{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T16:23:21Z","timestamp":1787243001467,"version":"build-2736575974"},"reference-count":90,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2015,1,16]],"date-time":"2015-01-16T00:00:00Z","timestamp":1421366400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"published-print":{"date-parts":[[2015,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Cyclooxygenases (COX) are present in the body in two isoforms, namely: COX-1, constitutively expressed, and COX-2, induced in physiopathological conditions such as cancer or chronic inflammation. The inhibition of COX with non-steroideal anti-inflammatory drugs (NSAIDs) is the most widely used treatment for chronic inflammation despite the adverse effects associated to prolonged NSAIDs intake. Although selective COX-2 inhibition has been shown not to palliate all adverse effects (\n                    <jats:italic>e.g.<\/jats:italic>\n                    cardiotoxicity), there are still niche populations which can benefit from selective COX-2 inhibition. Thus, capitalizing on bioactivity data from both isoforms simultaneously would contribute to develop COX inhibitors with better safety profiles. We applied ensemble proteochemometric modeling (PCM) for the prediction of the potency of 3,228 distinct COX inhibitors on 11 mammalian cyclooxygenases. Ensemble PCM models (\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$R_{0\\ test}^{2}=0.65$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msubsup>\n                            <mml:mrow>\n                              <mml:mi>R<\/mml:mi>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>0<\/mml:mn>\n                              <mml:mspace\/>\n                              <mml:mtext>test<\/mml:mtext>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>2<\/mml:mn>\n                            <\/mml:mrow>\n                          <\/mml:msubsup>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>0.65<\/mml:mn>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    , and RMSE\n                    <jats:sub>test<\/jats:sub>\n                    = 0.71) outperformed models exclusively trained on compound (\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$R_{0\\ test}^{2}=0.17$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msubsup>\n                            <mml:mrow>\n                              <mml:mi>R<\/mml:mi>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>0<\/mml:mn>\n                              <mml:mspace\/>\n                              <mml:mtext>test<\/mml:mtext>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>2<\/mml:mn>\n                            <\/mml:mrow>\n                          <\/mml:msubsup>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>0.17<\/mml:mn>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    , and RMSE\n                    <jats:sub>test<\/jats:sub>\n                    = 1.09) or protein descriptors (\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$R_{0\\ test}^{2}=0.16$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msubsup>\n                            <mml:mrow>\n                              <mml:mi>R<\/mml:mi>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>0<\/mml:mn>\n                              <mml:mspace\/>\n                              <mml:mtext>test<\/mml:mtext>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>2<\/mml:mn>\n                            <\/mml:mrow>\n                          <\/mml:msubsup>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>0.16<\/mml:mn>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    and RMSE\n                    <jats:sub>test<\/jats:sub>\n                    = 1.10) on the test set. Moreover, PCM predicted COX potency for 1,086 selective and non-selective COX inhibitors with\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$R_{0\\ test}^{2}=0.59$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msubsup>\n                            <mml:mrow>\n                              <mml:mi>R<\/mml:mi>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>0<\/mml:mn>\n                              <mml:mspace\/>\n                              <mml:mtext>test<\/mml:mtext>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>2<\/mml:mn>\n                            <\/mml:mrow>\n                          <\/mml:msubsup>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>0.59<\/mml:mn>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    and RMSE\n                    <jats:sub>test<\/jats:sub>\n                    = 0.76. These values are in agreement with the maximum and minimum achievable\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$R_{0\\ test}^{2}$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msubsup>\n                            <mml:mrow>\n                              <mml:mi>R<\/mml:mi>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>0<\/mml:mn>\n                              <mml:mspace\/>\n                              <mml:mtext>test<\/mml:mtext>\n                            <\/mml:mrow>\n                            <mml:mrow>\n                              <mml:mn>2<\/mml:mn>\n                            <\/mml:mrow>\n                          <\/mml:msubsup>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    and RMSE\n                    <jats:sub>test<\/jats:sub>\n                    values of approximately 0.68 for both metrics. Confidence intervals for individual predictions were calculated from the standard deviation of the predictions from the individual models composing the ensembles. Finally, two substructure analysis pipelines singled out chemical substructures implicated in both potency and selectivity in agreement with the literature.\n                  <\/jats:p>","DOI":"10.1186\/s13321-014-0049-z","type":"journal-article","created":{"date-parts":[[2015,1,15]],"date-time":"2015-01-15T11:44:35Z","timestamp":1421322275000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["Prediction of the potency of mammalian cyclooxygenase inhibitors with ensemble proteochemometric modeling"],"prefix":"10.1186","volume":"7","author":[{"given":"Isidro","family":"Cortes-Ciriano","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel S","family":"Murrell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gerard JP","family":"van Westen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Bender","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Th\u00e9r\u00e8se E","family":"Malliavin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2015,1,16]]},"reference":[{"issue":"8","key":"49_CR1","doi-asserted-by":"publisher","first-page":"926","DOI":"10.1111\/j.1745-7254.2005.00150.x","volume":"26","author":"C Luo","year":"2005","unstructured":"Luo C, He Ml, Bohlin L. Is COX-2 a perpetrator or a protector? Selective COX-2 inhibitors remain controversial. Acta Pharm Sinic. 2005; 26(8):926\u2013933.","journal-title":"Acta Pharm Sinic"},{"issue":"25","key":"49_CR2","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1038\/newbio231232a0","volume":"231","author":"JR Vane","year":"1971","unstructured":"Vane JR. Inhibition of prostaglandin synthesis as a mechanism of action for aspirin-like drugs. Nat New Biol. 1971; 231(25):232\u2013235.","journal-title":"Nat New Biol"},{"issue":"14 Suppl","key":"49_CR3","first-page":"267","volume":"19","author":"M Fine","year":"2013","unstructured":"Fine M. Quantifying the impact of NSAID-associated adverse events. Am J Manag Care. 2013; 19(14 Suppl):267\u2013272.","journal-title":"Am J Manag Care"},{"issue":"7","key":"49_CR4","doi-asserted-by":"publisher","first-page":"2692","DOI":"10.1073\/pnas.88.7.2692","volume":"88","author":"WL Xie","year":"1991","unstructured":"Xie WL, Chipman JG, Robertson DL, Erikson RL, Simmons DL. Expression of a mitogen-responsive gene encoding prostaglandin synthase is regulated by mRNA splicing. Proc Nat Acad Sci. 1991; 88(7):2692\u20132696.","journal-title":"Proc Nat Acad Sci"},{"key":"49_CR5","doi-asserted-by":"publisher","first-page":"40","DOI":"10.4292\/wjgpt.v5.i1.40","volume":"5","author":"C Sostres","year":"2014","unstructured":"Sostres C, Gargallo CJ, Lanas A. Aspirin, cyclooxygenase inhibition and colorectal cancer. World J Gastrointest Pharmacol Ther. 2014; 5:40\u201349.","journal-title":"World J Gastrointest Pharmacol Ther"},{"issue":"13","key":"49_CR6","doi-asserted-by":"publisher","first-page":"7563","DOI":"10.1073\/pnas.96.13.7563","volume":"96","author":"TD Warner","year":"1999","unstructured":"Warner TD, Giuliano F, Vojnovic I, Bukasa A, Mitchell JA, Vane JR. Nonsteroid drug selectivities for cyclo-oxygenase-1 rather than cyclo-oxygenase-2 are associated with human gastrointestinal toxicity: a full in vitro analysis. Proc Nat Acad Sci. 1999; 96(13):7563\u20137568.","journal-title":"Proc Nat Acad Sci"},{"issue":"11","key":"49_CR7","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1056\/NEJMoa050493","volume":"352","author":"RS Bresalier","year":"2005","unstructured":"Bresalier RS, Sandler RS, Quan H, Bolognese JA, Oxenius B, Horgan K, Lines C, Riddell R, Morton D, Lanas A, Konstam MA, Baron JA. Adenomatous Polyp Prevention on Vioxx (APPROVe) Trial Investigators: Cardiovascular events associated with rofecoxib in a colorectal adenoma chemoprevention trial. N Engl J Med. 2005; 352(11):1092\u20131102.","journal-title":"N Engl J Med"},{"issue":"11","key":"49_CR8","doi-asserted-by":"publisher","first-page":"1081","DOI":"10.1056\/NEJMoa050330","volume":"352","author":"NA Nussmeier","year":"2005","unstructured":"Nussmeier NA, Whelton AA, Brown MT, Langford RM, Hoeft A, Parlow JL, Boyce SW, Verburg KM. Complications of the COX-2 inhibitors parecoxib and valdecoxib after cardiac surgery. N Engl J Med. 2005; 352(11):1081\u20131091.","journal-title":"N Engl J Med"},{"issue":"5","key":"49_CR9","first-page":"831","volume":"3","author":"LG Howes","year":"2007","unstructured":"Howes LG. Selective COX-2 inhibitors, NSAIDs and cardiovascular events - is celecoxib the safest choice?Ther Clin Risk Manag. 