{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T22:01:39Z","timestamp":1763071299522},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["SFRH\/BD\/147629\/2019","UIDB\/00006\/2020","UIDB\/00006\/2020"],"award-info":[{"award-number":["SFRH\/BD\/147629\/2019","UIDB\/00006\/2020","UIDB\/00006\/2020"]}]},{"DOI":"10.13039\/501100014434","name":"Polish National Agency for Academic Exchange","doi-asserted-by":"crossref","award":["PPN\/ULM\/2020\/1\/00069\/U\/00001"],"award-info":[{"award-number":["PPN\/ULM\/2020\/1\/00069\/U\/00001"]}],"id":[{"id":"10.13039\/501100014434","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BioData Mining"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to\u00a0the availability of multi-sera data. The analysis of these data is typically divided into a feature selection phase followed by a predictive one where several models are constructed for predicting\u00a0the outcome of interest. A key question in the analysis is to determine which antibodies\u00a0 should be included in the predictive stage and whether they should be included in the original  or  a transformed scale (i.e. binary\/dichotomized).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>To answer this question, we developed three approaches for antibody selection in the context of predicting clinical malaria: (i) a basic and simple approach based on selecting antibodies via the nonparametric Mann\u2013Whitney-Wilcoxon test; (ii) an optimal dychotomizationdichotomization approach where each antibody was selected according to the optimal cut-off via maximization of the chi-squared (\u03c7<jats:sup>2<\/jats:sup>) statistic for two-way tables; (iii) a hybrid parametric\/non-parametric approach that integrates Box-Cox transformation followed by a t-test, together with the use of finite mixture models and the Mann\u2013Whitney-Wilcoxon test as a last resort. We illustrated the application of these three approaches with published serological data of 36 Plasmodium falciparum antigens for predicting clinical malaria in 121 Kenyan children. The predictive analysis was based on a Super Learner where predictions from multiple classifiers including the Random Forest were pooled together.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Our results led to almost similar areas under the Receiver Operating Characteristic curves of 0.72 (95% CI\u2009=\u2009[0.62, 0.82]), 0.80 (95% CI\u2009=\u2009[0.71, 0.89]), 0.79 (95% CI\u2009=\u2009[0.7, 0.88]) for the simple, dichotomization and hybrid approaches, respectively. These approaches were based on 6, 20, and 16 antibodies, respectively.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The three feature selection strategies provided a better predictive performance of the outcome when compared to the previous results relying on Random Forest including all the 36 antibodies (AUC\u2009=\u20090.68, 95% CI\u2009=\u2009[0.57;0.79]). Given the similar predictive performance, we recommended that the three strategies should be used in conjunction in the same data set and selected according to their complexity.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s13040-024-00354-4","type":"journal-article","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T17:02:27Z","timestamp":1706202147000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data"],"prefix":"10.1186","volume":"17","author":[{"given":"Andr\u00e9","family":"Fonseca","sequence":"first","affiliation":[]},{"given":"Mikolaj","family":"Spytek","sequence":"additional","affiliation":[]},{"given":"Przemys\u0142aw","family":"Biecek","sequence":"additional","affiliation":[]},{"given":"Clara","family":"Cordeiro","sequence":"additional","affiliation":[]},{"given":"Nuno","family":"Sep\u00falveda","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,25]]},"reference":[{"issue":"1","key":"354_CR1","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1002\/cyto.a.10047","volume":"45","author":"KL Kellar","year":"2001","unstructured":"Kellar KL, Kalwar RR, Dubois KA, Crouse D, Chafin WD, Kane BE. Multiplexed fluorescent bead-based immunoassays for quantitation of human cytokines in serum and culture supernatants. Cytometry. 