{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T11:46:28Z","timestamp":1792842388874,"version":"4.5.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T00:00:00Z","timestamp":1623628800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T00:00:00Z","timestamp":1623628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/M01360X\/1, MR\/N010469\/1, MR\/R025576\/1, and MR\/R020973\/1"],"award-info":[{"award-number":["MR\/M01360X\/1, MR\/N010469\/1, MR\/R025576\/1, and MR\/R020973\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/M01360X\/1, MR\/R025576\/1, and MR\/R020973\/1"],"award-info":[{"award-number":["MR\/M01360X\/1, MR\/R025576\/1, and MR\/R020973\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BB\/R013063\/1"],"award-info":[{"award-number":["BB\/R013063\/1"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"name":"BloomsburySET"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Malar J"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Malaria, caused by <jats:italic>Plasmodium<\/jats:italic> parasites, is a major global public health problem. To assist an understanding of malaria pathogenesis, including drug resistance, there is a need for the timely detection of underlying genetic mutations and their spread. With the increasing use of whole-genome sequencing (WGS) of <jats:italic>Plasmodium<\/jats:italic> DNA, the potential of deep learning models to detect loci under recent positive selection, historically signals of drug resistance, was evaluated.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A deep learning-based approach (called \u201c<jats:italic>DeepSweep\u201d<\/jats:italic>) was developed, which can be trained on haplotypic images from genetic regions with known sweeps, to identify loci under positive selection. <jats:italic>DeepSweep<\/jats:italic> software is available from <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/WDee\/Deepsweep\">https:\/\/github.com\/WDee\/Deepsweep<\/jats:ext-link>.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Using simulated genomic data, <jats:italic>DeepSweep<\/jats:italic> could detect recent sweeps with high predictive accuracy (areas under ROC curve\u2009&gt;\u20090.95). <jats:italic>DeepSweep<\/jats:italic> was applied to <jats:italic>Plasmodium falciparum<\/jats:italic> (n\u2009=\u20091125; genome size 23 Mbp) and <jats:italic>Plasmodium vivax<\/jats:italic> (n\u2009=\u2009368; genome size 29 Mbp) WGS data, and the genes identified overlapped with two established extended haplotype homozygosity methods (within-population iHS, across-population Rsb) (~\u200960\u201375% overlap of hits at P\u2009&lt;\u20090.0001). <jats:italic>DeepSweep<\/jats:italic> hits included regions proximal to known drug resistance loci for both <jats:italic>P. falciparum<\/jats:italic> (e.g. <jats:italic>pfcrt<\/jats:italic>, <jats:italic>pfdhps<\/jats:italic> and <jats:italic>pfmdr1<\/jats:italic>) and <jats:italic>P. vivax<\/jats:italic> (e.g. <jats:italic>pvmrp1<\/jats:italic>).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>The deep learning approach can detect positive selection signatures in malaria parasite WGS data. Further, as the approach is generalizable, it may be trained to detect other types of selection. With the ability to rapidly generate WGS data at low cost, machine learning approaches (e.g. <jats:italic>DeepSweep<\/jats:italic>) have the potential to assist parasite genome-based surveillance and inform malaria control decision-making.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12936-021-03788-x","type":"journal-article","created":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T07:03:28Z","timestamp":1623654208000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Using deep learning to identify recent positive selection in malaria parasite sequence data"],"prefix":"10.1186","volume":"20","author":[{"given":"Wouter","family":"Deelder","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ernest Diez","family":"Benavente","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jody","family":"Phelan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emilia","family":"Manko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susana","family":"Campino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luigi","family":"Palla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8985-9265","authenticated-orcid":false,"given":"Taane G.","family":"Clark","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,6,14]]},"reference":[{"key":"3788_CR1","unstructured":"WHO. World Malaria Report. Geneva, World Health Organization, 2020."