An Algorithm for Separating Overlapped Protein Spots Based on Valley Characteristics_Journal of Biomedical Engineering

Authors：

OUQiaofeng ^1,2 , ZHANGHuisheng ¹ ,  XIONGBangshu ²

1. School of Electronic Information, Northwestern Polytechnical University, Xi'an 710072, China;
2. Key Laboratory of Image Processing and Pattern Recognition of Jiangxi Province, Nanchang Hangkong University, Nanchang 330063, China;

Corresponding author：

XIONGBangshu, Email: xiongbs@126.com

Keywords：

two-dimensional gel ectrophoresis image; separation of overlapped protein spots; valley characteristics

DOI：

10.7507/1001-5515.20140191

Video：

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Abstract Full text Figures/Tables Video References Cited by

To separate the overlapped protein spots in two-dimensional gel electrophoresis (2-DE) images, we proposed an auto-separating algorithm based on valley characteristics. Firstly, the marker-controlled watershed algorithm was used to detect the initial outlines of the object regions. Secondly, medial axis transform and hierarchical branch pruning method were applied to the main skeletons of the object regions, and each main skeleton was fitted into line segments to describe the overlap directions. Then, the 3-dimensional model of the object region was scanned on the normal planes of the line segments to find the valley locations. And finally, a validation model was adopted to construct separation lines. The experiments on 2 real scanned 2-DE images showed that the true overlap separate (TOSs) were 78.95% and 85.71%, respectively. The results indicated that the proposed algorithm was better than the existing algorithms and could be used in engineering practice.

Citation： OUQiaofeng, ZHANGHuisheng, XIONGBangshu. An Algorithm for Separating Overlapped Protein Spots Based on Valley Characteristics. Journal of Biomedical Engineering, 2014, 31(5): 1018-1022. doi: 10.7507/1001-5515.20140191 Copy

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7.	PLEISSNER K P, HOFFMANN F, KRIEGEL K, et al. New algorithmic approaches to protein spot detection and pattern matching in two-dimensional electrophoresis gel databases[J]. Electrophoresis, 1999, 20(4-5): 755-765.
8.	PEER P, CORZO L G. Local pixel value collection algorithm for spot segmentation in two-dimensional gel electrophoresis research[J]. Comp Funct Genomics, 2007, 7(1): 89596.
9.	SRINARK T, KAMBHAMETTU C. An image analysis suite for spot detection and spot matching in two-dimensional electrophoresis gels[J]. Electrophoresis, 2008, 29(3): 706-715.
10.	RASHWAN S, FAHEEM T, SARHAN A. A fuzzy-watershed based algorithm for protein spot detection in 2DGE images[J]. International Journal of Computer Science and Network Security, 2010, 10(5): 254-260.
11.	SUN C L, WANG X M. Spot segmentation and verification based on improve marker controlled watershed transform[C]//IEEE Conference on Computer Science and Information Technology, Chengdu: 2010: 63-66.
12.	SCHLAGS W, WALTHER M, MASREE M, et al. Towards validating a method for two-dimensional electrophoresis/Silver staining[J]. Electrophoresis, 2005, 26(12): 2461-2469.
13.	RAMAN B, CHEUNG A, MARTEN M R. Quantitative comparison and evaluation of two commercially available, two-dimensional electrophoresis image analysis software packages, Z3 and Melanie[J]. Electrophoresis, 2002, 23(14): 2194-2202.

1. RABILLOUD T, CHEVALLET M, LUCHE S, et al. Two-dimensional gel electrophoresis in proteomics: Past, present and future[J]. J Proteomics, 2010, 73(11): 2064-2077.
2. ZELLNER M, GRAF A, ZEHETMAYER S, et al. How many spots with missing values can be tolerated in quantitative two-dimensional gel electrophoresis when applying univariate statistics?[J]. J Proteomics, 2012, 75(6): 1792-1802.
3. DOWSEY A W, DUNN M J, YANG Z G, et al. The role of bioinformatics in two-dimensional gel electrophoresis[J]. Proteomics, 2003, 3(8): 1567-1596.
4. DASZYKOWSKI M, STANIMIROVA I, BODZON-KULAKOWSKA A, et al. Start-to-end processing of two-dimensional gel electrophoretic images[J]. J Chromatogr A, 2007, 1158(1-2): 306-317.
5. HE F, XIONG B S, SUN C L. A laplacian of Gaussian-Based approach for spot detection in two images[C]//CCTA 2010, Part IV, IFIP AICT 347 proceedings, Nanchang: 2011: 8-15.
6. MORRIS J S, CLARK B N, GUTSTEIN H B. Pinnacle: a fast, automatic and accurate method for detecting and quantifying protein spots in 2-dimensional gel electrophoresis data[J]. Bioinformatics, 2008, 24(4): 529-536.
7. PLEISSNER K P, HOFFMANN F, KRIEGEL K, et al. New algorithmic approaches to protein spot detection and pattern matching in two-dimensional electrophoresis gel databases[J]. Electrophoresis, 1999, 20(4-5): 755-765.
8. PEER P, CORZO L G. Local pixel value collection algorithm for spot segmentation in two-dimensional gel electrophoresis research[J]. Comp Funct Genomics, 2007, 7(1): 89596.
9. SRINARK T, KAMBHAMETTU C. An image analysis suite for spot detection and spot matching in two-dimensional electrophoresis gels[J]. Electrophoresis, 2008, 29(3): 706-715.
10. RASHWAN S, FAHEEM T, SARHAN A. A fuzzy-watershed based algorithm for protein spot detection in 2DGE images[J]. International Journal of Computer Science and Network Security, 2010, 10(5): 254-260.
11. SUN C L, WANG X M. Spot segmentation and verification based on improve marker controlled watershed transform[C]//IEEE Conference on Computer Science and Information Technology, Chengdu: 2010: 63-66.
12. SCHLAGS W, WALTHER M, MASREE M, et al. Towards validating a method for two-dimensional electrophoresis/Silver staining[J]. Electrophoresis, 2005, 26(12): 2461-2469.
13. RAMAN B, CHEUNG A, MARTEN M R. Quantitative comparison and evaluation of two commercially available, two-dimensional electrophoresis image analysis software packages, Z3 and Melanie[J]. Electrophoresis, 2002, 23(14): 2194-2202.

Journal of Biomedical Engineering

An Algorithm for Separating Overlapped Protein Spots Based on Valley Characteristics

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