{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T00:51:04Z","timestamp":1775263864845,"version":"3.50.1"},"reference-count":160,"publisher":"Oxford University Press (OUP)","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brief Bioinform"],"DOI":"10.1093\/bib\/bbw129","type":"journal-article","created":{"date-parts":[[2016,11,19]],"date-time":"2016-11-19T04:05:52Z","timestamp":1479528352000},"page":"bbw129","source":"Crossref","is-referenced-by-count":102,"title":["Sixty-five years of the long march in protein secondary structure prediction: the final stretch?"],"prefix":"10.1093","author":[{"given":"Yuedong","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianzhao","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jihua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rhys","family":"Heffernan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jack","family":"Hanson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuldip","family":"Paliwal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaoqi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,12,31]]},"reference":[{"key":"2016123117402152000_bbw129v1.1","doi-asserted-by":"publisher","DOI":"10.1038\/75556"},{"key":"2016123117402152000_bbw129v1.2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkm993"},{"key":"2016123117402152000_bbw129v1.3","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gku947"},{"key":"2016123117402152000_bbw129v1.4","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gku1216"},{"key":"2016123117402152000_bbw129v1.5","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/28.1.235"},{"key":"2016123117402152000_bbw129v1.6","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.biophys.050708.133740"},{"key":"2016123117402152000_bbw129v1.7","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2006-7-7-112"},{"key":"2016123117402152000_bbw129v1.8","doi-asserted-by":"publisher","DOI":"10.1007\/s00214-010-0799-2"},{"key":"2016123117402152000_bbw129v1.9","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1002\/prot.24470","article-title":"Assessment of template-free modeling in CASP10 and ROLL","volume":"82(Suppl 2)","author":"Tai","year":"2014","journal-title":"Proteins"},{"key":"2016123117402152000_bbw129v1.10","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1995.0159"},{"key":"2016123117402152000_bbw129v1.11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmb.2011.02.056"},{"key":"2016123117402152000_bbw129v1.12","doi-asserted-by":"publisher","DOI":"10.1038\/43940"},{"key":"2016123117402152000_bbw129v1.13","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0703700104"},{"key":"2016123117402152000_bbw129v1.14","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1998.1645"},{"key":"2016123117402152000_bbw129v1.15","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1002\/pro.5560050516","article-title":"Protein fold recognition using sequence-derived predictions","volume":"5","author":"Fischer","year":"1996","journal-title":"Protein Sci"},{"key":"2016123117402152000_bbw129v1.16","doi-asserted-by":"publisher","DOI":"10.1002\/prot.20106"},{"key":"2016123117402152000_bbw129v1.17","doi-asserted-by":"publisher","DOI":"10.1016\/S0076-6879(04)83004-0"},{"key":"2016123117402152000_bbw129v1.18","doi-asserted-by":"publisher","DOI":"10.1186\/1741-7007-5-17"},{"key":"2016123117402152000_bbw129v1.19","doi-asserted-by":"publisher","DOI":"10.1002\/prot.10328"},{"key":"2016123117402152000_bbw129v1.20","doi-asserted-by":"publisher","DOI":"10.1002\/prot.20176"},{"key":"2016123117402152000_bbw129v1.21","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btv665"},{"key":"2016123117402152000_bbw129v1.22","doi-asserted-by":"publisher","DOI":"10.1002\/prot.20587"},{"key":"2016123117402152000_bbw129v1.23","doi-asserted-by":"publisher","DOI":"10.1529\/biophysj.106.094045"},{"key":"2016123117402152000_bbw129v1.24","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts209"},{"key":"2016123117402152000_bbw129v1.25","doi-asserted-by":"publisher","DOI":"10.1007\/s12013-013-9638-0"},{"key":"2016123117402152000_bbw129v1.26","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti582"},{"key":"2016123117402152000_bbw129v1.27","doi-asserted-by":"crossref","first-page":"472.","DOI":"10.1186\/1471-2105-12-472","article-title":"MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts","volume":"12","author":"Deng","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2016123117402152000_bbw129v1.28","doi-asserted-by":"publisher","DOI":"10.1007\/s00018-007-7211-y"},{"key":"2016123117402152000_bbw129v1.29","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1021\/acs.jcim.6b00320","article-title":"Sequence-based