1. 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(BIBE’03), 2003 Speaker: Ho, Yu An( 何玉安 ) Date: 2004/6/3

2. nmlab 2 Outline Introduction Methodology Experiments and results Conclusion

3. nmlab 3 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.

4. nmlab 4 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

5. nmlab 5 Introduction (3/4) Triosophosphate isomerase protein spots in two different images.

6. nmlab 6 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.

7. nmlab 7 Methodology 1.Determining the position of the protein spot in the source image 2.Defining the region of interest 3.Matching the selected protein spot in the target image 4.Searching for the protein spot in the neighbourhood area 5.Selecting the best matched spot 6.Retrieving 3D structure of a protein

8. nmlab 8 1. Determining the position of the protein spot in the source image (1/3) Source image divided into four quadrants.

9. nmlab 9 1. Determining the position of the protein spot in the source image (2/3)

10. nmlab 10 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.

11. nmlab 11 2. Defining the region of interest (1/2)

12. nmlab 12 2. Defining the region of interest (2/2) (a) A set of points defined by the user, (b) Defining the region of interest.

13. nmlab 13 3. Matching the selected protein spot in the target image

14. nmlab 14 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

15. nmlab 15 4. Searching for the protein spot in the neighbourhood area (2/2)

16. nmlab 16 5. Selecting the best matched spot

17. nmlab 17 Experiments and results 1.Identifying a spot along the line of path 2.Identifying a spot of interest in the target image 3.Matching on 2D gel electrophoresis image 4.Shape comparison 5.Retrieving 3D image

18. nmlab 18 1. Identifying a spot along the line of path (1/2)

19. nmlab 19 1. Identifying a spot along the line of path (2/2) Identifying a spot along the line of path using the low intensity values. threshold

20. nmlab 20 2. Identifying a spot of interest in the target image (1/3)

21. nmlab 21 2. Identifying a spot of interest in the target image (2/3)

22. nmlab 22 2. Identifying a spot of interest in the target image (3/3)

23. nmlab 23 3. Matching on 2D gel electrophoresis image (1/2)

24. nmlab 24 3. Matching on 2D gel electrophoresis image (2/2)

25. nmlab 25 4. Shape comparsion (a)Source spot (b)Detected spot

26. nmlab 26 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

27. nmlab 27 5. Retrieving 3D image (2/3)

28. nmlab 28 5. Retrieving 3D image (3/3)

29. nmlab 29 Conclusion This approach reduces the number of candidate spot to be identified within the image.