{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:14:20Z","timestamp":1763468060891},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"S7","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity\/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity\/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity\/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis-ContSHC regularizes an existing dissimilarity measure <jats:italic>d<\/jats:italic>\n              <jats:sub>\n                <jats:italic>ij<\/jats:italic>\n              <\/jats:sub> by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (<jats:italic>i<\/jats:italic>, <jats:italic>j<\/jats:italic>), if their context <jats:inline-formula>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mi>N<\/mml:mi>\n                  <mml:mrow>\n                    <mml:mo>(<\/mml:mo>\n                    <mml:mrow>\n                      <mml:mi>i<\/mml:mi>\n                    <\/mml:mrow>\n                    <mml:mo>)<\/mml:mo>\n                  <\/mml:mrow>\n                <\/mml:math>\n              <\/jats:inline-formula> and <jats:inline-formula>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mi>N<\/mml:mi>\n                  <mml:mrow>\n                    <mml:mo>(<\/mml:mo>\n                    <mml:mrow>\n                      <mml:mi>j<\/mml:mi>\n                    <\/mml:mrow>\n                    <mml:mo>)<\/mml:mo>\n                  <\/mml:mrow>\n                <\/mml:math>\n              <\/jats:inline-formula> is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing <jats:italic>d<\/jats:italic>\n              <jats:sub>\n                <jats:italic>ij<\/jats:italic>\n              <\/jats:sub> by a factor learned from the context <jats:inline-formula>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mi>N<\/mml:mi>\n                  <mml:mrow>\n                    <mml:mo>(<\/mml:mo>\n                    <mml:mrow>\n                      <mml:mi>i<\/mml:mi>\n                    <\/mml:mrow>\n                    <mml:mo>)<\/mml:mo>\n                  <\/mml:mrow>\n                <\/mml:math>\n              <\/jats:inline-formula> and <jats:inline-formula>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mi>N<\/mml:mi>\n                  <mml:mrow>\n                    <mml:mo>(<\/mml:mo>\n                    <mml:mrow>\n                      <mml:mi>j<\/mml:mi>\n                    <\/mml:mrow>\n                    <mml:mo>)<\/mml:mo>\n                  <\/mml:mrow>\n                <\/mml:math>\n              <\/jats:inline-formula>.<\/jats:p>\n            <jats:p>Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new <jats:bold>S<\/jats:bold> upervised learned <jats:bold>Dis<\/jats:bold> similarity measure, we update the <jats:bold>Pro<\/jats:bold> tein <jats:bold>H<\/jats:bold> ierarchial <jats:bold>Cont<\/jats:bold> ext <jats:bold>C<\/jats:bold> oherently in an iterative algorithm--<jats:bold>ProDis-ContSHC<\/jats:bold>.<\/jats:p>\n            <jats:p>We test the performance of ProDis-ContSHC on two benchmark sets, i.e., the ASTRAL 1.73 database and the FSSP\/DALI database. Experimental results demonstrate that plugging our supervised contextual dissimilarity measures into the retrieval systems significantly outperforms the context-free dissimilarity\/similarity measures and other unsupervised contextual dissimilarity measures that do not use the class label information.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Using the contextual proteins with their class labels in the database, we can improve the accuracy of the pairwise dissimilarity\/similarity measures dramatically for the protein retrieval tasks. In this work, for the first time, we propose the idea of supervised contextual dissimilarity learning, resulting in the ProDis-ContSHC algorithm. Among different contextual dissimilarity learning approaches that can be used to compare a pair of proteins, ProDis-ContSHC provides the highest accuracy. Finally, ProDis-ContSHC compares favorably with other methods reported in the recent literature.