2001;45(1):27\u201336. https:\/\/doi.org\/10.1002\/cyto.a.10047.","journal-title":"Cytometry"},{"issue":"4","key":"354_CR2","doi-asserted-by":"publisher","first-page":"1702","DOI":"10.1128\/IAI.01539-07","volume":"76","author":"T Tsuboi","year":"2008","unstructured":"Tsuboi T, Takeo S, Iriko H, et al. Wheat Germ Cell-Free System-Based Production of Malaria Proteins for Discovery of Novel Vaccine Candidates. Infect Immun. 2008;76(4):1702\u20138. https:\/\/doi.org\/10.1128\/IAI.01539-07.","journal-title":"Infect Immun"},{"issue":"1","key":"354_CR3","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1186\/s12936-018-2365-7","volume":"17","author":"I Ubillos","year":"2018","unstructured":"Ubillos I, Campo JJ, Jim\u00e9nez A, Doba\u00f1o C. Development of a high-throughput flexible quantitative suspension array assay for IgG against multiple Plasmodium falciparum antigens. Malar J. 2018;17(1):216. https:\/\/doi.org\/10.1186\/s12936-018-2365-7.","journal-title":"Malar J"},{"issue":"1","key":"354_CR4","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1186\/1475-2875-7-108","volume":"7","author":"GK Cham","year":"2008","unstructured":"Cham GK, Kurtis J, Lusingu J, Theander TG, Jensen AT, Turner L. A semi-automated multiplex high-throughput assay for measuring IgG antibodies against Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) domains in small volumes of plasma. Malar J. 2008;7(1):108. https:\/\/doi.org\/10.1186\/1475-2875-7-108.","journal-title":"Malar J"},{"issue":"6","key":"354_CR5","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1016\/j.vaccine.2017.01.001","volume":"35","author":"BN Kanoi","year":"2017","unstructured":"Kanoi BN, Takashima E, Morita M, et al. Antibody profiles to wheat germ cell-free system synthesized Plasmodium falciparum proteins correlate with protection from symptomatic malaria in Uganda. Vaccine. 2017;35(6):873\u201381. https:\/\/doi.org\/10.1016\/j.vaccine.2017.01.001.","journal-title":"Vaccine"},{"key":"354_CR6","doi-asserted-by":"publisher","unstructured":"Kanoi BN, Nagaoka H, White MT, et al. Global Repertoire of Human Antibodies Against Plasmodium falciparum RIFINs, SURFINs, and STEVORs in a Malaria Exposed Population. Front Immunol. 2020;11. https:\/\/doi.org\/10.3389\/fimmu.2020.00893","DOI":"10.3389\/fimmu.2020.00893"},{"issue":"1","key":"354_CR7","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1074\/mcp.RA118.001256","volume":"19","author":"C Proietti","year":"2020","unstructured":"Proietti C, Krause L, Trieu A, et al. Immune Signature Against Plasmodium falciparum Antigens Predicts Clinical Immunity in Distinct Malaria Endemic Communities. Mol Cell Proteomics. 2020;19(1):101\u201313. https:\/\/doi.org\/10.1074\/mcp.RA118.001256.","journal-title":"Mol Cell Proteomics"},{"key":"354_CR8","doi-asserted-by":"publisher","unstructured":"Osier FH, Mackinnon MJ, Crosnier C, et al. New antigens for a multicomponent blood-stage malaria vaccine. Sci Transl Med. 2014;6(247). https:\/\/doi.org\/10.1126\/scitranslmed.3008705","DOI":"10.1126\/scitranslmed.3008705"},{"issue":"5","key":"354_CR9","doi-asserted-by":"publisher","first-page":"2240","DOI":"10.1128\/IAI.01585-07","volume":"76","author":"FHA Osier","year":"2008","unstructured":"Osier FHA, Fegan G, Polley SD, et al. Breadth and Magnitude of Antibody Responses to Multiple Plasmodium falciparum Merozoite Antigens Are Associated with Protection from Clinical Malaria. Infect Immun. 2008;76(5):2240\u20138. https:\/\/doi.org\/10.1128\/IAI.01585-07.","journal-title":"Infect Immun"},{"key":"354_CR10","doi-asserted-by":"publisher","unstructured":"Fran\u00e7a CT, White MT, He WQ, et al. Identification of highly-protective combinations of Plasmodium vivax recombinant proteins for vaccine development. Elife. 