},{"key":"3788_CR2","doi-asserted-by":"publisher","unstructured":"Fairhurst RM, Dondorp AM. Artemisinin-resistant Plasmodium falciparum malaria. Microbiol Spectr. 2016;4:https:\/\/doi.org\/10.1128\/microbiolspec.ei10-0013-2016","DOI":"10.1128\/microbiolspec.ei10-0013-2016"},{"key":"3788_CR3","doi-asserted-by":"crossref","unstructured":"Zhao Y, Liu Z, Myat Thu Soe, Wang L, Soe TN, Wei H, et al. Genetic variations associated with drug resistance markers in asymptomatic Plasmodium falciparum infections in Myanmar. Genes (Basel). 2019;10:692","DOI":"10.3390\/genes10090692"},{"key":"3788_CR4","doi-asserted-by":"crossref","unstructured":"Benavente ED, Ward Z, Chan W, Mohareb FR, Sutherland CJ, Roper C, et al. Genomic variation in Plasmodium vivax malaria reveals regions under selective pressure. PLoS One. 2017;12:e0177134","DOI":"10.1371\/journal.pone.0177134"},{"key":"3788_CR5","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1186\/s13071-020-3934-5","volume":"13","author":"HG Ngassa Mbenda","year":"2020","unstructured":"Ngassa Mbenda HG, Wang M, Guo J, Siddiqui FA, Hu Y, Yang Z, et al. Evolution of the Plasmodium vivax multidrug resistance 1 gene in the Greater Mekong Subregion during malaria elimination. Parasit Vectors. 2020;13:67.","journal-title":"Parasit Vectors"},{"key":"3788_CR6","doi-asserted-by":"publisher","first-page":"3160","DOI":"10.1038\/s41467-021-23422-3","volume":"12","author":"E Diez Benavente","year":"2021","unstructured":"Diez Benavente E, Manko E, Phelan J, Campos M, Nolder D, Fernandez D, et al. Distinctive genetic structure and selection patterns in Plasmodium vivax from South Asia and East Africa. Nat Commun. 2021;12:3160.","journal-title":"Nat Commun"},{"key":"3788_CR7","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1146\/annurev.genet.39.073003.112420","volume":"39","author":"R Nielsen","year":"2005","unstructured":"Nielsen R. Molecular Signatures of Natural Selection SNP: single nucleotide polymorphism. Annu Rev Genet. 2005;39:197\u2013218.","journal-title":"Annu Rev Genet"},{"key":"3788_CR8","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1146\/annurev-genet-111212-133526","volume":"47","author":"JJ Vitti","year":"2013","unstructured":"Vitti JJ, Grossman SR, Sabeti PC. Detecting natural selection in genomic data. Annu Rev Genet. 2013;47:97\u2013120.","journal-title":"Annu Rev Genet"},{"key":"3788_CR9","doi-asserted-by":"publisher","first-page":"1991","DOI":"10.1093\/infdis\/jiu349","volume":"210","author":"H Ocholla","year":"2014","unstructured":"Ocholla H, Preston MD, Mipando M, Jensen ATR, Campino S, MacInnis B, et al. Whole-genome scans provide evidence of adaptive evolution in Malawian Plasmodium falciparum isolates. J Infect Dis. 2014;210:1991\u20132000.","journal-title":"J Infect Dis"},{"key":"3788_CR10","doi-asserted-by":"crossref","unstructured":"Samad H, Coll F, Preston MD, Ocholla H, Fairhurst RM, Clark TG. Imputation-based population genetics analysis of Plasmodium falciparum malaria parasites. PLoS Genet. 2015;11:e1005131.","DOI":"10.1371\/journal.pgen.1005131"},{"key":"3788_CR11","doi-asserted-by":"crossref","unstructured":"Gautier M, Klassmann A, Vitalis R. rehh 2.0: a reimplementation of the R package rehh to detect positive selection from haplotype structure. Mol Ecol Resour. 