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-13-s7-s2","type":"journal-article","created":{"date-parts":[[2012,5,8]],"date-time":"2012-05-08T12:32:02Z","timestamp":1336480322000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval"],"prefix":"10.1186","volume":"13","author":[{"given":"Jingyan","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quanquan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongping","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,5,8]]},"reference":[{"key":"5155_CR1","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1186\/1471-2105-11-536","volume":"11","author":"SA Chen","year":"2010","unstructured":"Chen SA, Lee TY, Ou YY: Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins. BMC Bioinformatics 2010, 11: 536. 10.1186\/1471-2105-11-536","journal-title":"BMC Bioinformatics"},{"key":"5155_CR2","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1186\/1471-2105-11-313","volume":"11","author":"B Sobolev","year":"2010","unstructured":"Sobolev B, Filimonov D, Lagunin A, Zakharov A, Koborova O, Kel A, Poroikov V: Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates. BMC Bioinformatics 2010, 11: 313. 10.1186\/1471-2105-11-313","journal-title":"BMC Bioinformatics"},{"key":"5155_CR3","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1186\/1471-2105-11-428","volume":"11","author":"A Albayrak","year":"2010","unstructured":"Albayrak A, Otu HH, Sezerman UO: Clustering of protein families into functional subtypes using Relative Complexity Measure with reduced amino acid alphabets. BMC Bioinformatics 2010, 11: 428. 10.1186\/1471-2105-11-428","journal-title":"BMC Bioinformatics"},{"issue":"3","key":"5155_CR4","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1093\/bib\/bbp021","volume":"10","author":"L Ezkurdia","year":"2009","unstructured":"Ezkurdia L, Bartoli L, Fariselli P, Casadio R, Valencia A, Tress ML: Progress and challenges in predicting protein-protein interaction sites. Brief Bioinform 2009, 10(3):233\u2013246.","journal-title":"Brief Bioinform"},{"issue":"3","key":"5155_CR5","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1016\/j.patcog.2009.08.012","volume":"43","author":"T Cook","year":"2010","unstructured":"Cook T, Sutton R, Buckley K: Automated flexion crease identification using internal image seams. Pattern Recognition 2010, 43(3):630\u2013635. 10.1016\/j.patcog.2009.08.012","journal-title":"Pattern Recognition"},{"issue":"7","key":"5155_CR6","doi-asserted-by":"publisher","first-page":"e119","DOI":"10.1371\/journal.pcbi.0030119","volume":"3","author":"Y Ofran","year":"2007","unstructured":"Ofran Y, Rost B: Protein-protein interaction hotspots carved into sequences. PLoS Comput Biol 2007, 3(7):e119. 10.1371\/journal.pcbi.0030119","journal-title":"PLoS Comput Biol"},{"issue":"21","key":"5155_CR7","doi-asserted-by":"publisher","first-page":"2744","DOI":"10.1093\/bioinformatics\/btq510","volume":"26","author":"ZH Yhou","year":"2010","unstructured":"Yhou ZH, Lei YK, Gui J, Huang DS, Zhou X: Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data. Bioinformatics 2010, 26(21):2744\u20132751. 10.1093\/bioinformatics\/btq510","journal-title":"Bioinformatics"},{"key":"5155_CR8","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1186\/1471-2105-11-174","volume":"11","author":"JF Xia","year":"2010","unstructured":"Xia JF, Zhao XM, Song J, Huang DS: APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility. BMC Bioinformatics 2010, 11: 174. 10.1186\/1471-2105-11-174","journal-title":"BMC Bioinformatics"},{"key":"5155_CR9","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1186\/1471-2105-11-343","volume":"11","author":"ZH Yhou","year":"2010","unstructured":"Yhou ZH, Yin Z, Han K, Huang DS, Zhou X: A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network. BMC Bioinformatics 2010, 11: 343. 