2017;6. https:\/\/doi.org\/10.7554\/eLife.28673","DOI":"10.7554\/eLife.28673"},{"key":"354_CR11","doi-asserted-by":"publisher","unstructured":"Van den Hoogen LL, Stresman G, Pr\u00e9sum\u00e9 J, et al. Selection of Antibody Responses Associated With Plasmodium falciparum Infections in the Context of Malaria Elimination. Front Immunol. 2020;11. https:\/\/doi.org\/10.3389\/fimmu.2020.00928","DOI":"10.3389\/fimmu.2020.00928"},{"issue":"5","key":"354_CR12","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1038\/s41591-020-0841-4","volume":"26","author":"RJ Longley","year":"2020","unstructured":"Longley RJ, White MT, Takashima E, et al. Development and validation of serological markers for detecting recent Plasmodium vivax infection. Nat Med. 2020;26(5):741\u20139. https:\/\/doi.org\/10.1038\/s41591-020-0841-4.","journal-title":"Nat Med"},{"issue":"32","key":"354_CR13","doi-asserted-by":"publisher","first-page":"E4438","DOI":"10.1073\/pnas.1501705112","volume":"112","author":"DA Helb","year":"2015","unstructured":"Helb DA, Tetteh KKA, Felgner PL, et al. Novel serologic biomarkers provide accurate estimates of recent Plasmodium falciparum exposure for individuals and communities. Proc Natl Acad Sci. 2015;112(32):E4438\u201347. https:\/\/doi.org\/10.1073\/pnas.1501705112.","journal-title":"Proc Natl Acad Sci"},{"issue":"15","key":"354_CR14","doi-asserted-by":"publisher","first-page":"6958","DOI":"10.1073\/pnas.1001323107","volume":"107","author":"PD Crompton","year":"2010","unstructured":"Crompton PD, Kayala MA, Traore B, et al. A prospective analysis of the Ab response to Plasmodium falciparum before and after a malaria season by protein microarray. Proc Natl Acad Sci. 2010;107(15):6958\u201363. https:\/\/doi.org\/10.1073\/pnas.1001323107.","journal-title":"Proc Natl Acad Sci"},{"issue":"10","key":"354_CR15","doi-asserted-by":"publisher","first-page":"e1005812","DOI":"10.1371\/journal.pcbi.1005812","volume":"13","author":"JJ Valletta","year":"2017","unstructured":"Valletta JJ, Recker M. Identification of immune signatures predictive of clinical protection from malaria. PLoS Comput Biol. 2017;13(10):e1005812. https:\/\/doi.org\/10.1371\/journal.pcbi.1005812.","journal-title":"PLoS Comput Biol"},{"issue":"1","key":"354_CR16","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.1038\/s41598-020-57876-0","volume":"10","author":"LL Van den Hoogen","year":"2020","unstructured":"Van den Hoogen LL, Pr\u00e9sum\u00e9 J, Romilus I, et al. Quality control of multiplex antibody detection in samples from large-scale surveys: the example of malaria in Haiti. Sci Rep. 2020;10(1):1135. https:\/\/doi.org\/10.1038\/s41598-020-57876-0.","journal-title":"Sci Rep"},{"key":"354_CR17","doi-asserted-by":"publisher","first-page":"26","DOI":"10.12688\/wellcomeopenres.14950.2","volume":"4","author":"L Wu","year":"2020","unstructured":"Wu L, Hall T, Ssewanyana I, et al. Optimisation and standardisation of a multiplex immunoassay of diverse Plasmodium falciparum antigens to assess changes in malaria transmission using sero-epidemiology. Wellcome Open Res. 2020;4:26. https:\/\/doi.org\/10.12688\/wellcomeopenres.14950.2.","journal-title":"Wellcome Open Res"},{"issue":"1","key":"354_CR18","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1186\/1475-2875-9-317","volume":"9","author":"E Ambrosino","year":"2010","unstructured":"Ambrosino E, Dumoulin C, Orlandi-Pradines E, et al. A multiplex assay for the simultaneous detection of antibodies against 15 Plasmodium falciparum and Anopheles gambiae saliva antigens. Malar J. 2010;9(1):317. https:\/\/doi.org\/10.1186\/1475-2875-9-317.","journal-title":"Malar J"},{"issue":"1","key":"354_CR19","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(1):5\u201332. https:\/\/doi.org\/10.1023\/A:1010933404324.","journal-title":"Mach Learn"},{"key":"354_CR20","doi-asserted-by":"publisher","unstructured":"Ahmed FYH, Ali YH, Shamsuddin SM. Using K-Fold Cross Validation Proposed Models for Spikeprop Learning Enhancements. International Journal of Engineering & Technology. 