2017;17:78\u201390.","DOI":"10.1111\/1755-0998.12634"},{"key":"3788_CR12","doi-asserted-by":"publisher","first-page":"2224","DOI":"10.1093\/molbev\/mst112","volume":"30","author":"P Pavlidis","year":"2013","unstructured":"Pavlidis P, \u017divkovi\u0107 D, Stamatakis A, Alachiotis N. SweeD: Likelihood-based detection of selective sweeps in thousands of genomes. Mol Biol Evol. 2013;30:2224\u201334.","journal-title":"Mol Biol Evol"},{"key":"3788_CR13","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1093\/bioinformatics\/bts419","volume":"28","author":"N Alachiotis","year":"2012","unstructured":"Alachiotis N, Stamatakis A, Pavlidis P. OmegaPlus: a scalable tool for rapid detection of selective sweeps in whole-genome datasets. Bioinformatics. 2012;28:2274\u20135.","journal-title":"Bioinformatics"},{"key":"3788_CR14","unstructured":"Hahn MW. Molecular population genetics. Oxford University Press (OUP); 2018."},{"key":"3788_CR15","doi-asserted-by":"crossref","unstructured":"Pybus M, Luisi P, Dall\u2019Olio GM, Uzkudun M, Laayouni H, Bertranpetit J, et al. Hierarchical boosting: a machine-learning framework to detect and classify hard selective sweeps in human populations. Bioinformatics. 2015;31:3946\u201352.","DOI":"10.1093\/bioinformatics\/btv493"},{"key":"3788_CR16","unstructured":"Goodfellow I, Bengio Y, Courville A. Deep learning. MIT Press; 2016."},{"key":"3788_CR17","first-page":"8594","volume":"31","author":"J Chan","year":"2018","unstructured":"Chan J, Perrone V, Spence JP, Jenkins PA, Mathieson S, Song YS. A likelihood-free inference framework for population genetic data using exchangeable neural networks. Adv Neural Inf Process Syst. 2018;31:8594\u2013605.","journal-title":"Adv Neural Inf Process Syst"},{"key":"3788_CR18","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1093\/molbev\/msy224","volume":"36","author":"L Flagel","year":"2019","unstructured":"Flagel L, Brandvain Y, Schrider DR. The unreasonable effectiveness of convolutional neural networks in population genetic inference. Mol Biol Evol. 2019;36:220\u201338.","journal-title":"Mol Biol Evol"},{"key":"3788_CR19","doi-asserted-by":"crossref","unstructured":"Sanchez T, Cury J, Charpiat G, Jay F. Deep learning for population size history inference: design, comparison and combination with approximate Bayesian computation. bioRxiv. 2020; 2020.01.20.910539.","DOI":"10.1101\/2020.01.20.910539"},{"key":"3788_CR20","unstructured":"Chollet F. Keras. Github; 2015. Available from: https:\/\/github.com\/fchollet\/keras"},{"key":"3788_CR21","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. Commun ACM. 2017;60:84\u201390.","journal-title":"Commun ACM"},{"key":"3788_CR22","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Salakhutdinov R. Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res. 2014;15:1929\u201358.","journal-title":"J Mach Learn Res"},{"key":"3788_CR23","doi-asserted-by":"publisher","first-page":"80","DOI":"10.4161\/fly.19695","volume":"6","author":"P Cingolani","year":"2012","unstructured":"Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly (Austin). 2012;6:80\u201392.","journal-title":"Fly (Austin)"},{"key":"3788_CR24","first-page":"35","volume":"3","author":"P Cingolani","year":"2012","unstructured":"Cingolani P, Patel VM, Coon M, Nguyen T, Land SJ, Ruden DM, et al. Using Drosophila melanogaster as a model for genotoxic chemical mutational studies with a new program. SnpSift Front Genet. 2012;3:35.","journal-title":"SnpSift Front Genet"},{"key":"3788_CR25","unstructured":"Casbon J. PyVCF-A Variant Call Format Parser for Python. Github; 2012. Available from: https:\/\/github.com\/jamescasbon\/PyVCF"},{"key":"3788_CR26","doi-asserted-by":"publisher","first-page":"2786","DOI":"10.1093\/bioinformatics\/btn522","volume":"24","author":"RD Hernandez","year":"2008","unstructured":"Hernandez RD. A flexible forward simulator for populations subject to selection and demography. Bioinformatics. 2008;24:2786\u20137.","journal-title":"Bioinformatics"},{"key":"3788_CR27","doi-asserted-by":"publisher","first-page":"8287","DOI":"10.1038\/s41598-019-44599-0","volume":"9","author":"M Ravenhall","year":"2019","unstructured":"Ravenhall M, Benavente ED, Sutherland CJ, Baker DA, Campino S, Clark TG. An analysis of large structural variation in global Plasmodium falciparum isolates identifies a novel duplication of the chloroquine resistance associated gene. Sci Rep. 2019;9:8287.","journal-title":"Sci Rep"},{"key":"3788_CR28","doi-asserted-by":"crossref","unstructured":"Diez Benavente E, Campos M, Phelan J, Nolder D, Dombrowski JG, Marinho CRF, et al. A molecular barcode to inform the geographical origin and transmission dynamics of Plasmodium vivax malaria. PLoS Genet. 