10.1186\/1471-2105-11-343","journal-title":"BMC Bioinformatics"},{"issue":"5","key":"5155_CR10","doi-asserted-by":"publisher","first-page":"1595","DOI":"10.1007\/s00726-010-0588-1","volume":"39","author":"JF Xia","year":"2010","unstructured":"Xia JF, Zhao XM, Huang DS: Predicting protein-protein interactions from protein sequences using meta predictor. Amino Acids 2010, 39(5):1595\u20131599. 10.1007\/s00726-010-0588-1","journal-title":"Amino Acids"},{"issue":"3","key":"5155_CR11","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1007\/s00726-009-0295-y","volume":"38","author":"MG Shi","year":"2010","unstructured":"Shi MG, Xia JF, Li XL, Huang DS: Predicting protein-protein interactions from sequence using correlation coefficient and high-quality interaction dataset. Amino Acids 2010, 38(3):891\u2013899. 10.1007\/s00726-009-0295-y","journal-title":"Amino Acids"},{"issue":"12","key":"5155_CR12","doi-asserted-by":"publisher","first-page":"2293","DOI":"10.1016\/j.patcog.2005.11.012","volume":"39","author":"DS Huang","year":"2006","unstructured":"Huang DS, Zhao XM, Huang GB, Cheung YM: Classifying protein sequences using hydropathy blocks. Pattern Recognition 2006, 39(12):2293\u20132300. 10.1016\/j.patcog.2005.11.012","journal-title":"Pattern Recognition"},{"key":"5155_CR13","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.ijbiomac.2006.02.024","volume":"38","author":"JJ Li","year":"2006","unstructured":"Li JJ, Huang DS, Wang B, Chen P: Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores. Int J Biol Macromol 2006, 38: 241\u2013247. 10.1016\/j.ijbiomac.2006.02.024","journal-title":"Int J Biol Macromol"},{"issue":"2","key":"5155_CR14","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1016\/j.febslet.2005.11.081","volume":"580","author":"B Wang","year":"2006","unstructured":"Wang B, Chen P, Huang DS, Li JJ, Lok TM, Lyu MR: Predicting protein interaction sites from residue spatial sequence profile and evolution rate. FEBS Lett 2006, 580(2):380\u2013384. 10.1016\/j.febslet.2005.11.081","journal-title":"FEBS Lett"},{"key":"5155_CR15","first-page":"1","volume-title":"2011 5th International Conference on Bioinformatics and Biomedical Engineering, (iCBBE).","author":"J Wang","year":"2011","unstructured":"Wang J, Li Y, Zhang Y, Tang N, Wang C: Class conditional distance metric for 3D protein structure classification. 2011 5th International Conference on Bioinformatics and Biomedical Engineering, (iCBBE). 2011, 1\u20134."},{"issue":"3","key":"5155_CR16","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1142\/S0218194005002439","volume":"15","author":"PH Chi","year":"2005","unstructured":"Chi PH, Scott G, Shyu CR: A fast protein structure retrieval system using image-based distance matrices and multidimensional index. International Journal of Software Engineering and Knowledge Engineering 2005, 15(3):527\u2013545. 10.1142\/S0218194005002439","journal-title":"International Journal of Software Engineering and Knowledge Engineering"},{"key":"5155_CR17","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s10115-007-0088-0","volume":"14","author":"K Marsolo","year":"2008","unstructured":"Marsolo K, Parthasarathy S: On the use of structure and sequence-based features for protein classification and retrieval. Knowledge and Information Systems 2008, 14: 59\u201380. 10.1007\/s10115-007-0088-0","journal-title":"Knowledge and Information Systems"},{"issue":"7","key":"5155_CR18","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1093\/bioinformatics\/bth036","volume":"20","author":"Z Aung","year":"2004","unstructured":"Aung Z, Tan K: Rapid 3D protein structure database searching using information retrieval techniques. Bioinformatics 2004, 20(7):1045\u20131052. 10.1093\/bioinformatics\/bth036","journal-title":"Bioinformatics"},{"issue":"3","key":"5155_CR19","doi-asserted-by":"publisher","first-page":"2758","DOI":"10.1016\/j.eswa.2010.08.066","volume":"38","author":"W Zhang","year":"2011","unstructured":"Zhang W, Yoshida T, Tang X: A comparative study of TF*IDF, LSI and multi-words for text classification. Expert Syst Appl 2011, 38(3):2758\u20132765. 