2018;7(411):145. https:\/\/doi.org\/10.14419\/ijet.v7i4.11.20790","DOI":"10.14419\/ijet.v7i4.11.20790"},{"key":"354_CR21","doi-asserted-by":"publisher","unstructured":"Wright MN, Ziegler A. ranger\u202f: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R. J Stat Softw. 2017;77(1) https:\/\/doi.org\/10.18637\/jss.v077.i01","DOI":"10.18637\/jss.v077.i01"},{"issue":"7","key":"354_CR22","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","volume":"30","author":"AP Bradley","year":"1997","unstructured":"Bradley AP. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognit. 1997;30(7):1145\u201359. https:\/\/doi.org\/10.1016\/S0031-3203(96)00142-2.","journal-title":"Pattern Recognit"},{"key":"354_CR23","unstructured":"Kuhn M. caret: Classification and Regression Training. Published online 2022. Accessed May 26, 2022. https:\/\/CRAN.R-project.org\/package=caret"},{"issue":"1","key":"354_CR24","doi-asserted-by":"publisher","first-page":"13","DOI":"10.20982\/tqmp.04.1.p013","volume":"4","author":"N Nachar","year":"2008","unstructured":"Nachar N. The Mann-Whitney U: A Test for Assessing Whether Two Independent Samples Come from the Same Distribution. Tutor Quant Methods Psychol. 2008;4(1):13\u201320. https:\/\/doi.org\/10.20982\/tqmp.04.1.p013.","journal-title":"Tutor Quant Methods Psychol"},{"key":"354_CR25","doi-asserted-by":"publisher","unstructured":"Domingues TD, Grabowska AD, Lee JS, et al. Herpesviruses Serology Distinguishes Different Subgroups of Patients From the United Kingdom Myalgic Encephalomyelitis\/Chronic Fatigue Syndrome Biobank. Front Med (Lausanne). 2021;8. https:\/\/doi.org\/10.3389\/fmed.2021.686736","DOI":"10.3389\/fmed.2021.686736"},{"issue":"34","key":"354_CR26","doi-asserted-by":"publisher","first-page":"16955","DOI":"10.1073\/pnas.1902623116","volume":"116","author":"K Tengvall","year":"2019","unstructured":"Tengvall K, Huang J, Hellstr\u00f6m C, et al. Molecular mimicry between Anoctamin 2 and Epstein-Barr virus nuclear antigen 1 associates with multiple sclerosis risk. Proc Natl Acad Sci. 2019;116(34):16955\u201360. https:\/\/doi.org\/10.1073\/pnas.1902623116.","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"354_CR27","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1080\/03610918.2014.957839","volume":"46","author":"\u00d6 Asar","year":"2017","unstructured":"Asar \u00d6, Ilk O, Dag O. Estimating Box-Cox power transformation parameter via goodness-of-fit tests. Commun Stat Simul Comput. 2017;46(1):91\u2013105. https:\/\/doi.org\/10.1080\/03610918.2014.957839.","journal-title":"Commun Stat Simul Comput"},{"key":"354_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/738030","volume":"2015","author":"N Sep\u00falveda","year":"2015","unstructured":"Sep\u00falveda N, Stresman G, White MT, Drakeley CJ. Current Mathematical Models for Analyzing Anti-Malarial Antibody Data with an Eye to Malaria Elimination and Eradication. J Immunol Res. 2015;2015:1\u201321. https:\/\/doi.org\/10.1155\/2015\/738030.","journal-title":"J Immunol Res"},{"key":"354_CR29","doi-asserted-by":"publisher","DOI":"10.1101\/2021.03.08.21252807","author":"TD Domingues","year":"2021","unstructured":"Domingues TD, Mouri\u00f1o H, Sep\u00falveda N. Analysis of antibody data using Finite Mixture Models based on Scale Mixtures of Skew-Normal distributions. Published online. 