2020;16:e1008576.","DOI":"10.1371\/journal.pgen.1008576"},{"key":"3788_CR29","doi-asserted-by":"publisher","first-page":"1292","DOI":"10.1093\/bioinformatics\/btu005","volume":"30","author":"SA Assefa","year":"2014","unstructured":"Assefa SA, Preston MD, Campino S, Ocholla H, Sutherland CJ, Clark TG. EstMOI: Estimating multiplicity of infection using parasite deep sequencing data. Bioinformatics. 2014;30:1292\u20134.","journal-title":"Bioinformatics"},{"key":"3788_CR30","unstructured":"Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. 2013; arXiv:1303.3997v2."},{"key":"3788_CR31","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1101\/gr.107524.110","volume":"20","author":"A McKenna","year":"2010","unstructured":"McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297\u2013303.","journal-title":"Genome Res"},{"key":"3788_CR32","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1093\/bioinformatics\/btr076","volume":"27","author":"H Li","year":"2011","unstructured":"Li H. Improving SNP discovery by base alignment quality. Bioinformatics. 2011;27:1157\u20138.","journal-title":"Bioinformatics"},{"key":"3788_CR33","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1186\/1471-2105-12-389","volume":"12","author":"F Mordelet","year":"2011","unstructured":"Mordelet F, Vert JP. ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples. BMC Bioinformatics. 2011;12:389.","journal-title":"BMC Bioinformatics"},{"key":"3788_CR34","doi-asserted-by":"crossref","unstructured":"Voight BF, Kudaravalli S, Wen X, Pritchard JK, Diamond J, Jobling M, et al. A map of recent positive selection in the human genome. PLoS Biol. 2006;4:e72.","DOI":"10.1371\/journal.pbio.0040072"},{"key":"3788_CR35","doi-asserted-by":"publisher","first-page":"1587","DOI":"10.1371\/journal.pbio.0050171","volume":"5","author":"K Tang","year":"2007","unstructured":"Tang K, Thornton KR, Stoneking M. A new approach for using genome scans to detect recent positive selection in the human genome. PLoS Biol. 2007;5:1587\u2013602.","journal-title":"PLoS Biol"},{"key":"3788_CR36","doi-asserted-by":"publisher","first-page":"1176","DOI":"10.1093\/bioinformatics\/bts115","volume":"28","author":"M Gautier","year":"2012","unstructured":"Gautier M, Vitalis R. rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure. Bioinformatics. 2012;28:1176\u20137.","journal-title":"Bioinformatics"},{"key":"3788_CR37","doi-asserted-by":"crossref","unstructured":"Turkiewicz A, Manko E, Sutherland CJ, Benavente ED, Campino S, Clark TG. Genetic diversity of the Plasmodium falciparum GTP-cyclohydrolase 1, dihydrofolate reductase and dihydropteroate synthetase genes reveals new insights into sulfadoxine-pyrimethamine antimalarial drug resistance. PLoS Genet. 2020;16:e1009268","DOI":"10.1371\/journal.pgen.1009268"},{"key":"3788_CR38","doi-asserted-by":"publisher","first-page":"766","DOI":"10.1016\/j.chom.2017.11.005","volume":"22","author":"M Zhang","year":"2017","unstructured":"Zhang M, Gallego-Delgado J, Fernandez-Arias C, Waters NC, Rodriguez A, Tsuji M, et al. Inhibiting the Plasmodium eIF2\u03b1 kinase PK4 prevents artemisinin-induced latency. Cell Host Microbe. 2017;22:766-776.e4.","journal-title":"Cell Host Microbe"},{"key":"3788_CR39","doi-asserted-by":"crossref","unstructured":"Sanchez CP, Liu C-H, Mayer S, Nurhasanah A, Cyrklaff M, Mu J, et al. A HECT ubiquitin-protein ligase as a novel candidate gene for altered quinine and quinidine responses in Plasmodium falciparum. PLoS Genet. 