2007; 3(5):831\u2013845.","journal-title":"Ther Clin Risk Manag"},{"key":"49_CR10","first-page":"132ra54","volume":"132","author":"Y Yu","year":"2012","unstructured":"Yu Y, Ricciotti E, Scalia R, Tang SY, Grant G, Yu Z, Landesberg G, Crichton I, Wu W, Pure E, Funk CD, FitzGerald GA. Vascular COX-2 modulates blood pressure and thrombosis in mice. Sci Transl Med. 2012; 132:132ra54.","journal-title":"Sci Transl Med"},{"issue":"Suppl 3","key":"49_CR11","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/ar4174","volume":"15","author":"LJ Crofford","year":"2013","unstructured":"Crofford LJ. Use of NSAIDs in treating patients with arthritis. Arthritis Res Ther. 2013; 15(Suppl 3):S2.","journal-title":"Arthritis Res Ther"},{"issue":"9","key":"49_CR12","doi-asserted-by":"publisher","first-page":"1291","DOI":"10.1038\/nn.3480","volume":"16","author":"DJ Hermanson","year":"2013","unstructured":"Hermanson DJ, Hartley ND, Gamble-George J, Brown N, Shonesy BC, Kingsley PJ, Colbran RJ, Reese J, Marnett LJ, Patel S. Substrate-selective COX-2 inhibition decreases anxiety via endocannabinoid activation. Nat Neurosci. 2013; 16(9):1291\u20131298.","journal-title":"Nat Neurosci"},{"key":"49_CR13","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1038\/bjc.2014.127","volume":"110","author":"S Zhang","year":"2014","unstructured":"Zhang S, Zhang XQ, Ding XW, Yang RK, Huang SL, Kastelein F, Bruno M, Yu XJ, Zhou D, Zou XP. Cyclooxygenase inhibitors use is associated with reduced risk of esophageal adenocarcinoma in patients with Barretts esophagus: a meta-analysis. Br J Cancer. 2014; 110:2378\u20132388.","journal-title":"Br J Cancer"},{"key":"49_CR14","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.ejphar.2014.02.032","volume":"730","author":"RV Frolov","year":"2014","unstructured":"Frolov RV, Singh S. Celecoxib and ion channels: A story of unexpected discoveries. Eur J Pharmacol. 2014; 730:61\u201371.","journal-title":"Eur J Pharmacol"},{"issue":"8","key":"49_CR15","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1080\/10428190802108854","volume":"49","author":"P Robak","year":"2008","unstructured":"Robak P, Smolewski P, Robak T. The role of non-steroidal anti-inflammatory drugs in the risk of development and treatment of hematologic malignancies. Leuk Lymphoma. 2008; 49(8):1452\u20131462.","journal-title":"Leuk Lymphoma"},{"issue":"11","key":"49_CR16","doi-asserted-by":"publisher","first-page":"1131","DOI":"10.2174\/0929867003374273","volume":"7","author":"BC Moore","year":"2000","unstructured":"Moore BC, Simmons DL. COX-2 inhibition, apoptosis, and chemoprevention by nonsteroidal anti-inflammatory drugs. Curr Med Chem. 2000; 7(11):1131\u20131144.","journal-title":"Curr Med Chem"},{"issue":"2","key":"49_CR17","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/s12032-007-9015-1","volume":"25","author":"L Chen","year":"2008","unstructured":"Chen L, He Y, Huang H, Liao H, Wei W. Selective COX-2 inhibitor celecoxib combined with EGFR-TKI ZD1839 on non-small cell lung cancer cell lines: in vitro toxicity and mechanism study. Med Oncol. 2008; 25(2):161\u2013171.","journal-title":"Med Oncol"},{"issue":"4","key":"49_CR18","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1093\/jnci\/94.4.252","volume":"94","author":"MJ Thun","year":"2002","unstructured":"Thun MJ, Henley SJ, Patrono C. Nonsteroidal anti-inflammatory drugs as anticancer agents: mechanistic, pharmacologic, and clinical issues. J Nat Cancer Inst. 2002; 94(4):252\u2013266.","journal-title":"J Nat Cancer Inst"},{"issue":"7","key":"49_CR19","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1002\/mc.20409","volume":"47","author":"JW Soh","year":"2008","unstructured":"Soh JW, Kazi JU, Li H, Thompson WJ, Weinstein IB. Celecoxib-induced growth inhibition in SW480 colon cancer cells is associated with activation of protein kinase G. Mol Carcinog. 2008; 47(7):519\u2013525.","journal-title":"Mol Carcinog"},{"issue":"4","key":"49_CR20","doi-asserted-by":"publisher","first-page":"563","DOI":"10.2165\/00003495-199753040-00003","volume":"53","author":"JY Jouzeau","year":"1997","unstructured":"Jouzeau JY, Terlain B, Abid A, N\u00e9d\u00e9lec E, Netter P. Cyclo-oxygenase isoenzymes. How recent findings affect thinking about nonsteroidal anti-inflammatory drugs. Drugs. 