prediction of protein\u2013carbohydrate binding sites using support vector machines","volume":"56","author":"Taherzadeh","year":"2016","journal-title":"J Chem Inf Model"},{"key":"2016123117402152000_bbw129v1.30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmb.2005.08.020"},{"key":"2016123117402152000_bbw129v1.31","doi-asserted-by":"crossref","first-page":"56.","DOI":"10.1186\/1472-6807-7-56","article-title":"Spectrum of disease-causing mutations in protein secondary structures","volume":"7","author":"Khan","year":"2007","journal-title":"BMC Struct Biol"},{"key":"2016123117402152000_bbw129v1.32","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btp528"},{"key":"2016123117402152000_bbw129v1.33","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2013-14-5-r43"},{"key":"2016123117402152000_bbw129v1.34","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu862"},{"key":"2016123117402152000_bbw129v1.35","doi-asserted-by":"publisher","DOI":"10.1038\/181662a0"},{"key":"2016123117402152000_bbw129v1.36","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.37.4.205"},{"key":"2016123117402152000_bbw129v1.37","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.37.11.729"},{"key":"2016123117402152000_bbw129v1.38","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/978-1-4939-3572-7_7","article-title":"Criteria to extract high-quality protein data bank subsets for structure users","volume":"1415","author":"Carugo","year":"2016","journal-title":"Methods Mol Biol"},{"key":"2016123117402152000_bbw129v1.39","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/978-1-4939-3572-7_6","article-title":"Data mining of macromolecular structures","volume":"1415","author":"van Beusekom","year":"2016","journal-title":"Methods Mol Biol"},{"key":"2016123117402152000_bbw129v1.40","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gki402"},{"key":"2016123117402152000_bbw129v1.41","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv494"},{"key":"2016123117402152000_bbw129v1.42","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s10858-015-9958-z","article-title":"PPM_One: a static protein structure based chemical shift predictor","volume":"62","author":"Li","year":"2015","journal-title":"J Biomol NMR"},{"key":"2016123117402152000_bbw129v1.43","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2006.202"},{"key":"2016123117402152000_bbw129v1.44","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1500851112"},{"key":"2016123117402152000_bbw129v1.45","doi-asserted-by":"publisher","DOI":"10.1021\/bi00465a022"},{"key":"2016123117402152000_bbw129v1.46","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1038\/nprot.2015.024","article-title":"Obtaining information about protein secondary structures in aqueous solution using Fourier transform IR spectroscopy","volume":"10","author":"Yang","year":"2015","journal-title":"Nat Protoc"},{"key":"2016123117402152000_bbw129v1.47","doi-asserted-by":"publisher","DOI":"10.1006\/jsbi.2001.4336"},{"key":"2016123117402152000_bbw129v1.48","doi-asserted-by":"publisher","DOI":"10.2174\/1389203043379675"},{"key":"2016123117402152000_bbw129v1.49","doi-asserted-by":"publisher","DOI":"10.2174\/1389203003381324"},{"key":"2016123117402152000_bbw129v1.50","doi-asserted-by":"crossref","first-page":"74","DOI":"10.2174\/157489308784340676","article-title":"Machine learning techniques for protein secondary structure prediction: an overview and evaluation","volume":"3","author":"Yoo","year":"2008","journal-title":"Curr Bioinform"},{"key":"2016123117402152000_bbw129v1.51","doi-asserted-by":"crossref","unstructured":"Zhou Y Faraggi E , Prediction of one-dimensional structural properties of proteins by integrated neural network. In: Rangwala H Karypis G (eds). Protein Structure Prediction: Method and Algorithms. Hoboken, NJ: Wiley, 2010, 