{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:33:54Z","timestamp":1750221234422,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":33,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,8,15]],"date-time":"2018-08-15T00:00:00Z","timestamp":1534291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"SVV","award":["260451"],"award-info":[{"award-number":["260451"]}]},{"name":"GAUK","award":["1556217"],"award-info":[{"award-number":["1556217"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,8,15]]},"DOI":"10.1145\/3233547.3233708","type":"proceedings-article","created":{"date-parts":[[2018,8,24]],"date-time":"2018-08-24T12:05:17Z","timestamp":1535112317000},"page":"645-650","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Peptide-Binding Site Prediction From Protein Structure via points on the Solvent Accessible Surface"],"prefix":"10.1145","author":[{"given":"Radoslav","family":"Kriv\u00e1k","sequence":"first","affiliation":[{"name":"Charles University, Prague, Czech Rep"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luk\u00e1\u0161","family":"Jendele","sequence":"additional","affiliation":[{"name":"Charles University, Prague, Czech Rep"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Hoksza","sequence":"additional","affiliation":[{"name":"Charles University, Prague, Congo Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,8,15]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Raveh Barak London Nir and Schueler-Furman Ora. {n. d.}. Sub-angstrom modeling of complexes between flexible peptides and globular proteins. Proteins: Structure Function and Bioinformatics 78 9 ({n. d.}) 2029--2040.  Raveh Barak London Nir and Schueler-Furman Ora. {n. d.}. Sub-angstrom modeling of complexes between flexible peptides and globular proteins. Proteins: Structure Function and Bioinformatics 78 9 ({n. d.}) 2029--2040.","key":"e_1_3_2_1_1_1","DOI":"10.1002\/prot.22716"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_2_1","DOI":"10.1023\/A:1010933404324"},{"unstructured":"Eric Brochu Vlad M. Cora and Nando de Freitas. 2009. A Tutorial on Bayesian Optimization of Expensive Cost Functions with Application to Active User Modeling and Hierarchical Reinforcement Learning. CoRR abs\/1012.2599 (2009).  Eric Brochu Vlad M. Cora and Nando de Freitas. 2009. A Tutorial on Bayesian Optimization of Expensive Cost Functions with Application to Active User Modeling and Hierarchical Reinforcement Learning. CoRR abs\/1012.2599 (2009).","key":"e_1_3_2_1_3_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_4_1","DOI":"10.1093\/bioinformatics\/btm270"},{"doi-asserted-by":"crossref","unstructured":"Yan Chengfei and Zou Xiaoqin. {n. d.}. Predicting peptide binding sites on protein surfaces by clustering chemical interactions. Journal of Computational Chemistry 36 1 ({n. d.}) 49--61.  Yan Chengfei and Zou Xiaoqin. {n. d.}. Predicting peptide binding sites on protein surfaces by clustering chemical interactions. Journal of Computational Chemistry 36 1 ({n. d.}) 49--61.","key":"e_1_3_2_1_5_1","DOI":"10.1002\/jcc.23771"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_6_1","DOI":"10.1016\/j.sbi.2016.12.009"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_7_1","DOI":"10.1021\/ci300184x"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_8_1","DOI":"10.4155\/fmc.15.142"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_9_1","DOI":"10.1002\/jcc.540160303"},{"doi-asserted-by":"crossref","unstructured":"Sumaiya Iqbal and Tamjidul Hoque. 2018. PBRpredict-Suite: A Suite of Models to Predict Peptide Recognition Domain Residues from Protein Sequence. Bioinformatics (2018) bty352.  Sumaiya Iqbal and Tamjidul Hoque. 2018. PBRpredict-Suite: A Suite of Models to Predict Peptide Recognition Domain Residues from Protein Sequence. Bioinformatics (2018) bty352.","key":"e_1_3_2_1_10_1","DOI":"10.1093\/bioinformatics\/bty352"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_11_1","DOI":"10.1016\/j.jmb.2013.09.039"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_12_1","DOI":"10.1186\/s13321-015-0059-5"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_13_1","DOI":"10.1007\/978-3-319-21233-3_4"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_14_1","DOI":"10.1016\/0022-2836(82)90515-0"},{"doi-asserted-by":"crossref","unstructured":"Assaf Lavi Chi Ho Ngan Dana Movshovitz-Attias Tanggis Bohnuud Christine Yueh Dmitri Beglov Ora Schueler-Furman and Dima Kozakov. {n. d.}. Detection of peptide-binding sites on protein surfaces: The first step toward the modeling and targeting of peptide-mediated interactions. Proteins: Structure Function and Bioinformatics 81 12 ({n. d.}) 2096--2105.  Assaf Lavi Chi Ho Ngan Dana Movshovitz-Attias Tanggis Bohnuud Christine Yueh Dmitri Beglov Ora Schueler-Furman and Dima Kozakov. {n. d.}. Detection of peptide-binding sites on protein surfaces: The first step toward the modeling and targeting of peptide-mediated interactions. Proteins: Structure Function and Bioinformatics 81 12 ({n. d.}) 2096--2105.","key":"e_1_3_2_1_15_1","DOI":"10.1002\/prot.24422"},{"doi-asserted-by":"crossref","unstructured":"Bin Li Srinivasan Turuvekere Manish Agrawal David La Karthik Ramani and Daisuke Kihara. {n. d.