1997; 53(4):563\u2013582.","journal-title":"Drugs"},{"issue":"6","key":"49_CR21","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1016\/j.amjmed.2008.01.045","volume":"121","author":"R Jones","year":"2008","unstructured":"Jones R, Rubin G, Berenbaum F, Scheiman J. Gastrointestinal and cardiovascular risks of nonsteroidal anti-inflammatory drugs. Am J Med. 2008; 121(6):464\u2013474.","journal-title":"Am J Med"},{"key":"49_CR22","doi-asserted-by":"publisher","first-page":"S23","DOI":"10.1111\/pme.12275","volume":"14 Suppl 1","author":"RV Curiel","year":"2013","unstructured":"Curiel RV, Katz JD. Mitigating the cardiovascular and renal effects of NSAIDs. Pain Med. 2013; 14 Suppl 1:S23\u201328.","journal-title":"Pain Med"},{"issue":"7","key":"49_CR23","doi-asserted-by":"publisher","first-page":"1425","DOI":"10.1021\/jm0613166","volume":"50","author":"AL Blobaum","year":"2007","unstructured":"Blobaum AL, Marnett LJ. Structural and functional basis of cyclooxygenase inhibition. J Med Chem. 2007; 50(7):1425\u20131441.","journal-title":"J Med Chem"},{"issue":"11","key":"49_CR24","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.2174\/0929867003374237","volume":"7","author":"G Dannhardt","year":"2000","unstructured":"Dannhardt G, Laufer S. Structural approaches to explain the selectivity of COX-2 inhibitors: is there a common pharmacophore?Curr Med Chem. 2000; 7(11):1101\u20131112.","journal-title":"Curr Med Chem"},{"issue":"10","key":"49_CR25","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.2174\/0929867003374417","volume":"7","author":"X de Leval","year":"2000","unstructured":"de Leval X, Delarge J, Somers F, de Tullio P, Henrotin Y, Pirotte B, Dogn\u00e9 JM. Recent advances in inducible cyclooxygenase (COX-2) inhibition. Curr Med Chem. 2000; 7(10):1041\u20131062.","journal-title":"Curr Med Chem"},{"issue":"34","key":"49_CR26","doi-asserted-by":"publisher","first-page":"3505","DOI":"10.2174\/138161207782794275","volume":"13","author":"RN Reddy","year":"2007","unstructured":"Reddy RN, Mutyala R, Aparoy P, Reddanna P, Reddy MR. Computer aided drug design approaches to develop cyclooxygenase based novel anti-inflammatory and anti-cancer drugs. Curr Pharm Des. 2007; 13(34):3505\u20133517.","journal-title":"Curr Pharm Des"},{"issue":"7","key":"49_CR27","doi-asserted-by":"publisher","first-page":"1629","DOI":"10.1016\/j.bmc.2004.01.027","volume":"12","author":"HJ Kim","year":"2004","unstructured":"Kim HJ, Chae CH, Yi KY, Park KL, Yoo Se. Computational studies of COX-2 inhibitors: 3D-QSAR and docking. Bioorg Med Chem Lett. 2004; 12(7):1629\u20131641.","journal-title":"Bioorg Med Chem Lett"},{"key":"49_CR28","doi-asserted-by":"crossref","unstructured":"Dube PN, Bule SS, Mokale SN, Kumbhare MR, Dighe PR, Ushir YV. Synthesis and biological evaluation of substituted 5-methyl-2-phenyl-1H-pyrazol-3(2H)-one derivatives as selective COX-2 inhibitors: Molecular docking study. Chem Biol Drug Des. 2014.","DOI":"10.1111\/cbdd.12324"},{"issue":"4","key":"49_CR29","first-page":"763","volume":"69","author":"GK Gupta","year":"2012","unstructured":"Gupta GK, Kumar A. 3D-QSAR studies of some tetrasubstituted pyrazoles as COX-II inhibitors. Acta Pol Pharm. 2012; 69(4):763\u2013772.","journal-title":"Acta Pol Pharm"},{"issue":"2","key":"49_CR30","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1016\/j.bmcl.2005.07.067","volume":"16","author":"T Narsinghani","year":"2006","unstructured":"Narsinghani T, Chaturvedi SC. QSAR analysis of meclofenamic acid analogues as selective COX-2 inhibitors. Bioorg Med Chem Lett. 2006; 16(2):461\u2013468.","journal-title":"Bioorg Med Chem Lett"},{"issue":"6","key":"49_CR31","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.1124\/mol.61.6.1465","volume":"61","author":"M Lapinsh","year":"2002","unstructured":"Lapinsh M, Prusis P, Lundstedt T, Wikberg JES. Proteochemometrics modeling of the interaction of amine g-protein coupled receptors with a diverse set of ligands. Mol Pharmacol. 2002; 61(6):1465\u20131475.","journal-title":"Mol Pharmacol"},{"key":"49_CR32","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1039\/c0md00165a","volume":"2","author":"GJP van Westen","year":"2011","unstructured":"van Westen GJP, Wegner JK, IJzerman AP, van Vlijmen HWT, Bender A. Proteochemometric modeling as a tool to design selective compounds and for extrapolating to novel targets. Med Chem Commun. 2011; 2:16\u201330.","journal-title":"Med Chem Commun"},{"key":"49_CR33","doi-asserted-by":"crossref","unstructured":"Cortes Ciriano I, Ain QU, Subramanian V, Lenselink EB, Mendez Lucio O, IJzerman AP, Wohlfahrt G, Prusis P, Malliavin T, van Westen G, Bender A. Polypharmacology modelling using proteochemometrics: recent developments and future prospects. Med Chem Comm. doi:10.1039\/C4MD00216D.","DOI":"10.1039\/C4MD00216D"},{"issue":"16","key":"49_CR34","doi-asserted-by":"publisher","first-page":"7010","DOI":"10.1021\/jm3003069","volume":"55","author":"GJP van Westen","year":"2012","unstructured":"van Westen GJP, van den Hoven OO, van der Pijl R, Mulder-Krieger T, de Vries H, Wegner AP, J\u00f6rg K an IJzerman, van Vlijmen HWT, Bender A. Identifying novel adenosine receptor ligands by simultaneous proteochemometric modeling of rat and human bioactivity data. J Med Chem. 2012; 55(16):7010\u20137020.","journal-title":"J Med Chem"},{"issue":"2","key":"49_CR35","doi-asserted-by":"publisher","first-page":"e1002899","DOI":"10.1371\/journal.pcbi.1002899","volume":"9","author":"GJP van Westen","year":"2013","unstructured":"van Westen GJP, Hendriks A, Wegner JK, IJzerman AP, van Vlijmen HW, Bender A. Significantly improved HIV inhibitor efficacy prediction employing proteochemometric models generated from antivirogram data. PLoS Comput Biol. 2013; 9(2):e1002899.","journal-title":"PLoS Comput Biol"},{"issue":"D1","key":"49_CR36","first-page":"D1100\u2014D1107","volume":"40","author":"A Gaulton","year":"2011","unstructured":"Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, Light Y, McGlinchey S, Michalovich D, Al-Lazikani B, Overington JP. ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 2011; 40(D1):D1100\u2014D1107.","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"49_CR37","doi-asserted-by":"publisher","first-page":"e61007","DOI":"10.1371\/journal.pone.0061007","volume":"8","author":"T Kalliokoski","year":"2013","unstructured":"Kalliokoski T, Kramer C, Vulpetti A, Gedeck P. Comparability of mixed IC50 data - a statistical analysis. PloS ONE. 2013; 8(4):e61007.","journal-title":"PloS ONE"},{"key":"49_CR38","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/nar\/28.1.235","volume":"28","author":"HM Berman","year":"2000","unstructured":"Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res. 2000; 28:235\u2013242.","journal-title":"Nucleic Acids Res"},{"key":"49_CR39","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1073\/pnas.0909765106","volume":"107","author":"G Rimon","year":"2010","unstructured":"Rimon G, Sidhu RS, Lauver DA, Lee JY, Sharma NP, Yuan C, Frieler RA, Trievel RC, Lucchesi BR, Smith WL. Coxibs interfere with the action of aspirin by binding tightly to one monomer of cyclooxygenase-1. Proc Nat Acad Sci. 2010; 107:28\u201333.","journal-title":"Proc Nat Acad Sci"},{"key":"49_CR40","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1038\/msb.2011.75","volume":"7","author":"F Sievers","year":"2011","unstructured":"Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, S\u00f6ding J, Thompson JD, Higgins DG. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 2011; 7:539. doi:10.1038\/msb.2011.75.","journal-title":"Mol Syst Biol"},{"key":"49_CR41","doi-asserted-by":"crossref","unstructured":"Murrell DS, Cortes-Ciriano I, van Westen G, Malliavin T, Bender A. Chemistry aware model builder (camb): an r package for predictive bioactivity modeling. 2014. http:\/\/github.com\/cambDI\/camb.","DOI":"10.1186\/s13321-015-0086-2"},{"issue":"5","key":"49_CR42","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1021\/ci100050t","volume":"50","author":"D Rogers","year":"2010","unstructured":"Rogers D, Hahn M. Extended-connectivity fingerprints. J Chem Inf Model. 2010; 50(5):742\u2013754.","journal-title":"J Chem Inf Model"},{"issue":"3","key":"49_CR43","first-page":"199","volume":"9","author":"RC Glem","year":"2006","unstructured":"Glem RC, Bender A, Arnby CH, Carlsson L, Boyer S, Smith J. Circular fingerprints: flexible molecular descriptors with applications from physical chemistry to ADME. IDrugs. 2006; 9(3):199\u2013204.","journal-title":"IDrugs"},{"key":"49_CR44","unstructured":"Landrum G. RDKit Open-source cheminformatics. 2006."},{"key":"49_CR45","unstructured":"Cortes-Ciriano I. FingerprintCalculator. 2014. http:\/\/github.com\/isidroc\/FingerprintCalculator."},{"issue":"7","key":"49_CR46","doi-asserted-by":"publisher","first-page":"1466","DOI":"10.1002\/jcc.21707","volume":"32","author":"CW Yap","year":"2011","unstructured":"Yap CW. PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints. J Comput Chem. 2011; 32(7):1466\u20131474.","journal-title":"J Comput Chem"},{"key":"49_CR47","unstructured":"Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O\u2019Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H. vegan: Community Ecology Package; 2013. [R package version 2.0-9]."},{"issue":"14","key":"49_CR48","doi-asserted-by":"publisher","first-page":"2481","DOI":"10.1021\/jm9700575","volume":"41","author":"M Sandberg","year":"1998","unstructured":"Sandberg M, Eriksson L, Jonsson J, Sj\u00f6str\u00f6m M, Wold S. New chemical descriptors relevant for the design of biologically active peptides. A multivariate characterization of 87 amino acids. J Med Chem. 1998; 41(14):2481\u20132491.","journal-title":"J Med Chem"},{"issue":"5","key":"49_CR49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","volume":"28","author":"M Kuhn","year":"2008","unstructured":"Kuhn M. Building predictive models in R using the caret package. J Stat Soft. 2008; 28(5):1\u201326.","journal-title":"J Stat Soft"},{"key":"49_CR50","unstructured":"Mayer Z. caretEnsemble: Framework for combining caret models into ensembles. [R package version 1.0]. 2013."