44\u201374.","DOI":"10.1002\/9780470882207.ch4"},{"key":"2016123117402152000_bbw129v1.52","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-60327-241-4_19"},{"key":"2016123117402152000_bbw129v1.53","doi-asserted-by":"publisher","DOI":"10.1002\/bip.360221211"},{"key":"2016123117402152000_bbw129v1.54","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.90.16.7558"},{"key":"2016123117402152000_bbw129v1.55","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1999.3091"},{"key":"2016123117402152000_bbw129v1.56","doi-asserted-by":"publisher","DOI":"10.1002\/prot.21298"},{"key":"2016123117402152000_bbw129v1.57","doi-asserted-by":"publisher","DOI":"10.1038\/srep11476"},{"key":"2016123117402152000_bbw129v1.58","doi-asserted-by":"publisher","DOI":"10.1038\/srep18962"},{"key":"2016123117402152000_bbw129v1.59","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1994.1700"},{"key":"2016123117402152000_bbw129v1.60","doi-asserted-by":"publisher","DOI":"10.1002\/prot.21654"},{"key":"2016123117402152000_bbw129v1.61","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/25.17.3389"},{"key":"2016123117402152000_bbw129v1.62","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.23718"},{"key":"2016123117402152000_bbw129v1.63","doi-asserted-by":"crossref","first-page":"3847","DOI":"10.1021\/ja01500a015","article-title":"Structural studies of ribonuclease.3. A model for the secondary and tertiary structure","volume":"82","author":"Scheraga","year":"1960","journal-title":"J Am Chem Soc"},{"key":"2016123117402152000_bbw129v1.64","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1016\/0022-2836(71)90160-4","article-title":"Statistical analysis of correlation among amino acid residues in helical, beta-structural and non-regular regions of globular proteins","volume":"62","author":"Finkelstein","year":"1971","journal-title":"J Mol Biol"},{"key":"2016123117402152000_bbw129v1.65","doi-asserted-by":"publisher","DOI":"10.1021\/bi00699a002"},{"key":"2016123117402152000_bbw129v1.66","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(78)90297-8"},{"key":"2016123117402152000_bbw129v1.67","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(74)90405-7"},{"key":"2016123117402152000_bbw129v1.68","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.70.5.1473"},{"key":"2016123117402152000_bbw129v1.69","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1002\/prot.340120410","article-title":"Use of conditional probabilities for determining relationships between amino-acid-sequence and protein secondary structure","volume":"12","author":"Arnold","year":"1992","journal-title":"Proteins"},{"key":"2016123117402152000_bbw129v1.70","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(90)90312-A"},{"key":"2016123117402152000_bbw129v1.71","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.86.1.152"},{"key":"2016123117402152000_bbw129v1.72","doi-asserted-by":"publisher","DOI":"10.1016\/0014-5793(88)81066-4"},{"key":"2016123117402152000_bbw129v1.73","doi-asserted-by":"publisher","DOI":"10.1093\/protein\/5.7.647"},{"key":"2016123117402152000_bbw129v1.74","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1993.1464"},{"key":"2016123117402152000_bbw129v1.75","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(87)90501-8"},{"key":"2016123117402152000_bbw129v1.76","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.2001.4580"},{"key":"2016123117402152000_bbw129v1.77","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btg223"},{"key":"2016123117402152000_bbw129v1.78","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-7-178"},{"key":"2016123117402152000_bbw129v1.79","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-9-49"},{"key":"2016123117402152000_bbw129v1.80","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth370"},{"key":"2016123117402152000_bbw129v1.81","doi-asserted-by":"publisher","DOI":"10.1021\/bi00668a030"},{"key":"2016123117402152000_bbw129v1.82","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0134(20000815)40:3<502::AID-PROT170>3.0.CO;2-Q"},{"key":"2016123117402152000_bbw129v1.83","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti524"},{"key":"2016123117402152000_bbw129v1.84","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-7-301"},{"key":"2016123117402152000_bbw129v1.85","doi-asserted-by":"publisher","DOI":"10.1002\/prot.21177"},{"key":"2016123117402152000_bbw129v1.86","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-8-1"},{"key":"2016123117402152000_bbw129v1.87","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm379"},{"key":"2016123117402152000_bbw129v1.88","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr611"},{"key":"2016123117402152000_bbw129v1.89","doi-asserted-by":"crossref","first-page":"4275","DOI":"10.1007\/s00894-012-1410-7","article-title":"Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction","volume":"18","author":"Saraswathi","year":"2012","journal-title":"J Mol