2021. https:\/\/doi.org\/10.1101\/2021.03.08.21252807.","journal-title":"Published online"},{"key":"354_CR30","doi-asserted-by":"publisher","unstructured":"Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics. 2001;29(4). https:\/\/doi.org\/10.1214\/aos\/1013699998","DOI":"10.1214\/aos\/1013699998"},{"key":"354_CR31","doi-asserted-by":"publisher","unstructured":"Van der Laan MJ, Polley EC, Hubbard AE. Super Learner. Stat Appl Genet Mol Biol. 2007;6(1). https:\/\/doi.org\/10.2202\/1544-6115.1309","DOI":"10.2202\/1544-6115.1309"},{"key":"354_CR32","unstructured":"Polley E, LeDell E, Kennedy C, Van der Laan M. SuperLearner: Super Learner Prediction. Published online 2021. Accessed March 13, 2023. https:\/\/CRAN.R-project.org\/package=SuperLearner"},{"key":"354_CR33","doi-asserted-by":"publisher","unstructured":"Davis J, Goadrich M. The relationship between Precision-Recall and ROC curves. In: Proceedings of the 23rd International Conference on Machine Learning - ICML \u201906. ACM Press; 2006:233\u2013240. https:\/\/doi.org\/10.1145\/1143844.1143874","DOI":"10.1145\/1143844.1143874"},{"issue":"1","key":"354_CR34","doi-asserted-by":"publisher","first-page":"012055","DOI":"10.1088\/1742-6596\/1229\/1\/012055","volume":"1229","author":"I D\u00fcntsch","year":"2019","unstructured":"D\u00fcntsch I, Gediga G. Confusion Matrices and Rough Set Data Analysis. J Phys Conf Ser. 2019;1229(1):012055. https:\/\/doi.org\/10.1088\/1742-6596\/1229\/1\/012055.","journal-title":"J Phys Conf Ser"},{"key":"354_CR35","doi-asserted-by":"publisher","unstructured":"L\u00f3pez-Rat\u00f3n M, Rodr\u00edguez-\u00c1lvarez MX, Su\u00e1rez CC, Sampedro FG. OptimalCutpoints: An R Package for Selecting Optimal Cutpoints in Diagnostic Tests. J Stat Softw. 2014;61(8). https:\/\/doi.org\/10.18637\/jss.v061.i08","DOI":"10.18637\/jss.v061.i08"},{"issue":"3","key":"354_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3494672","volume":"55","author":"D Pessach","year":"2023","unstructured":"Pessach D, Shmueli E. A Review on Fairness in Machine Learning. ACM Comput Surv. 2023;55(3):1\u201344. https:\/\/doi.org\/10.1145\/3494672.","journal-title":"ACM Comput Surv"},{"issue":"1","key":"354_CR37","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/s44176-022-00006-z","volume":"1","author":"X Wang","year":"2022","unstructured":"Wang X, Zhang Y, Zhu R. A brief review on algorithmic fairness. Management System Engineering. 2022;1(1):7. https:\/\/doi.org\/10.1007\/s44176-022-00006-z.","journal-title":"Management System Engineering"},{"key":"354_CR38","unstructured":"R Core Team. R: A Language and Environment for Statistical Computing. Published online 2022. Accessed October 26, 2022. https:\/\/www.R-project.org\/"},{"issue":"8","key":"354_CR39","doi-asserted-by":"publisher","first-page":"6424","DOI":"10.1080\/03610918.2016.1204458","volume":"46","author":"O Dag","year":"2017","unstructured":"Dag O, Ilk O. An algorithm for estimating Box-Cox transformation parameter in ANOVA. Commun Stat Simul Comput. 2017;46(8):6424\u201335. https:\/\/doi.org\/10.1080\/03610918.2016.1204458.","journal-title":"Commun Stat Simul Comput"},{"key":"354_CR40","unstructured":"Microsoft Corporation, Weston S. doParallel: Foreach Parallel Adaptor for the \u201cparallel\u201d Package. Published online 2022. Accessed March 23, 2023. https:\/\/CRAN.R-project.org\/package=doParallel"},{"key":"354_CR41","unstructured":"Wickman H, Fran\u00e7ois R, Henry L, M\u00fcller K. dplyr: A Grammar of Data Manipulation. Published online 2021. Accessed March 14, 2022. https:\/\/CRAN.R-project.org\/package=dplyr"},{"key":"354_CR42","doi-asserted-by":"crossref","unstructured":"Wickham H. ggplot2: Elegant Graphics for Data Analysis. Published online 2016. Accessed March 13, 2023. https:\/\/ggplot2.tidyverse.org","DOI":"10.1007\/978-3-319-24277-4"},{"key":"354_CR43","unstructured":"Slowikowski K. ggrepel: Automatically Position Non-Overlapping Text Labels with \u201cggplot2.\u201d Published online 2023. Accessed April 11, 2023. https:\/\/CRAN.R-project.org\/package=ggrepel"},{"key":"354_CR44","unstructured":"Hothorn T, Zeileis A, Farebrother WR, et al. lmtest: Testing Linear Regression Models. Published online March 21, 2022. Accessed January 27, 2023. https:\/\/CRAN.R-project.org\/doc\/Rnews\/"},{"key":"354_CR45","doi-asserted-by":"crossref","unstructured":"Venables WB, Ripley BD. Modern Applied Statistics with S. Fourth.; 2002. Accessed April 23, 2022. https:\/\/www.stats.ox.ac.uk\/pub\/MASS4\/","DOI":"10.1007\/978-0-387-21706-2"},{"key":"354_CR46","doi-asserted-by":"publisher","unstructured":"Prates MO, Cabral CRB, Lachos VH. mixsmsn\u202f: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions. J Stat Softw. 