10.1016\/j.eswa.2010.08.066","journal-title":"Expert Syst Appl"},{"key":"5155_CR20","first-page":"1130","volume-title":"IEEE International Conference on Image Processing, 2005. ICIP 2005","author":"P Daras","year":"2005","unstructured":"Daras P, Zarpalas D, Tzovaras D, Strintzis M: 3D shape-based techniques for protein classification. IEEE International Conference on Image Processing, 2005. ICIP 2005. 2005, 1130\u20131133."},{"issue":"3","key":"5155_CR21","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1109\/TCBB.2006.43","volume":"3","author":"P Daras","year":"2006","unstructured":"Daras P, Zarpalas D, Axenopoulos A, Tzovaras D, Strintzis MG: Three-dimensional shape-structure comparison method for protein classification. IEEE\/ACM Trans Comput Biol Bioinform 2006, 3(3):193\u2013207. 10.1109\/TCBB.2006.43","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"5155_CR22","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1186\/1471-2105-9-511","volume":"9","author":"M Oscamou","year":"2008","unstructured":"Oscamou M, McDonald D, Yap VB, Huttley GA, Lladser ME, Knight R: Comparison of methods for estimating the nucleotide substitution matrix. BMC Bioinformatics 2008, 9: 511. 10.1186\/1471-2105-9-511","journal-title":"BMC Bioinformatics"},{"key":"5155_CR23","first-page":"394","volume-title":"Proceedings of the Sixth International Conference on Data Mining, 2006. ICDM '06","author":"K Marsolo","year":"2006","unstructured":"Marsolo K, Parthasarathy S: On the use of structure and sequence-based features for protein classification and retrieval. Proceedings of the Sixth International Conference on Data Mining, 2006. ICDM '06. 2006, 394\u2013403. 10.1109\/ICDM.2006.119"},{"key":"5155_CR24","doi-asserted-by":"publisher","first-page":"1259","DOI":"10.1002\/prot.22030","volume":"72","author":"L Sael","year":"2008","unstructured":"Sael L, Li B, La D, Fang Y, Ramani K, Rustamov R, Kihara D: Fast protein tertiary structure retrieval based on global surface shape similarity. Proteins 2008, 72: 1259\u20131273. 10.1002\/prot.22030","journal-title":"Proteins"},{"issue":"6","key":"5155_CR25","doi-asserted-by":"publisher","first-page":"3408","DOI":"10.1137\/090748834","volume":"20","author":"H Mittelmann","year":"2010","unstructured":"Mittelmann H, Peng J: Estimating bounds for quadratic assignment problems associated with Hamming and Manhattan distance matrices based on semidefinite programming. SIAM J Optim 2010, 20(6):3408\u20133426. 10.1137\/090748834","journal-title":"SIAM J Optim"},{"issue":"Suppl 1","key":"5155_CR26","doi-asserted-by":"publisher","first-page":"S46","DOI":"10.1186\/1471-2105-11-S1-S46","volume":"11","author":"L Zhang","year":"2010","unstructured":"Zhang L, Bailey J, Konagurthu AS, Ramamohanarao K: A fast indexing approach for protein structure comparison. BMC Bioinformatics 2010, 11(Suppl 1):S46. 10.1186\/1471-2105-11-S1-S46","journal-title":"BMC Bioinformatics"},{"issue":"Suppl 15","key":"5155_CR27","doi-asserted-by":"publisher","first-page":"S5","DOI":"10.1186\/1471-2105-10-S15-S5","volume":"10","author":"B Lee","year":"2009","unstructured":"Lee B, Lee D: Protein comparison at the domain architecture level. BMC Bioinformatics 2009, 10(Suppl 15):S5. 10.1186\/1471-2105-10-S15-S5","journal-title":"BMC Bioinformatics"},{"key":"5155_CR28","first-page":"2701","volume-title":"International Conference on Computer Science, ICCS 2010","author":"M Rahman","year":"2010","unstructured":"Rahman M, Hassan MR, Buyya R: Jaccard index based availability prediction in enterprise grids. International Conference on Computer Science, ICCS 2010. 2010, 2701\u20132710."},{"key":"5155_CR29","first-page":"2483","volume-title":"International Joint Conference on Neural Networks, 2001. IJCNN '01","author":"S Garavaglia","year":"2001","unstructured":"Garavaglia S: Statistical analysis of the Tanimoto coefficient self-organizing map (TCSOM) applied to health behavioral survey data. International Joint Conference on Neural Networks, 2001. IJCNN '01. 2001, 2483\u20132488."