{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:11:31Z","timestamp":1772554291154,"version":"3.50.1"},"publisher-location":"Berlin, Heidelberg","reference-count":30,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783540720300","type":"print"},{"value":"9783540720317","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/978-3-540-72031-7_54","type":"book-chapter","created":{"date-parts":[[2007,8,5]],"date-time":"2007-08-05T14:16:24Z","timestamp":1186323384000},"page":"590-600","source":"Crossref","is-referenced-by-count":1,"title":["A Feature Selection Algorithm Based on Graph Theory and Random Forests for Protein Secondary Structure Prediction"],"prefix":"10.1007","author":[{"given":"Gulsah","family":"Altun","sequence":"first","affiliation":[]},{"given":"Hae-Jin","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Stefan","family":"Gremalschi","sequence":"additional","affiliation":[]},{"given":"Robert W.","family":"Harrison","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Pan","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"17","key":"54_CR1","doi-asserted-by":"publisher","first-page":"3389","DOI":"10.1093\/nar\/25.17.3389","volume":"25","author":"S.F. Altschul","year":"1997","unstructured":"Altschul, S.F., et al.: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research\u00a025(17), 3389\u20133402 (1997)","journal-title":"Nucleic Acids Research"},{"key":"54_CR2","doi-asserted-by":"crossref","unstructured":"Altun, G., et al.: Hybrid SVM kernels for protein secondary structure prediction. In: Proc. IEEE Intl Conf. on Granular Computing (GRC 2006), pp. 762\u2013765 (2006)","DOI":"10.1109\/GRC.2006.1635912"},{"key":"54_CR3","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1186\/1471-2105-7-178","volume":"7","author":"Z. Aydin","year":"2006","unstructured":"Aydin, Z., Altunbasak, Y., Borodovsky, M.: Protein secondary structure prediction for a single-sequence using hidden semi-Markov models. BMC Bioinformatics\u00a07, 178 (2006)","journal-title":"BMC Bioinformatics"},{"key":"54_CR4","unstructured":"Berman, H., et al.: The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB Data."},{"issue":"21","key":"54_CR5","doi-asserted-by":"publisher","first-page":"2628","DOI":"10.1093\/bioinformatics\/btl453","volume":"22","author":"F. Birzele","year":"2006","unstructured":"Birzele, F., Kramer, S.: A new representation for protein secondary structure prediction based on frequent patterns. Bioinformatics\u00a022(21), 2628\u20132634 (2006)","journal-title":"Bioinformatics"},{"key":"54_CR6","doi-asserted-by":"crossref","unstructured":"Butenko, S., Wilhelm, W.: Clique-detection models in computational biochemistry and genomics. European Journal of Operational Research, To appear (2006), Available online at \n                  \n                    http:\/\/www.sciencedirect.com\/","DOI":"10.1016\/j.ejor.2005.05.026"},{"key":"54_CR7","first-page":"15","volume":"45","author":"L. Breiman","year":"2001","unstructured":"Breiman, L.: Random Forests. Machine Learning\u00a045, 15\u201332 (2001)","journal-title":"Machine Learning"},{"key":"54_CR8","unstructured":"Breiman, L., Cutler, A.: Random Forest, \n                  \n                    http:\/\/www.stat.berkeley.edu\/~breiman\/RandomForests\/cc_software.htm"},{"key":"54_CR9","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1006\/jmbi.2000.3837","volume":"301","author":"C. Bystroff","year":"2000","unstructured":"Bystroff, C., Thorsson, V., Baker, D.: HMMSTR: a Hidden Markov Model for Local Sequence Structure Correlations in Proteins. J. Mol. Biol.\u00a0301, 173\u2013190 (2000)","journal-title":"J. Mol. Biol."