2013;54(12) https:\/\/doi.org\/10.18637\/jss.v054.i12","DOI":"10.18637\/jss.v054.i12"},{"issue":"1","key":"354_CR47","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, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12(1):77. https:\/\/doi.org\/10.1186\/1471-2105-12-77.","journal-title":"BMC Bioinformatics"},{"key":"354_CR48","unstructured":"Azzalini A. sn: The Skew-Normal and Related Distributions Such as the Skew-t and the SUN. Published online April 4, 2023. Accessed May 18, 2022. http:\/\/azzalini.stat.unipd.it\/SN\/"},{"key":"354_CR49","unstructured":"Wickham H. tidyr: Tidy Messy Data. Published online 2021. Accessed March 13, 2023. https:\/\/CRAN.R-project.org\/package=tidyr"},{"issue":"2\u20133","key":"354_CR50","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.ijpara.2016.06.002","volume":"47","author":"MJ Boyle","year":"2017","unstructured":"Boyle MJ, Reiling L, Osier FH, Fowkes FJI. Recent insights into humoral immunity targeting Plasmodium falciparum and Plasmodium vivax malaria. Int J Parasitol. 2017;47(2\u20133):99\u2013104. https:\/\/doi.org\/10.1016\/j.ijpara.2016.06.002.","journal-title":"Int J Parasitol"},{"issue":"1","key":"354_CR51","doi-asserted-by":"publisher","first-page":"558","DOI":"10.1038\/s41467-017-02646-2","volume":"9","author":"WJR Stone","year":"2018","unstructured":"Stone WJR, Campo JJ, Ou\u00e9draogo AL, et al. Unravelling the immune signature of Plasmodium falciparum transmission-reducing immunity. Nat Commun. 2018;9(1):558. https:\/\/doi.org\/10.1038\/s41467-017-02646-2.","journal-title":"Nat Commun"},{"issue":"8","key":"354_CR52","doi-asserted-by":"publisher","first-page":"e0273106","DOI":"10.1371\/journal.pone.0273106","volume":"17","author":"T Oulton","year":"2022","unstructured":"Oulton T, Obiero J, Rodriguez I, et al. Plasmodium falciparum serology: A comparison of two protein production methods for analysis of antibody responses by protein microarray. PLoS ONE. 2022;17(8):e0273106. https:\/\/doi.org\/10.1371\/journal.pone.0273106.","journal-title":"PLoS ONE"},{"key":"354_CR53","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.ins.2014.05.042","volume":"282","author":"V Bol\u00f3n-Canedo","year":"2014","unstructured":"Bol\u00f3n-Canedo V, S\u00e1nchez-Maro\u00f1o N, Alonso-Betanzos A, Ben\u00edtez JM, Herrera F. A review of microarray datasets and applied feature selection methods. Inf Sci (N Y). 2014;282:111\u201335. https:\/\/doi.org\/10.1016\/j.ins.2014.05.042.","journal-title":"Inf Sci (N Y)"},{"issue":"12","key":"354_CR54","doi-asserted-by":"publisher","first-page":"2383","DOI":"10.1016\/j.patcog.2005.11.001","volume":"39","author":"R Ruiz","year":"2006","unstructured":"Ruiz R, Riquelme JC, Aguilar-Ruiz JS. Incremental wrapper-based gene selection from microarray data for cancer classification. Pattern Recognit. 2006;39(12):2383\u201392. https:\/\/doi.org\/10.1016\/j.patcog.2005.11.001.","journal-title":"Pattern Recognit"},{"issue":"2","key":"354_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/980972.980974","volume":"5","author":"G Piatetsky-Shapiro","year":"2003","unstructured":"Piatetsky-Shapiro G, Tamayo P. Microarray data mining. ACM SIGKDD Explorations Newsl. 2003;5(2):1\u20135. https:\/\/doi.org\/10.1145\/980972.980974.","journal-title":"ACM SIGKDD Explorations Newsl"},{"issue":"19","key":"354_CR56","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1093\/bioinformatics\/btm344","volume":"23","author":"Y Saeys","year":"2007","unstructured":"Saeys Y, Inza I, Larra\u00f1aga P. A review of feature selection techniques in bioinformatics. Bioinformatics. 