},{"key":"5155_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/CVPR.2007.382970","volume-title":"IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR '07","author":"H Jegou","year":"2007","unstructured":"Jegou H, Harzallah H, Schmid C: A contextual dissimilarity measure for accurate and efficient image search. IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR '07. 2007, 1\u20138."},{"issue":"1","key":"5155_CR31","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1109\/TPAMI.2008.285","volume":"32","author":"H Jegou","year":"2010","unstructured":"Jegou H, Schmid C, Harzallah H, Verbeek J: Accurate image search using the contextual dissimilarity measure. IEEE Trans Pattern Anal Mach Intell 2010, 32(1):2\u201311.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"5155_CR32","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1007\/978-3-540-88693-8_58","volume-title":"10th European Conference on Computer Vision. ECCV 2008","author":"X Yang","year":"2008","unstructured":"Yang X, Bai X, Latecki LJ, Tu Z: Improving shape retrieval by learning graph transduction. 10th European Conference on Computer Vision. ECCV 2008. 2008, 788\u2013801."},{"issue":"5","key":"5155_CR33","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1109\/TPAMI.2009.85","volume":"32","author":"X Bai","year":"2010","unstructured":"Bai X, Yang X, Latecki LJ, Liu W, Tu Z: Learning context-sensitive shape similarity by graph transduction. IEEE Trans Pattern Anal Mach Intell 2010, 32(5):861\u2013874.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"5155_CR34","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1007\/978-3-642-15558-1_24","volume-title":"11th European Conference on Computer Vision. ECCV 2010","author":"X Bai","year":"2010","unstructured":"Bai X, Wang B, Wang X, Liu W, Tu Z: Co-transduction for shape retrieval. 11th European Conference on Computer Vision. ECCV 2010. 2010, 328\u2013341."},{"issue":"2","key":"5155_CR35","doi-asserted-by":"publisher","first-page":"876","DOI":"10.1214\/aoms\/1177703591","volume":"35","author":"R Sinkhorn","year":"1964","unstructured":"Sinkhorn R: A relationship between arbitrary positive matrices and doubly stochastic matrices. Ann Math Statist 1964, 35(2):876\u2013879. 10.1214\/aoms\/1177703591","journal-title":"Ann Math Statist"},{"issue":"10-11","key":"5155_CR36","doi-asserted-by":"publisher","first-page":"2367","DOI":"10.1016\/j.patcog.2011.02.007","volume":"44","author":"J Wang","year":"2011","unstructured":"Wang J, Li Y, Bai X, Zhang Y, Wang C, Tang N: Learning context-sensitive similarity by shortest path propagation. Pattern Recognition 2011, 44(10\u201311):2367\u20132374. 10.1016\/j.patcog.2011.02.007","journal-title":"Pattern Recognition"},{"issue":"19","key":"5155_CR37","doi-asserted-by":"publisher","first-page":"3711","DOI":"10.1093\/bioinformatics\/bti608","volume":"21","author":"R Kuang","year":"2005","unstructured":"Kuang R, Weston J, Noble W, Leslie C: Motif-based protein ranking by network propagation. Bioinformatics 2005, 21(19):3711\u20133718. 10.1093\/bioinformatics\/bti608","journal-title":"Bioinformatics"},{"issue":"Suppl 1","key":"5155_CR38","doi-asserted-by":"publisher","first-page":"S10","DOI":"10.1186\/1471-2105-7-S1-S10","volume":"7","author":"J Weston","year":"2006","unstructured":"Weston J, Kuang R, Leslie C, Noble WS: Protein ranking by semi-supervised network propagation. BMC Bioinformatics 2006, 7(Suppl 1):S10. 10.1186\/1471-2105-7-S1-S10","journal-title":"BMC Bioinformatics"},{"key":"5155_CR39","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1109\/CBMI.2008.4564949","volume-title":"International Workshop on Content-Based Multimedia Indexing, 2008. CBMI 2008.","author":"H Sahbi","year":"2008","unstructured":"Sahbi H, Audibert JY, Rabarisoa J, Keriven R: Object recognition and retrieval by context dependent similarity kernels. International Workshop on Content-Based Multimedia Indexing, 2008. CBMI 2008. 2008, 216\u2013223."},{"issue":"4","key":"5155_CR40","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1109\/TPAMI.2010.198","volume":"33","author":"H Sahbi","year":"2011","unstructured":"Sahbi H, Audibert J, Keriven R: Context-dependent kernels for object classification. IEEE Trans Pattern Anal Mach Intell 2011, 33(4):699\u2013708.