}. Characterization of local geometry of protein surfaces with the visibility criterion. Proteins: Structure Function and Bioinformatics 71 2 ({n. d.}) 670--683. arXiv:https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/prot.21732  Bin Li Srinivasan Turuvekere Manish Agrawal David La Karthik Ramani and Daisuke Kihara. {n. d.}. Characterization of local geometry of protein surfaces with the visibility criterion. Proteins: Structure Function and Bioinformatics 71 2 ({n. d.}) 670--683. arXiv:https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/prot.21732","key":"e_1_3_2_1_16_1","DOI":"10.1002\/prot.21732"},{"doi-asserted-by":"crossref","unstructured":"Haiou Li Liyao Lu Rong Chen Lijun Quan Xiaoyan Xia and Qiang L\u00fc. 2014. PaFlexPepDock: Parallel Ab-Initio Docking of Peptides onto Their Receptors with Full Flexibility Based on Rosetta. PLOS ONE 9 5 (05 2014) 1--13.  Haiou Li Liyao Lu Rong Chen Lijun Quan Xiaoyan Xia and Qiang L\u00fc. 2014. PaFlexPepDock: Parallel Ab-Initio Docking of Peptides onto Their Receptors with Full Flexibility Based on Rosetta. PLOS ONE 9 5 (05 2014) 1--13.","key":"e_1_3_2_1_17_1","DOI":"10.1371\/journal.pone.0094769"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_18_1","DOI":"10.1093\/nar\/gkl454"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_19_1","DOI":"10.1517\/17460441.2016.1146250"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_20_1","DOI":"10.1016\/j.tips.2016.05.008"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_21_1","DOI":"10.1093\/bioinformatics\/18.7.980"},{"doi-asserted-by":"crossref","unstructured":"Barak Raveh Nir London Lior Zimmerman and Ora Schueler-Furman. 2011. Rosetta FlexPepDock ab-initio: Simultaneous Folding Docking and Refinement of Peptides onto Their Receptors. PLOS ONE 6 4 (04 2011) 1--10.  Barak Raveh Nir London Lior Zimmerman and Ora Schueler-Furman. 2011. Rosetta FlexPepDock ab-initio: Simultaneous Folding Docking and Refinement of Peptides onto Their Receptors. PLOS ONE 6 4 (04 2011) 1--10.","key":"e_1_3_2_1_22_1","DOI":"10.1371\/journal.pone.0018934"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_23_1","DOI":"10.1093\/nar\/gku404"},{"doi-asserted-by":"crossref","unstructured":"Joan Segura Pamela F. Jones and Narcis Fernandez-Fuentes. 2011. Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams. BMC Bioinformatics 12 1 (23 Aug 2011) 352.  Joan Segura Pamela F. Jones and Narcis Fernandez-Fuentes. 2011. Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams. BMC Bioinformatics 12 1 (23 Aug 2011) 352.","key":"e_1_3_2_1_24_1","DOI":"10.1186\/1471-2105-12-352"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_25_1","DOI":"10.1093\/bioinformatics\/bts269"},{"unstructured":"Jasper Snoek Hugo Larochelle and Ryan P Adams. 2012. Practical Bayesian Optimization of Machine Learning Algorithms. In Advances in Neural Information Processing Systems 25. 2951--2959.   Jasper Snoek Hugo Larochelle and Ryan P Adams. 2012. Practical Bayesian Optimization of Machine Learning Algorithms. In Advances in Neural Information Processing Systems 25. 2951--2959.","key":"e_1_3_2_1_26_1"},{"doi-asserted-by":"crossref","unstructured":"Ghazaleh Taherzadeh Yuedong Yang Tuo Zhang Alan Wee-Chung Liew and Yaoqi Zhou. {n. d.}. Sequence-based prediction of protein peptide binding sites using support vector machine. Journal of Computational Chemistry 37 13 ({n. d.}) 1223--1229.  Ghazaleh Taherzadeh Yuedong Yang Tuo Zhang Alan Wee-Chung Liew and Yaoqi Zhou. {n. d.}. Sequence-based prediction of protein peptide binding sites using support vector machine. Journal of Computational Chemistry 37 13 ({n. d.}) 1223--1229.","key":"e_1_3_2_1_27_1","DOI":"10.1002\/jcc.24314"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_28_1","DOI":"10.1093\/bioinformatics\/btx614"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_29_1","DOI":"10.1093\/nar\/gks398"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_30_1","DOI":"10.1093\/nar\/gks398"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_31_1","DOI":"10.1016\/j.str.2013.02.023"},{"key":"e_1_3_2_1_32_1","article-title":"The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching","volume":"9","author":"Willighagen Egon L.","year":"2017","journal-title":"Journal of Cheminformatics"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_33_1","DOI":"10.1016\/j.bmcl.2015.12.084"}],"event":{"sponsor":["SIGBio ACM Special Interest Group on Bioinformatics"],"acronym":"BCB '18","name":"BCB '18: 9th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","location":"Washington DC USA"},"container-title":["Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3233547.3233708","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3233547.3233708","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:07:11Z","timestamp":1750212431000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3233547.3233708"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,15]]},"references-count":33,"alternative-id":["10.1145\/3233547.3233708","10.1145\/3233547"],"URL":"https:\/\/doi.org\/10.1145\/3233547.3233708","relation":{},"subject":[],"published":{"date-parts":[[2018,8,15]]},"assertion":[{"value":"2018-08-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}