Model"},{"key":"2016123117402152000_bbw129v1.90","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu352"},{"key":"2016123117402152000_bbw129v1.91","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkq427"},{"key":"2016123117402152000_bbw129v1.92","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkn238"},{"key":"2016123117402152000_bbw129v1.93","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv332"},{"key":"2016123117402152000_bbw129v1.94","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1002\/jcc.21968","article-title":"SPINE X: Improving protein secondary structure prediction by multi-step learning coupled with prediction of solvent accessible surface area and backbone torsion angles","volume":"33","author":"Faraggi","year":"2011","journal-title":"J Comput Chem"},{"key":"2016123117402152000_bbw129v1.95","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btt344"},{"key":"2016123117402152000_bbw129v1.96","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1021\/ci400647u","article-title":"Context-based features enhance protein secondary structure prediction accuracy","volume":"54","author":"Yaseen","year":"2014","journal-title":"J Chem Inf Model"},{"key":"2016123117402152000_bbw129v1.97","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2007.09.004"},{"key":"2016123117402152000_bbw129v1.98","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0032235"},{"key":"2016123117402152000_bbw129v1.99","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1109\/TCBB.2014.2343960","article-title":"A deep learning network approach to ab initio protein secondary structure prediction","volume":"12","author":"Spencer","year":"2015","journal-title":"IEEE ACM Trans Comput Biol Bioinform"},{"key":"2016123117402152000_bbw129v1.100","doi-asserted-by":"crossref","unstructured":"Lee H Grosse R Ranganath R , . Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In: Proceedings of the 26th International Conference on Machine Learning. Montreal, Canada, 2009.","DOI":"10.1145\/1553374.1553453"},{"key":"2016123117402152000_bbw129v1.101","unstructured":"Lafferty J Mccallum A Pereira F , Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: 18th International Conference on Machine Learning. Morgan Kaufmann, San Francisco, CA, 2001, p. 282\u20139."},{"key":"2016123117402152000_bbw129v1.102","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl158"},{"key":"2016123117402152000_bbw129v1.103","doi-asserted-by":"publisher","DOI":"10.1002\/prot.20218"},{"key":"2016123117402152000_bbw129v1.104","doi-asserted-by":"crossref","unstructured":"Midic U Dunker AK Obradovic Z. Improving protein secondary-structure prediction by predicting ends of secondary-structure segments. In: Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005, pp. 490\u201397 (IEEE, Niagara Falls, Canada).","DOI":"10.1109\/CIBCB.2005.1594959"},{"key":"2016123117402152000_bbw129v1.105","doi-asserted-by":"publisher","DOI":"10.1093\/protein\/11.6.411"},{"key":"2016123117402152000_bbw129v1.106","doi-asserted-by":"publisher","DOI":"10.1002\/pro.2689"},{"key":"2016123117402152000_bbw129v1.107","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.bbrc.2016.01.187","article-title":"Chameleon sequences in neurodegenerative diseases","volume":"472","author":"Bahramali","year":"2016","journal-title":"Biochem Biophys Res Commun"},{"key":"2016123117402152000_bbw129v1.108","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0134(20001201)41:4<535::AID-PROT100>3.0.CO;2-C"},{"key":"2016123117402152000_bbw129v1.109","doi-asserted-by":"publisher","DOI":"10.1002\/prot.21285"},{"key":"2016123117402152000_bbw129v1.110","doi-asserted-by":"publisher","DOI":"10.6026\/97320630003367"},{"key":"2016123117402152000_bbw129v1.111","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1002\/pro.5560040401","article-title":"Principles of protein folding\u2013a perspective from simple exact models","volume":"4","author":"Dill","year":"1995","journal-title":"Protein Sci"},{"key":"2016123117402152000_bbw129v1.112","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0134(20000201)38:2<121::AID-PROT1>3.0.CO;2-M"},{"key":"2016123117402152000_bbw129v1.113","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0134(19990701)36:1<135::AID-PROT11>3.0.CO;2-I"},{"key":"2016123117402152000_bbw129v1.114","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth132"},{"key":"2016123117402152000_bbw129v1.115","doi-asserted-by":"publisher","DOI":"10.1110\/ps.051479505"},{"key":"2016123117402152000_bbw129v1.116","doi-asserted-by":"crossref","unstructured":"Ceroni