},{"issue":"2","key":"54_CR10","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1021\/bi00699a002","volume":"13","author":"P.Y. Chou","year":"1974","unstructured":"Chou, P.Y., Fasman, G.D.: Prediction of protein conformation. Biochemistry\u00a013(2), 222\u2013245 (1974)","journal-title":"Biochemistry"},{"key":"54_CR11","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-4541-9","volume-title":"An Introduction to the Bootstrap","author":"B. Efron","year":"1993","unstructured":"Efron, B., Tibshirani, R.: An Introduction to the Bootstrap. Chapman and Hall, New York (1993)"},{"key":"54_CR12","doi-asserted-by":"publisher","first-page":"1829","DOI":"10.1110\/ps.062305106","volume":"15","author":"P.J. Fleming","year":"2006","unstructured":"Fleming, P.J., Gong, H., Rose, G.D.: Secondary structure determines protein topology. Protein Science\u00a015, 1829\u20131834 (2006)","journal-title":"Protein Science"},{"key":"54_CR13","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/0022-2836(78)90297-8","volume":"120","author":"J. Garnier","year":"1978","unstructured":"Garnier, J., Osguthorpe, D.J., Robson, B.: Analysis of the accuracy and implications of simple methods for predicting the secondary structure of globular proteins. J. Mol. Biol.\u00a0120, 97\u2013120 (1978)","journal-title":"J. Mol. Biol."},{"key":"54_CR14","doi-asserted-by":"publisher","first-page":"10915","DOI":"10.1073\/pnas.89.22.10915","volume":"89","author":"S. Henikoff","year":"1992","unstructured":"Henikoff, S., Henikoff, J.G.: Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci.\u00a089, 10915\u201310919 (1992)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"54_CR15","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1109\/TNB.2004.837906","volume":"3","author":"H. Hu","year":"2004","unstructured":"Hu, H., et al.: Improved protein secondary structure prediction using support vector machine with a new encoding scheme and an advanced tertiary classifier. IEEE Trans. NanoBiosci.\u00a03, 265 (2004)","journal-title":"IEEE Trans. NanoBiosci."},{"key":"54_CR16","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1006\/jmbi.2001.4580","volume":"308","author":"S. Hua","year":"2001","unstructured":"Hua, S., Sun, Z.: A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach. J. Mol. Biol\u00a0308, 397\u2013407 (2001)","journal-title":"J. Mol. Biol"},{"key":"54_CR17","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1006\/jmbi.1999.3091","volume":"292","author":"D.T. Jones","year":"1999","unstructured":"Jones, D.T.: Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol.\u00a0292, 195\u2013202 (1999)","journal-title":"J. Mol. Biol."},{"issue":"3","key":"54_CR18","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1002\/prot.21036","volume":"64","author":"G. Karypis","year":"2006","unstructured":"Karypis, G.: YASSPP: better kernels and coding schemes lead to improvements in protein secondary structure prediction. Proteins\u00a064(3), 575\u2013586 (2006)","journal-title":"Proteins"},{"key":"54_CR19","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1002\/prot.10181","volume":"49","author":"A. Kloczkowski","year":"2002","unstructured":"Kloczkowski, A., et al.: Combining the GOR V algorithm with evolutionary information for protein secondary structure prediction from amino acid sequence. Proteins\u00a049, 154\u2013166 (2002)","journal-title":"Proteins"},{"key":"54_CR20","doi-asserted-by":"crossref","unstructured":"Kim, H., Park, H.: Protein Secondary Structure based on an improved support vector machines approach. Protein Eng. (2003)","DOI":"10.1093\/protein\/gzg072"},{"key":"54_CR21","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1007\/11510888_33","volume-title":"Machine Learning and Data Mining in Pattern Recognition","author":"L. Kurgan","year":"2005","unstructured":"Kurgan, L., Homaeian, L.: Prediction of Secondary Protein Structure Content from Primary Sequence Alone-A Feature Selection Based Approach. In: Perner, P., Imiya, A. (eds.) MLDM 2005. LNCS (LNAI), vol.