2014;10:e1004382.","DOI":"10.1371\/journal.pgen.1004382"},{"key":"3788_CR40","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1186\/s12936-016-1634-6","volume":"15","author":"M Ravenhall","year":"2016","unstructured":"Ravenhall M, Benavente ED, Mipando M, Jensen ATR, Sutherland CJ, Roper C, et al. Characterizing the impact of sustained sulfadoxine\/pyrimethamine use upon the Plasmodium falciparum population in Malawi. Malar J. 2016;15:575.","journal-title":"Malar J"},{"key":"3788_CR41","doi-asserted-by":"publisher","first-page":"14552","DOI":"10.1038\/srep14552","volume":"5","author":"S Pulcini","year":"2015","unstructured":"Pulcini S, Staines HM, Lee AH, Shafik SH, Bouyer G, Moore CM, et al. Mutations in the Plasmodium falciparum chloroquine resistance transporter, PfCRT, enlarge the parasite\u2019s food vacuole and alter drug sensitivities. Sci Rep. 2015;5:14552.","journal-title":"Sci Rep"},{"key":"3788_CR42","unstructured":"Sedillo J. Pathogenic mechanisms and signaling pathways in Plasmodium falciparum. Grad Theses Dissertation, University of South Florida. 2014."},{"key":"3788_CR43","doi-asserted-by":"crossref","unstructured":"Fran\u00e7a CT, He W-Q, Gruszczyk J, Lim NTY, Lin E, Kiniboro B, et al. Plasmodium vivax reticulocyte binding proteins are key targets of naturally acquired immunity in young Papua New Guinean children. PLoS Negl Trop Dis. 2016;10:e0005014.","DOI":"10.1371\/journal.pntd.0005014"},{"key":"3788_CR44","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1038\/ng.3588","volume":"48","author":"DN Hupalo","year":"2016","unstructured":"Hupalo DN, Luo Z, Melnikov A, Sutton PL, Rogov P, Escalante A, et al. Population genomics studies identify signatures of global dispersal and drug resistance in Plasmodium vivax. Nat Genet. 2016;48:953\u20138.","journal-title":"Nat Genet"},{"key":"3788_CR45","doi-asserted-by":"publisher","first-page":"866","DOI":"10.1016\/j.ajhg.2013.04.021","volume":"92","author":"X Liu","year":"2013","unstructured":"Liu X, Ong RTH, Pillai EN, Elzein AM, Small KS, Clark TG, et al. Detecting and characterizing genomic signatures of positive selection in global populations. Am J Hum Genet. 2013;92:866\u201381.","journal-title":"Am J Hum Genet"},{"key":"3788_CR46","doi-asserted-by":"publisher","first-page":"15429","DOI":"10.1038\/s41598-018-33767-3","volume":"8","author":"ED Benavente","year":"2018","unstructured":"Benavente ED, Oresegun DR, de Sessions PF, Walker EM, Roper C, Dombrowski JG, et al. Global genetic diversity of var2csa in Plasmodium falciparum with implications for malaria in pregnancy and vaccine development. Sci Rep. 2018;8:15429.","journal-title":"Sci Rep"},{"key":"3788_CR47","doi-asserted-by":"crossref","unstructured":"Mohring F, Hart MN, Rawlinson TA, Henrici R, Charleston JA, Diez Benavente E, et al. Rapid and iterative genome editing in the malaria parasite Plasmodium knowlesi provides new tools for P. vivax research. Elife. 2019;8:e45829.","DOI":"10.7554\/eLife.45829"},{"key":"3788_CR48","doi-asserted-by":"crossref","unstructured":"Henden L, Lee S, Mueller I, Barry A, Bahlo M. Identity-by-descent analyses for measuring population dynamics and selection in recombining pathogens. PLoS Genet. 2018;14:e1007279.","DOI":"10.1371\/journal.pgen.1007279"}],"container-title":["Malaria Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12936-021-03788-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12936-021-03788-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12936-021-03788-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T07:04:58Z","timestamp":1623654298000},"score":1,"resource":{"primary":{"URL":"https:\/\/malariajournal.biomedcentral.com\/articles\/10.1186\/s12936-021-03788-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,14]]},"references-count":48,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["3788"],"URL":"https:\/\/doi.org\/10.1186\/s12936-021-03788-x","relation":{},"ISSN":["1475-2875"],"issn-type":[{"value":"1475-2875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,14]]},"assertion":[{"value":"24 March 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 June 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","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":"WD was employed by the company Dalberg Advisors in Switzerland. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"270"}}