},{"key":"49_CR51","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-6849-3","volume-title":"Applied Predictive Modeling","author":"M Kuhn","year":"2013","unstructured":"Kuhn M, Johnson K. Applied Predictive Modeling. New York, NY: Springer New York; 2013."},{"issue":"2","key":"49_CR52","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1021\/ci025626i","volume":"43","author":"DM Hawkins","year":"2003","unstructured":"Hawkins DM, Basak SC, Mills D. Assessing model fit by cross-validation. J Chem Inf Model. 2003; 43(2):579\u2013586.","journal-title":"J Chem Inf Model"},{"issue":"6","key":"49_CR53","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/s10822-014-9743-1","volume":"28","author":"J Brown","year":"2014","unstructured":"Brown J, Okuno Y, Marcou G, Varnek A, Horvath D. Computational chemogenomics: Is it more than inductive transfer?J Comput Aided Mol Des. 2014; 28(6):597\u2013618. [10.1007\/s10822-014-9743-1].","journal-title":"J Comput Aided Mol Des"},{"issue":"4","key":"49_CR54","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/S1093-3263(01)00123-1","volume":"20","author":"A Golbraikh","year":"2002","unstructured":"Golbraikh A, Tropsha A. Beware of q2!J Mol Graphics Modell. 2002; 20(4):269\u2013276.","journal-title":"J Mol Graphics Modell"},{"key":"49_CR55","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1201\/9781420082999-c7","volume":"33","author":"A Tropsha","year":"2010","unstructured":"Tropsha A, Golbraikh A. Predictive quantitative structure-activity relationships modeling. Handb Chemoinform Algorithms. 2010; 33:211.","journal-title":"Handb Chemoinform Algorithms"},{"key":"49_CR56","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1002\/qsar.200390007","volume":"22","author":"A Tropsha","year":"2003","unstructured":"Tropsha A, Gramatica P, Gombar VK. The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci. 2003; 22:69\u201377.","journal-title":"QSAR Comb Sci"},{"issue":"11","key":"49_CR57","doi-asserted-by":"publisher","first-page":"5165","DOI":"10.1021\/jm300131x","volume":"55","author":"C Kramer","year":"2012","unstructured":"Kramer C, Kalliokoski T, Gedeck P, Vulpetti A. The experimental uncertainty of heterogeneous public Ki data. J Med Chem. 2012; 55(11):5165\u20135173.","journal-title":"J Med Chem"},{"key":"49_CR58","doi-asserted-by":"crossref","unstructured":"Kramer C, Lewis R. QSARs, data and error in the modern age of drug discovery. Curr Top Med Chem. 2012-09-01T00:00:00;12(17):1896\u20131902.","DOI":"10.2174\/156802612804547380"},{"issue":"3","key":"49_CR59","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1021\/ci300004n","volume":"52","author":"RP Sheridan","year":"2012","unstructured":"Sheridan RP. Three useful dimensions for domain applicability in QSAR models using random forest. J Chem Inf Model. 2012; 52(3):814\u2013823.","journal-title":"J Chem Inf Model"},{"key":"49_CR60","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2000","unstructured":"Friedman JH. Greedy function approximation: a gradient boosting machine. Ann Stat. 2000; 29:1189\u20131232.","journal-title":"Ann Stat"},{"key":"49_CR61","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L. Random forests. Mach Learn. 2001; 45:5\u201332.","journal-title":"Mach Learn"},{"issue":"10","key":"49_CR62","doi-asserted-by":"publisher","first-page":"e1000173","DOI":"10.1371\/journal.pcbi.1000173","volume":"4","author":"A Ben-Hur","year":"2008","unstructured":"Ben-Hur A, Ong CS, Sonnenburg S, Sch\u00f6lkopf B, R\u00e4tsch G. Support vector machines and kernels for computational biology. PLoS Comput Biol. 2008; 4(10):e1000173.","journal-title":"PLoS Comput Biol"},{"key":"49_CR63","doi-asserted-by":"crossref","unstructured":"Caruana R, Niculescu-Mizil A, Crew G, Ksikes A. Ensemble Selection from Libraries of Models. New York, NY, USA: ACM. Banff, Alberta, Canada; 2004.","DOI":"10.1145\/1015330.1015432"},{"issue":"11","key":"49_CR64","doi-asserted-by":"publisher","first-page":"2837","DOI":"10.1021\/ci400482e","volume":"53","author":"RP Sheridan","year":"2013","unstructured":"Sheridan RP. Using random forest to model the domain applicability of another random forest model. J Chem Inf Model. 2013; 53(11):2837\u20132850.","journal-title":"J Chem Inf Model"},{"issue":"3","key":"49_CR65","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1007\/s10822-013-9639-5","volume":"27","author":"DJ Wood","year":"2013","unstructured":"Wood DJ, Carlsson L, Eklund M, Norinder U, St\u00e5 lring J. QSAR with experimental and predictive distributions: an information theoretic approach for assessing model quality. J Comput Aided Mol Des. 2013; 27(3):203\u2013219.","journal-title":"J Comput Aided Mol Des"},{"issue":"7","key":"49_CR66","doi-asserted-by":"publisher","first-page":"1762","DOI":"10.1021\/ci9000579","volume":"49","author":"H Dragos","year":"2009","unstructured":"Dragos H, Gilles M, Alexandre V. Predicting the predictability: a unified approach to the applicability domain problem of QSAR models. J Chem Inf Model. 