A Frasconi P. On the role of long-range dependencies in learning protein secondary structure. In: 2004 IEEE International Joint Conference on Neural Networks, Vols 1\u20134, Proceedings 2004, p. 1899\u20131904 (IEEE, Budapest).","DOI":"10.1109\/IJCNN.2004.1380901"},{"key":"2016123117402152000_bbw129v1.117","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1016\/j.neunet.2005.07.001","article-title":"Learning protein secondary structure from sequential and relational data","volume":"18","author":"Ceroni","year":"2005","journal-title":"Neural Netw"},{"key":"2016123117402152000_bbw129v1.118","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1831973100"},{"key":"2016123117402152000_bbw129v1.119","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1002\/prot.23181","article-title":"CASP9 assessment of free modeling target predictions","volume":"79(Suppl 10)","author":"Kinch","year":"2011","journal-title":"Proteins"},{"key":"2016123117402152000_bbw129v1.120","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0811363106"},{"key":"2016123117402152000_bbw129v1.121","doi-asserted-by":"publisher","DOI":"10.1002\/prot.10082"},{"key":"2016123117402152000_bbw129v1.122","doi-asserted-by":"publisher","DOI":"10.1002\/pmic.201100196"},{"key":"2016123117402152000_bbw129v1.123","first-page":"1","article-title":"Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features","volume":"15(Suppl 8)","author":"Yaseen","year":"2014","journal-title":"BMC Bioinformatics"},{"key":"2016123117402152000_bbw129v1.124","doi-asserted-by":"publisher","DOI":"10.1002\/prot.21940"},{"key":"2016123117402152000_bbw129v1.125","doi-asserted-by":"publisher","DOI":"10.1002\/prot.22193"},{"key":"2016123117402152000_bbw129v1.126","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0105667"},{"key":"2016123117402152000_bbw129v1.127","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0907674106"},{"key":"2016123117402152000_bbw129v1.128","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.94.26.14429"},{"key":"2016123117402152000_bbw129v1.129","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.181328398"},{"key":"2016123117402152000_bbw129v1.130","doi-asserted-by":"publisher","DOI":"10.1039\/c1cp20752k"},{"key":"2016123117402152000_bbw129v1.131","doi-asserted-by":"publisher","DOI":"10.1002\/pro.5560041017"},{"key":"2016123117402152000_bbw129v1.132","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1997.1309"},{"key":"2016123117402152000_bbw129v1.133","doi-asserted-by":"publisher","DOI":"10.1016\/S1359-0278(98)00019-4"},{"key":"2016123117402152000_bbw129v1.134","doi-asserted-by":"crossref","unstructured":"Gao J Yang Y Zhou Y. Predicting the errors of predicted local backbone angles and non-local solvent-accessibilities of proteins by deep neural networks. Bioinformatics 2016, doi: 10.1093\/bioinformatics\/btw549.","DOI":"10.1093\/bioinformatics\/btw549"},{"key":"2016123117402152000_bbw129v1.135","doi-asserted-by":"crossref","first-page":"1604","DOI":"10.1107\/S1399004715008263","article-title":"Detection of trans-cis flips and peptide-plane flips in protein structures","volume":"71","author":"Touw","year":"2015","journal-title":"Acta Crystallogr D Struct Biol"},{"key":"2016123117402152000_bbw129v1.136","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/0014-5793(90)80833-5","article-title":"Prediction of prolyl residues in Cis-conformation in protein structures on the basis of the amino-acid-sequence","volume":"277","author":"Frommel","year":"1990","journal-title":"FEBS Lett"},{"key":"2016123117402152000_bbw129v1.137","doi-asserted-by":"crossref","unstructured":"Song JN Burrage K Yuan Z , . Prediction of cis\/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information. BMC Bioinformatics 2006;7: 124.1-124.13.","DOI":"10.1186\/1471-2105-7-124"},{"key":"2016123117402152000_bbw129v1.138","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-10-14"},{"key":"2016123117402152000_bbw129v1.139","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.jbi.2008.05.006","article-title":"Prediction of cis\/trans isomerization using feature selection and support vector machines","volume":"42","author":"Exarchos","year":"2009","journal-title":"J Biomed Inf"},{"key":"2016123117402152000_bbw129v1.140","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/S1672-0229(08)60042-X","article-title":"PBOND: web server for the prediction of proline and non-proline cis\/trans