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"Suppl 11","key":"5155_CR41","doi-asserted-by":"publisher","first-page":"S11","DOI":"10.1186\/1471-2105-11-S11-S11","volume":"11","author":"J Ding","year":"2010","unstructured":"Ding J, Zhou S, Guan J: MiRenSVM: towards better prediction of microRNA precursors using an ensemble SVM classifier with multi-loop features. BMC Bioinformatics 2010, 11(Suppl 11):S11. 10.1186\/1471-2105-11-S11-S11","journal-title":"BMC Bioinformatics"},{"key":"5155_CR42","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1186\/1471-2105-11-537","volume":"11","author":"AJ Gonz\u00e1lez","year":"2010","unstructured":"Gonz\u00e1lez AJ, Liao L: Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines. BMC Bioinformatics 2010, 11: 537. 10.1186\/1471-2105-11-537","journal-title":"BMC Bioinformatics"},{"key":"5155_CR43","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1109\/ICSMC.2009.5346745","volume-title":"IEEE International Conference on Systems, Man and Cybernetics, 2009. SMC 2009","author":"J Wang","year":"2009","unstructured":"Wang J, Li Y, Liang P, Zhang G, Ao X: An effective multi-biometrics solution for embedded device. IEEE International Conference on Systems, Man and Cybernetics, 2009. SMC 2009. 2009, 917\u2013922."},{"key":"5155_CR44","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1109\/SSP.2009.5278568","volume-title":"IEEE\/SP 15th Workshop on Statistical Signal Processing, 2009. SSP '09","author":"J Wang","year":"2009","unstructured":"Wang J, Li Y, Ao X, Wang C, Zhou J: Multi-modal biometric authentication fusing iris and palmprint based on GMM. IEEE\/SP 15th Workshop on Statistical Signal Processing, 2009. SSP '09. 2009, 349\u2013352."},{"key":"5155_CR45","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1109\/CBMI.2008.4564972","volume-title":"International Workshop on Content-Based Multimedia Indexing, 2008. CBMI 2008.","author":"G Shih-Wen Ke","year":"2008","unstructured":"Shih-Wen Ke G, Oakes MP, Palomino MA, Xu Y: Comparison between SVM-Light, a search engine-based approach and the mediamill baselines for assigning concepts to video shot annotations. International Workshop on Content-Based Multimedia Indexing, 2008. CBMI 2008. 2008, 381\u2013387."},{"key":"5155_CR46","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1186\/1471-2105-10-445","volume":"10","author":"J Ramana","year":"2009","unstructured":"Ramana J, Gupta D: LipocalinPred: a SVM-based method for prediction of lipocalins. BMC Bioinformatics 2009, 10: 445. 10.1186\/1471-2105-10-445","journal-title":"BMC Bioinformatics"},{"issue":"2","key":"5155_CR47","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1016\/j.jmaa.2007.04.052","volume":"337","author":"K Ey","year":"2008","unstructured":"Ey K, Poetzsche C: Asymptotic behavior of recursions via fixed point theory. Journal of Mathematical Analysis and Applications 2008, 337(2):1125\u20131141. 10.1016\/j.jmaa.2007.04.052","journal-title":"Journal of Mathematical Analysis and Applications"},{"issue":"1","key":"5155_CR48","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1093\/nar\/28.1.254","volume":"28","author":"S Brenner","year":"2000","unstructured":"Brenner S, Koehl P, Levitt R: The ASTRAL compendium for protein structure and sequence analysis. Nucleic Acids Res 2000, 28(1):254\u2013256. 10.1093\/nar\/28.1.254","journal-title":"Nucleic Acids Res"},{"key":"5155_CR49","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1186\/1471-2105-10-153","volume":"10","author":"A Stivala","year":"2009","unstructured":"Stivala A, Wirth A, Stuckey PJ: Tableau-based protein substructure search using quadratic programming. BMC Bioinformatics 2009, 10: 153. 10.1186\/1471-2105-10-153","journal-title":"BMC Bioinformatics"},{"key":"5155_CR50","unstructured":"FSSP\/DALI Database[http:\/\/ekhidna.biocenter.helsinki.fi\/dali\/start]"},{"issue":"1","key":"5155_CR51","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1093\/nar\/24.1.206","volume":"24","author":"L Holm","year":"1996","unstructured":"Holm L, Sander C: The FSSP database: fold classification based on structure-structure alignment of proteins. Nucleic Acids Res 1996, 24(1):206\u2013209. 