2009; 49(7):1762\u20131776.","journal-title":"J Chem Inf Model"},{"issue":"11","key":"49_CR67","doi-asserted-by":"publisher","first-page":"e27518","DOI":"10.1371\/journal.pone.0027518","volume":"6","author":"GJP van Westen","year":"2011","unstructured":"van Westen GJP, Wegner JK, Geluykens P, Kwanten L, Vereycken I, Peeters A, IJzerman AP, van Vlijmen HW, Bender A. Which compound to select in lead optimization? Prospectively validated proteochemometric models guide preclinical development. PLoS ONE. 2011; 6(11):e27518.","journal-title":"PLoS ONE"},{"key":"49_CR68","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1186\/1758-2946-6-35","volume":"6","author":"I Cortes Ciriano","year":"2014","unstructured":"Cortes Ciriano I, van Westen G, Lenselink EB, Murrell DS, Bender A, Malliavin T. Proteochemometrics modeling in a bayesian framework. J Cheminf. 2014; 6:35.","journal-title":"J Cheminf"},{"key":"49_CR69","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/1758-2946-3-11","volume":"3","author":"L Rosenbaum","year":"2011","unstructured":"Rosenbaum L, Hinselmann G, Jahn A, Zell A. Interpreting linear support vector machine models with heat map molecule coloring. J Cheminf. 2011; 3:11.","journal-title":"J Cheminf"},{"key":"49_CR70","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1186\/1758-2946-1-22","volume":"1","author":"BM Spowage","year":"2009","unstructured":"Spowage BM, Bruce CL, Hirst JD. Interpretable correlation descriptors for quantitative structure-activity relationships. J Cheminf. 2009; 1:22.","journal-title":"J Cheminf"},{"issue":"9","key":"49_CR71","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1002\/minf.201100136","volume":"31","author":"G Marcou","year":"2012","unstructured":"Marcou G, Horvath D, Solov\u2019ev V, Arrault A, Vayer P, Varnek A. Interpretability of SAR\/QSAR Models of any complexity by atomic contributions. Mol Inform. 2012; 31(9):639\u2013642.","journal-title":"Mol Inform"},{"key":"49_CR72","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1002\/minf.201300029","volume":"32","author":"PG Polishchuk","year":"2013","unstructured":"Polishchuk PG, Kuzmin VE, Artemenko AG, Muratov EN. Universal approach for structural interpretation of QSAR\/QSPR models. Mol Inform. 2013; 32:843\u2013853.","journal-title":"Mol Inform"},{"key":"49_CR73","doi-asserted-by":"publisher","first-page":"e1.002333","DOI":"10.1371\/journal.pcbi.1002333","volume":"8","author":"FA Kruger","year":"2012","unstructured":"Kruger FA, Overington JP. Global analysis of small molecule binding to related protein targets. PLoS Comput Biol. 2012; 8:e1.002333.","journal-title":"PLoS Comput Biol"},{"key":"49_CR74","doi-asserted-by":"publisher","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. New York: Chapman & Hall; 1993."},{"key":"49_CR75","doi-asserted-by":"publisher","first-page":"255","DOI":"10.2307\/2532051","volume":"45","author":"LI Lin","year":"1989","unstructured":"Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989; 45:255\u2013268.","journal-title":"Biometrics"},{"issue":"2","key":"49_CR76","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1177\/1536867X0200200206","volume":"2","author":"TJ Steichen","year":"2002","unstructured":"Steichen TJ, Cox NJ. A note on the concordance correlation coefficient. Stata J. 2002; 2(2):183\u2013189(7).","journal-title":"Stata J"},{"issue":"7\u20139","key":"49_CR77","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s10822-004-4077-z","volume":"18","author":"R Clark","year":"2004","unstructured":"Clark R, Fox P. Statistical variation in progressive scrambling. J Comput-Aided Mol Design. 2004; 18(7\u20139):563\u2013576.","journal-title":"J Comput-Aided Mol Design"},{"issue":"7\u20138","key":"49_CR78","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1016\/j.drudis.2009.01.012","volume":"14","author":"SP Brown","year":"2009","unstructured":"Brown SP, Muchmore SW, Hajduk PJ. Healthy skepticism: assessing realistic model performance. Drug Discov Today. 2009; 14(7\u20138):420\u2013427.","journal-title":"Drug Discov Today"},{"issue":"7","key":"49_CR79","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1021\/jm00033a017","volume":"37","author":"WW Wilkerson","year":"1994","unstructured":"Wilkerson WW, Galbraith W, Gans-Brangs K, Grubb M, Hewes WE, Jaffee B, Kenney JP, Kerr J, Wong N. Antiinflammatory 4,5-Diarylpyrroles: Synthesis and QSAR. J Med Chem. 1994; 37(7):988\u2013998.","journal-title":"J Med Chem"},{"issue":"20","key":"49_CR80","doi-asserted-by":"publisher","first-page":"3895","DOI":"10.1021\/jm00020a002","volume":"38","author":"WW Wilkerson","year":"1995","unstructured":"Wilkerson WW, Copeland RA, Covington M, Trzaskos JM. Antiinflammatory 4,5-Diarylpyrroles. 