現有測定蛋白質三維構形的預測方法依其運用之資訊可分為三代，第一代的方法依據單一殘基之特性來做判斷，第二代的方法加入區域性影響之考量，第三代更融入物種演化同源性之資訊。雖然每一世代預測的準確度都得以提昇，但仍不甚理想。鑑此，我們致力於建立一套協助研究人員判別蛋白質二級結構的電腦協助預測系統（computer-assisted prediction system, CAPS）。期望藉由導入人類的智慧判定能力，再進一步提昇預測的準確度。
　　本研究建立螺旋體之電腦協助預測系統（Helix CAPS），此系統之建構包含了螺旋體資料庫、二元交鎖樹（interlock binary tree）資料表及查詢系統。令使用者輸入所要預測的蛋白質氨基酸序列，電腦輔助預測系統將列出現存於PDB的該氨基酸序列之所有子序列（含螺旋體和非螺旋體）及二元交鎖樹示意圖。
　　Helix CAPS並不像現有的預測方法由電腦程式直接預測蛋白質二級結構，而是提供給使用者預測時所需的相關資訊，協助使用者做預測，期望藉由人類智慧（human intelligence）和專業技術（expertise skill）的融入，來提昇蛋白質螺旋體的預測準確度。

none

[1] Chou, P. Y. and Fasman G. D., “Prediction of protein conformation,” Biochemistry, vol. 13, pp. 222-245, 1974.

[2] Cuff, J. A. and Barton, G. J., “Application of multiple sequence alignment profiles to improve protein secondary structure prediction,” Proteins, vol. 40, pp. 502-511, 2000.

[3] Cuff, J. A. , Clamp, M. E. , Siddiqui, A. S., Finlay, M., and Barton, G. J., “JPred: a consensus secondary structure prediction server,”Bioinformatics, vol. 14, pp. 892 – 893, Nov. 1998.

[4] Frishman, D. and Argos, P., “Seventy-five percent accuracy in protein secondary structure prediction,” Proteins, vol. 27, pp. 329-335, 1997.

[5] Garnier, J., Osguthorpe D. J., and Robson B., “Analysis of the accuracy and implications of simple methods for predicting the secondary structure of globular proteins,” Journal of Molecular Biology, vol. 120, pp. 97-120, 1978.

[6] Gibrat, J. F., Garnier, J., and Robson, B., “Further developments of protein secondary structure prediction using information theory,” Journal of Molecular Biology, vol. 198, pp. 425-443, 1987.

[7] Holly, L. H. and Karplus, M., “Protein secondary structure prediction with a neural network,” Proc Natl. Acad. Sci. USA, vol. 86, pp.152-156, 1989.

[8] Jones, D. T., “Protein secondary structure prediction based on position-specific scoring matrices,” Journal of Molecular Biology, vol. 292, pp. 195-202, 1999.

[9] King, R. D. and Sternberg, M. J. E., “Identification and application of the concepts important for accurate and reliable protein secondary structure prediction,” Protein Science, vol. 5, pp. 2298-2310, 1996.

[10] Levin, J., Robson, B., and Garnier, J., “An algorithm for secondary structure determination in proteins based on sequence similarity,” FEBS Lett., vol. 205, pp. 303-308, 1986.

[11] Lim, V. I., “Structural Principles of the Globular Organization of Protein Chains: A stereochemical Theory of Globular Protein Secondary Structure,” Journal of Molecular Biology, vol. 88, pp. 857-872, 1974.

[12] Rost, B. and Sander C., “Prediction of protein secondary structure at better than 70% accuracy,” Journal of Molecular Biology, vol. 232, pp. 584-599, 1993.

[13] Rost, B., “Review: Protein secondary structure prediction continues to rise,” Journal of Structure Biology, vol. 134, pp. 204-218, 2001.

[14] Salamov, A. A. and Solovyev, V. V., “Prediction of protein secondary structure by combining nearest-neighbor algorithms and multiple sequence alignment,” Journal of Molecular Biology, vol. 247, pp. 11-15, 1995.

[15] Yi, T. M. and Lander, E. S., “Protein Secondary Structure Prediction Using Nearest-neighbor Methods,” Journal of Molecular Biology, vol. 232, pp. 1117-1129, 1993.

[16] Zvelebil, M. J., Barton, G. J., Taylor, W. R., and Sternberg, M, J. E., “Prediction of Protein Secondary Structure and Active Sites using the Alignment of Homologous Sequences,” Journal of Molecular Biology, vol. 195, pp. 957-961, 1987.

[17] 方廷堯，「以蛋白質初級結構做二級結構之電腦輔助預測－所需之結構分類」，碩士論文，國立成功大學製造工程研究所，2001.

[18] 林凡凱，「蛋白質二級結構預測－使用基因演算法」，碩士論文，國立交通大學資訊科學研究所，2002.