10.1093\/nar\/24.1.206","journal-title":"Nucleic Acids Res"},{"key":"5155_CR52","first-page":"3600","volume":"22","author":"L Holm","year":"1994","unstructured":"Holm L, Sander C: The FSSP database of structurally aligned protein fold families. Nucleic Acids Res 1994, 22: 3600\u20133609.","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"5155_CR53","first-page":"536","volume":"247","author":"AG Murzin","year":"1995","unstructured":"Murzin AG, Brenner SE, Hubbard T, Chothia C: SCOP: a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 1995, 247(4):536\u2013540.","journal-title":"J Mol Biol"},{"key":"5155_CR54","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1186\/1471-2105-12-77","volume":"12","author":"X Robin","year":"2011","unstructured":"Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, M\u00fcller M: pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011, 12: 77. 10.1186\/1471-2105-12-77","journal-title":"BMC Bioinformatics"},{"key":"5155_CR55","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1186\/1471-2105-12-60","volume":"12","author":"RT Tsai","year":"2011","unstructured":"Tsai RT, Lai PT: Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles. BMC Bioinformatics 2011, 12: 60. 10.1186\/1471-2105-12-60","journal-title":"BMC Bioinformatics"},{"issue":"5","key":"5155_CR56","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1093\/bioinformatics\/btm641","volume":"24","author":"AS Konagurthu","year":"2008","unstructured":"Konagurthu AS, Stuckey PJ, Lesk AM: Structural search and retrieval using a tableau representation of protein folding patterns. Bioinformatics 2008, 24(5):645\u2013651. 10.1093\/bioinformatics\/btm641","journal-title":"Bioinformatics"},{"issue":"1","key":"5155_CR57","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1002\/prot.20517","volume":"61","author":"M Carpentier","year":"2005","unstructured":"Carpentier M, Brouillet S, Pothier J: YAKUSA: a fast structural database scanning method. Proteins 2005, 61(1):137\u2013151. 10.1002\/prot.20517","journal-title":"Proteins"},{"issue":"8","key":"5155_CR58","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1093\/protein\/13.8.535","volume":"13","author":"J Jung","year":"2000","unstructured":"Jung J, Lee B: Protein structure alignment using environmental profiles. Protein Eng 2000, 13(8):535\u2013543. 10.1093\/protein\/13.8.535","journal-title":"Protein Eng"},{"issue":"3","key":"5155_CR59","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1002\/prot.340230309","volume":"23","author":"T Madej","year":"1995","unstructured":"Madej T, Gibrat JF, Bryant SH: Threading a database of protein cores. Proteins 1995, 23(3):356\u2013369. 10.1002\/prot.340230309","journal-title":"Proteins"},{"issue":"3","key":"5155_CR60","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1016\/S0959-440X(96)80058-3","volume":"6","author":"JF Gibrat","year":"1996","unstructured":"Gibrat JF, Madej T, Bryant SH: Surprising similarities in structure comparison. Curr Opin Struct Biol 1996, 6(3):377\u2013385. 10.1016\/S0959-440X(96)80058-3","journal-title":"Curr Opin Struct Biol"},{"issue":"4","key":"5155_CR61","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1093\/bioinformatics\/15.4.317","volume":"15","author":"D Gilbert","year":"1999","unstructured":"Gilbert D, Westhead D, Nagano N, Thornton J: Motif-based searching in TOPS protein topology databases. Bioinformatics 1999, 15(4):317\u2013326. 10.1093\/bioinformatics\/15.4.317","journal-title":"Bioinformatics"},{"issue":"10","key":"5155_CR62","doi-asserted-by":"publisher","first-page":"2537","DOI":"10.1093\/bioinformatics\/bti331","volume":"21","author":"G Torrance","year":"2005","unstructured":"Torrance G, Gilbert D, Michalopoulos I, Westhead D: Protein structure topological comparison, discovery and matching service. Bioinformatics 2005, 21(10):2537\u20132538. 