2007;23(19):2507\u201317. https:\/\/doi.org\/10.1093\/bioinformatics\/btm344.","journal-title":"Bioinformatics"},{"issue":"2","key":"354_CR57","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.artmed.2004.01.007","volume":"31","author":"I Inza","year":"2004","unstructured":"Inza I, Larra\u00f1aga P, Blanco R, Cerrolaza AJ. Filter versus wrapper gene selection approaches in DNA microarray domains. Artif Intell Med. 2004;31(2):91\u2013103. https:\/\/doi.org\/10.1016\/j.artmed.2004.01.007.","journal-title":"Artif Intell Med"},{"issue":"1","key":"354_CR58","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1002\/pst.331","volume":"8","author":"V Fedorov","year":"2009","unstructured":"Fedorov V, Mannino F, Zhang R. Consequences of dichotomization. Pharm Stat. 2009;8(1):50\u201361. https:\/\/doi.org\/10.1002\/pst.331.","journal-title":"Pharm Stat"},{"issue":"4","key":"354_CR59","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1002\/pst.396","volume":"9","author":"B Yoo","year":"2010","unstructured":"Yoo B. The impact of dichotomization in longitudinal data analysis: a simulation study. Pharm Stat. 2010;9(4):298\u2013312. https:\/\/doi.org\/10.1002\/pst.396.","journal-title":"Pharm Stat"},{"issue":"1","key":"354_CR60","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1037\/1082-989X.7.1.19","volume":"7","author":"RC MacCallum","year":"2002","unstructured":"MacCallum RC, Zhang S, Preacher KJ, Rucker DD. On the practice of dichotomization of quantitative variables. Psychol Methods. 2002;7(1):19\u201340. https:\/\/doi.org\/10.1037\/1082-989X.7.1.19.","journal-title":"Psychol Methods"},{"issue":"1","key":"354_CR61","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12936-021-04022-4","volume":"21","author":"I Kyomuhangi","year":"2022","unstructured":"Kyomuhangi I, Giorgi E. A threshold-free approach with age-dependency for estimating malaria seroprevalence. Malar J. 2022;21(1):1. https:\/\/doi.org\/10.1186\/s12936-021-04022-4.","journal-title":"Malar J"},{"issue":"1","key":"354_CR62","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1186\/s12936-016-1121-0","volume":"15","author":"E Pothin","year":"2016","unstructured":"Pothin E, Ferguson NM, Drakeley CJ, Ghani AC. Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models. Malar J. 2016;15(1):79. https:\/\/doi.org\/10.1186\/s12936-016-1121-0.","journal-title":"Malar J"},{"key":"354_CR63","doi-asserted-by":"publisher","unstructured":"Aitken EH, Damelang T, Ortega-Pajares A, et al. Developing a multivariate prediction model of antibody features associated with protection of malaria-infected pregnant women from placental malaria. Elife. 2021;10. https:\/\/doi.org\/10.7554\/eLife.65776","DOI":"10.7554\/eLife.65776"},{"issue":"5","key":"354_CR64","doi-asserted-by":"publisher","first-page":"1413","DOI":"10.1080\/03610926.2020.1764042","volume":"51","author":"M Loecher","year":"2022","unstructured":"Loecher M. Unbiased variable importance for random forests. Commun Stat Theory Methods. 2022;51(5):1413\u201325. https:\/\/doi.org\/10.1080\/03610926.2020.1764042.","journal-title":"Commun Stat Theory Methods"}],"container-title":["BioData Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13040-024-00354-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13040-024-00354-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13040-024-00354-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T17:06:34Z","timestamp":1706202394000},"score":1,"resource":{"primary":{"URL":"https:\/\/biodatamining.biomedcentral.com\/articles\/10.1186\/s13040-024-00354-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,25]]},"references-count":64,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["354"],"URL":"https:\/\/doi.org\/10.1186\/s13040-024-00354-4","relation":{},"ISSN":["1756-0381"],"issn-type":[{"value":"1756-0381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,25]]},"assertion":[{"value":"14 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study is based on publicly available data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"2"}}