\u00a03587, pp. 334\u2013345. Springer, Heidelberg (2005)"},{"key":"54_CR22","unstructured":"Niskanen, S., \u00d6sterg\u00e5rd, P.R.J.: Cliquer User\u2019s Guide, Version 1.0. Communications Laboratory, Helsinki University of Technology, Espoo, Finland, Tech. Rep. T48 (2003)"},{"issue":"1-3","key":"54_CR23","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/S0166-218X(01)00290-6","volume":"120","author":"P.R.J. \u00d6sterg\u00e5rd","year":"2002","unstructured":"\u00d6sterg\u00e5rd, P.R.J.: A fast algorithm for the maximum clique problem. Discrete Applied Mathematics\u00a0120(1-3), 197\u2013207 (2002)","journal-title":"Discrete Applied Mathematics"},{"key":"54_CR24","doi-asserted-by":"publisher","first-page":"672","DOI":"10.1038\/10728","volume":"6","author":"T. Przytycka","year":"1999","unstructured":"Przytycka, T., Aurora, R., Rose, G.D.: A protein taxonomy based on secondary structure. Nature Structural Biol.\u00a06, 672\u2013682 (1999)","journal-title":"Nature Structural Biol."},{"key":"54_CR25","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1002\/prot.10029","volume":"46","author":"D. Przybylski","year":"2002","unstructured":"Przybylski, D., Rost, B.: Alignments grow, secondary structure prediction improves. Proteins\u00a046, 197\u2013205 (2002)","journal-title":"Proteins"},{"key":"54_CR26","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1201\/9780203911327.ch8","volume-title":"Protein structure determination, analysis, and modeling for drug discovery","author":"B. Rost","year":"2003","unstructured":"Rost, B.: Rising accuracy of protein secondary structure prediction. In: Chasman, D. (ed.) Protein structure determination, analysis, and modeling for drug discovery, pp. 207\u2013249. Dekker, New York (2003)"},{"key":"54_CR27","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1006\/jmbi.1993.1413","volume":"232","author":"B. Rost","year":"1993","unstructured":"Rost, B., Sander, C.: Prediction of protein secondary structure at better than 70% accuracy. J. Mol. Biol.\u00a0232, 584\u2013599 (1993)","journal-title":"J. Mol. Biol."},{"key":"54_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1007\/3-540-44989-2_137","volume-title":"Artificial Neural Networks and Neural Information Processing - ICANN\/ICONIP 2003","author":"S.Y.M. Shi","year":"2003","unstructured":"Shi, S.Y.M., Suganthan, P.N.: Feature Analysis and Classification of Protein Secondary Structure Data. In: Kaynak, O., et al. (eds.) ICANN 2003 and ICONIP 2003. LNCS, vol.\u00a02714, pp. 1151\u20131158. Springer, Heidelberg (2003)"},{"key":"54_CR29","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1186\/1471-2105-7-319","volume":"7","author":"C.-T. Su","year":"2006","unstructured":"Su, C.-T., Chen, C.-Y., Ou, Y.-Y.: Protein disorder prediction by condensed PSSM considering propensity for order or disorder. BMC Bioinformatics\u00a07, 319 (2006)","journal-title":"BMC Bioinformatics"},{"key":"54_CR30","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1142\/S0219633602000117","volume":"1","author":"S. Vishveshwara","year":"2002","unstructured":"Vishveshwara, S., Brinda, K.V., Kannan, N.: Protein Structure: Insights from Graph Theory. J. Th. Comp. Chem.\u00a01, 187\u2013211 (2002)","journal-title":"J. Th. Comp. Chem."}],"container-title":["Lecture Notes in Computer Science","Bioinformatics Research and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-72031-7_54.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,19]],"date-time":"2020-11-19T05:28:14Z","timestamp":1605763694000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-72031-7_54"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9783540720300","9783540720317"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-72031-7_54","relation":{},"subject":[]}}