information from the neighbourhood spots
  for comparison.

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Introduction (2/4)

• Although the spot in the source and target image
  can be identical or similar, but still the
  following parameters can very
• Background value
• Protein spot intensity
• Protein spot shape
• Noise in the image

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Introduction (3/4)
Triosophosphate isomerase protein spots in two
different images.
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Introduction (4/4)

• This paper presents a novel approach for
  identifying the identical or similar protein spot
  in 2D gel electrophoresis images by considering
  the following factors
• 2D gel electrophoresis protein spots differ
  significantly in two different images even when
  they represent the same protein.
• Same or similar protein spots will lie at the
  same line of path because of their
  electrophoresis mobility and molecular weight.
• The intensity of the matched regions in both
  images can be different even thought it shows a
  correct matching.
• The region of similar spot at the target image
  must lie at the same or different directional
  vector on the line of path.

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Methodology

• Determining the position of the protein spot in
  the source image
• Defining the region of interest
• Matching the selected protein spot in the target
  image
• Searching for the protein spot in the
  neighbourhood area
• Selecting the best matched spot
• Retrieving 3D structure of a protein

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1. Determining the position of the protein spot
in the source image (1/3)
Source image divided into four quadrants.
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1. Determining the position of the protein spot
in the source image (2/3)
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1. Determining the position of the protein spot
in the source image (3/3)
Angle produced with the horizontal axis for any
point of interest on the vertical plane.
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2. Defining the region of interest (1/2)
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2. Defining the region of interest (2/2)
(a) A set of points defined by the user, (b)
Defining the region of interest.
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3. Matching the selected protein spot in the
target image
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4. Searching for the protein spot in the
neighbourhood area (1/2)
Non emptied straight line of path in the target
image to determine the neighbourhood protein spot
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4. Searching for the protein spot in the
neighbourhood area (2/2)
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5. Selecting the best matched spot
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Experiments and results

• Identifying a spot along the line of path
• Identifying a spot of interest in the target
  image
• Matching on 2D gel electrophoresis image
• Shape comparison
• Retrieving 3D image

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1. Identifying a spot along the line of path (1/2)
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1. Identifying a spot along the line of path (2/2)
threshold
Identifying a spot along the line of path using
the low intensity values.
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2. Identifying a spot of interest in the target
image (1/3)
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2. Identifying a spot of interest in the target
image (2/3)
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2. Identifying a spot of interest in the target
image (3/3)
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3. Matching on 2D gel electrophoresis image (1/2)
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3. Matching on 2D gel electrophoresis image (2/2)
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4. Shape comparsion

• Source spot
• Detected spot

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5. Retrieving 3D image (1/3)

• The following parameters are stored in the target
  specific dedicated database
• Coordinates
• Intensity values
• Positional orientation
• Average shape radius

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5. Retrieving 3D image (2/3)
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5. Retrieving 3D image (3/3)
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Conclusion

• This approach reduces the number of candidate
  spot to be identified within the image.