isomerization","volume":"7","author":"Exarchos","year":"2009","journal-title":"Genomics Proteomics Bioinformatics"},{"key":"2016123117402152000_bbw129v1.141","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1999.3217"},{"key":"2016123117402152000_bbw129v1.142","doi-asserted-by":"publisher","DOI":"10.1021\/cr0104375"},{"key":"2016123117402152000_bbw129v1.143","doi-asserted-by":"publisher","DOI":"10.1016\/j.tips.2004.10.011"},{"key":"2016123117402152000_bbw129v1.144","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmb.2014.12.007"},{"key":"2016123117402152000_bbw129v1.145","doi-asserted-by":"crossref","unstructured":"Abriata LA. Structural database resources for biological macromolecules. Brief Bioinform 2016, in press. [Epub ahead of print]","DOI":"10.1093\/bib\/bbw049"},{"key":"2016123117402152000_bbw129v1.146","doi-asserted-by":"publisher","DOI":"10.1002\/prot.340180402"},{"key":"2016123117402152000_bbw129v1.147","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0028766"},{"key":"2016123117402152000_bbw129v1.148","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2012.04.012"},{"key":"2016123117402152000_bbw129v1.149","doi-asserted-by":"crossref","first-page":"250A","DOI":"10.1016\/j.bpj.2011.11.1378","article-title":"Estimation of residue-residue coevolution using direct coupling analysis identifies many native contacts across a large number of domain families","volume":"102","author":"Morcos","year":"2012","journal-title":"Biophysical Journal"},{"key":"2016123117402152000_bbw129v1.150","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.08932"},{"key":"2016123117402152000_bbw129v1.151","doi-asserted-by":"crossref","first-page":"265","DOI":"10.2174\/1573406411666141230095427","article-title":"Advances in protein contact map prediction based on machine learning","volume":"11","author":"Xie","year":"2015","journal-title":"Med Chem"},{"key":"2016123117402152000_bbw129v1.152","doi-asserted-by":"crossref","unstructured":"Wuyun Q Zheng W Peng Z , . A large-scale comparative assessment of methods for residue\u2013residue contact prediction. Brief Bioinform 2016, doi: https:\/\/doi.org\/10.1093\/bib\/bbw106.","DOI":"10.1093\/bib\/bbw106"},{"key":"2016123117402152000_bbw129v1.153","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1002\/prot.24943","article-title":"New encouraging developments in contact prediction: assessment of the CASP11 results","volume":"84(Suppl 1)","author":"Monastyrskyy","year":"2016","journal-title":"Proteins"},{"key":"2016123117402152000_bbw129v1.154","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/TCBB.2006.17","article-title":"Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction","volume":"3","author":"Chu","year":"2006","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2016123117402152000_bbw129v1.155","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.cell.2016.09.010","article-title":"Structured states of disordered proteins from genomic sequences","volume":"167","author":"Toth-Petroczy","year":"2016","journal-title":"Cell"},{"key":"2016123117402152000_bbw129v1.156","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"2016123117402152000_bbw129v1.157","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"2016123117402152000_bbw129v1.158","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1016\/j.neunet.2005.06.042","article-title":"Framewise phoneme classification with bidirectional LSTM and other neural network architectures","volume":"18","author":"Graves","year":"2005","journal-title":"Neural Netw"},{"key":"2016123117402152000_bbw129v1.159","unstructured":"Vinyals O Toshev A Bengio S , . Show and tell: a neural image caption generator. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, p. 3156\u201364 (IEEE, Boston, Massachusetts)."},{"key":"2016123117402152000_bbw129v1.160","doi-asserted-by":"crossref","unstructured":"Hanson J Yang Y Paliwal K , . Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks. Bioinformatics 2016, in press.","DOI":"10.1093\/bioinformatics\/btw678"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","deposited":{"date-parts":[[2019,9,15]],"date-time":"2019-09-15T19:34:17Z","timestamp":1568576057000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article-lookup\/doi\/10.1093\/bib\/bbw129"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,31]]},"references-count":160,"alternative-id":["10.1093\/bib\/bbw129"],"URL":"https:\/\/doi.org\/10.1093\/bib\/bbw129","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,12,31]]}}}