2. activity as a function of cyclooxygenase-2 inhibition. J Med Chem. 1995; 38(20):3895\u20133901.","journal-title":"J Med Chem"},{"issue":"11","key":"49_CR81","doi-asserted-by":"publisher","first-page":"1619","DOI":"10.1021\/jm970036a","volume":"40","author":"IK Khanna","year":"1997","unstructured":"Khanna IK, Weier RM, Yu Y, Collins PW, Miyashiro JM, Koboldt CM, Veenhuizen AW, Currie JL, Seibert K, Isakson PC. 1,2-Diarylpyrroles as potent and selective inhibitors of cyclooxygenase-2. J Med Chem. 1997; 40(11):1619\u20131633.","journal-title":"J Med Chem"},{"issue":"22","key":"49_CR82","doi-asserted-by":"publisher","first-page":"3187","DOI":"10.1016\/S0960-894X(99)00560-0","volume":"9","author":"CK Lau","year":"1999","unstructured":"Lau CK, Brideau C, Chan CC, Charleson S, Cromlish WA, Ethier D, Gauthier JY, Gordon R, Guay J, Kargman S, Li CS, Prasit P, Reindeau D, Th\u00e9rien M, Visco DM, Xu L. Synthesis and biological evaluation of 3-heteroaryloxy-4-phenyl-2(5H)-furanones as selective COX-2 inhibitors. Bioorg Med Chem Lett. 1999; 9(22):3187\u20133192.","journal-title":"Bioorg Med Chem Lett"},{"issue":"2","key":"49_CR83","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/S0223-5234(01)01330-7","volume":"37","author":"G Dannhardt","year":"2002","unstructured":"Dannhardt G, Fiebich BL, Schweppenhauser J. COX-1\/COX-2 inhibitors based on the methanone moiety. Eur J Med Chem. 2002; 37(2):147\u2013161.","journal-title":"Eur J Med Chem"},{"issue":"15","key":"49_CR84","doi-asserted-by":"publisher","first-page":"4830","DOI":"10.1016\/j.bmc.2012.05.063","volume":"20","author":"M Scholz","year":"2012","unstructured":"Scholz M, Blobaum AL, Marnett LJ, Hey-Hawkins E. ortho-Carbaborane derivatives of indomethacin as cyclooxygenase (COX)-2 selective inhibitors. Bioorg Med Chem Lett. 2012; 20(15):4830\u20134837.","journal-title":"Bioorg Med Chem Lett"},{"key":"49_CR85","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.ejmech.2012.01.053","volume":"50","author":"S Hayashi","year":"2012","unstructured":"Hayashi S, Ueno N, Murase A, Nakagawa Y, Takada J. Novel acid-type cyclooxygenase-2 inhibitors: design, synthesis, and structure\u2013activity relationship for anti-inflammatory drug. Eur J Med Chem. 2012; 50:179\u2013195.","journal-title":"Eur J Med Chem"},{"issue":"8","key":"49_CR86","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1038\/nmeth.2016","volume":"9","author":"D Marbach","year":"2012","unstructured":"Marbach D, Costello JC, Kuffner R, Vega NM, Prill RJ, Camacho DM, Allison KR, Kellis M, Collins JJ, Stolovitzky G. Wisdom of crowds for robust gene network inference. Nat Methods. 2012; 9(8):796\u2013804.","journal-title":"Nat Methods"},{"key":"49_CR87","doi-asserted-by":"crossref","unstructured":"Costello JC, Heiser LM, Georgii E, G\u00f6nen M, Menden MP, Wang NJ, Bansal M, Ammad-Ud-Din M, Hintsanen P, Khan SA, Mpindi JP, Kallioniemi O, Honkela A, Aittokallio T, Wennerberg K, Collins JJ, Gallahan D, Singer D, Saez-Rodriguez J, Kaski S, Gray JW, Stolovitzky G. A community effort to assess and improve drug sensitivity prediction algorithms. Nat Biotechnol. 2014. doi:10.1038\/nbt.2877.","DOI":"10.1038\/nbt.2877"},{"key":"49_CR88","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1146\/annurev.ps.46.020195.003021","volume":"46","author":"JP Shaffer","year":"1995","unstructured":"Shaffer JP. Multiple hypothesis testing. Ann Rev Psychol. 1995; 46:561\u2013584.","journal-title":"Ann Rev Psychol"},{"issue":"9","key":"49_CR89","doi-asserted-by":"publisher","first-page":"3786","DOI":"10.1021\/jm500317a","volume":"57","author":"C Kramer","year":"2014","unstructured":"Kramer C, Fuchs JE, Whitebread S, Gedeck P, Liedl KR. Matched molecular pair analysis: significance and the impact of experimental uncertainty. J Med Chem. 2014; 57(9):3786\u20133802.","journal-title":"J Med Chem"},{"issue":"21","key":"49_CR90","doi-asserted-by":"publisher","first-page":"2518","DOI":"10.1093\/bioinformatics\/btn479","volume":"24","author":"J Klekota","year":"2008","unstructured":"Klekota J, Roth FP. Chemical substructures that enrich for biological activity. Bioinformatics. 2008; 24(21):2518\u20132525.","journal-title":"Bioinformatics"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-014-0049-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s13321-014-0049-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-014-0049-z","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13321-014-0049-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,2]],"date-time":"2021-09-02T03:45:19Z","timestamp":1630554319000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/s13321-014-0049-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,1,16]]},"references-count":90,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,12]]}},"alternative-id":["49"],"URL":"https:\/\/doi.org\/10.1186\/s13321-014-0049-z","relation":{},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,1,16]]},"assertion":[{"value":"1 August 2014","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2014","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 2015","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"1"}}