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Advanced Protein Structure Analysis Research

Develop an automatic system to generate input dataset for protein structure analysis. Apply clustering algorithms and visualization techniques. Explore collaboration possibilities for comprehensive structural analysis.

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Advanced Protein Structure Analysis Research

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  1. Research Topics Dr. Bernard Chen Ph.D. University of Central Arkansas Fall 2010

  2. FutureWorks

  3. Part 1 • Forming the protein sequence to structure dataset for analyzing the hidden information • Develop a automatic system to generate original input dataset with various window size • The dataset includes all research required information (Primary sequence, 2nd structure and 3D structure information) • (apply K-means clustering on the dataset) • Difficulty: 2*~3*

  4. Part 5 • Structural Motif Visualization • Given a set of distances, draw a corresponding 3D structure • This may help all parts of my research • Difficulty: 2*

  5. Part 2 • Forming Information Granules by High performance Fuzzy C-means clustering with Chou-Fasman parameter • Forming information granule via Fuzzy C-means • Combine the information of Chou-Fasman parameter, this will end up 180+27 dimensions • High performance computing is required • Difficulty: 3*

  6. Part 4 • Multi-Level Positional Association Rule • Combine the idea of Super-Rule-Tree (SRT) structure to solve the problem caused by fixed window size • Difficulty: 3*~4*

  7. Part 4 • Distance Association Rule Algorithm

  8. Part 3 and 5 • Decision Tree for (1) protein sequence motifs extraction and (2) local tertiary structure prediction • Difficulty: 4*~5*

  9. New Area • Collaboration with Dr. Young: system talks between primary sequence, 2nd structure, and 3D structure • Difficulty: 2*~5*

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