10.1093\/bioinformatics\/bti331","journal-title":"Bioinformatics"},{"issue":"Suppl 1","key":"5155_CR63","doi-asserted-by":"publisher","first-page":"S11","DOI":"10.1186\/1471-2105-12-S1-S11","volume":"12","author":"W Zhang","year":"2011","unstructured":"Zhang W, Sun F, Jiang R: Integrating multiple protein-protein interaction networks to prioritize disease genes: a Bayesian regression approach. BMC Bioinformatics 2011, 12(Suppl 1):S11. 10.1186\/1471-2105-12-S1-S11","journal-title":"BMC Bioinformatics"},{"key":"5155_CR64","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1186\/1471-2105-12-214","volume":"12","author":"F Meyer","year":"2011","unstructured":"Meyer F, Kurtz S, Backofen R, Will S, Beckstette M: Structator: fast index-based search for RNA sequence-structure patterns. BMC Bioinformatics 2011, 12: 214. 10.1186\/1471-2105-12-214","journal-title":"BMC Bioinformatics"},{"key":"5155_CR65","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1186\/1471-2105-12-109","volume":"12","author":"WE Chang","year":"2011","unstructured":"Chang WE, Sarver K, Higgs BW, Read TD, Nolan NM, Chapman CE, Bishop-Lilly KA, Sozhamannan S: PheMaDB: a solution for storage, retrieval, and analysis of high throughput phenotype data. BMC Bioinformatics 2011, 12: 109. 10.1186\/1471-2105-12-109","journal-title":"BMC Bioinformatics"},{"key":"5155_CR66","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1186\/1471-2105-9-533","volume":"9","author":"A Krebs","year":"2008","unstructured":"Krebs A, Frontini M, Tora L: GPAT: retrieval of genomic annotation from large genomic position datasets. BMC Bioinformatics 2008, 9: 533. 10.1186\/1471-2105-9-533","journal-title":"BMC Bioinformatics"},{"issue":"11","key":"5155_CR67","doi-asserted-by":"publisher","first-page":"1996","DOI":"10.1109\/TMI.2011.2161673","volume":"30","author":"J Wang","year":"2011","unstructured":"Wang J, Li Y, Zhang Y, Wang C, Xie H, Chen G, Gao X: Bag-of-features based medical image retrieval via multiple assignment and visual words weighting. IEEE Trans Med Imaging 2011, 30(11):1996\u20132011.","journal-title":"IEEE Trans Med Imaging"},{"key":"5155_CR68","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1109\/ICIG.2011.193","volume-title":"2011 Sixth International Conference on Image and Graphics (ICIG)","author":"J Wang","year":"2011","unstructured":"Wang J, Li Y, Zhang Y, Xie H, Wang C: Boosted learning of visual word weighting factors for bag-of-features based medical image retrieval. 2011 Sixth International Conference on Image and Graphics (ICIG). 2011, 1035\u20131040."},{"key":"5155_CR69","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1109\/ICIG.2011.192","volume-title":"2011 Sixth International Conference on Image and Graphics (ICIG)","author":"J Wang","year":"2011","unstructured":"Wang J, Li Y, Zhang Y, Xie H, Wang C: Bag-of-features based classification of breast parenchymal tissue in the mammogram via jointly selecting and weighting visual words. 2011 Sixth International Conference on Image and Graphics (ICIG). 2011, 622\u2013627."},{"key":"5155_CR70","first-page":"80092P","volume-title":"Proceedings of SPIE 8009","author":"Z Liu","year":"2011","unstructured":"Liu Z, Wang J, Li Y, Zhang Y, Wang C: Quantized image patches co-occurrence matrix: a new statistical approach for texture classification using image patch exemplars. Proceedings of SPIE 8009. 2011, 80092P."}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-13-S7-S2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T18:55:40Z","timestamp":1630522540000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-13-S7-S2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,5,8]]},"references-count":70,"journal-issue":{"issue":"S7","published-print":{"date-parts":[[2012,12]]}},"alternative-id":["5155"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-13-s7-s2","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,5,8]]},"assertion":[{"value":"8 May 2012","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"S2"}}