{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T17:38:08Z","timestamp":1781890688023,"version":"3.54.5"},"reference-count":73,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T00:00:00Z","timestamp":1626998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:p>Bovine babesiosis causes significant annual global economic loss in the beef and dairy cattle industry. It is a disease instigated from infection of red blood cells by haemoprotozoan parasites of the genus <jats:italic>Babesia<\/jats:italic> in the phylum Apicomplexa. Principal species are <jats:italic>Babesia bovis, Babesia bigemina<\/jats:italic>, and <jats:italic>Babesia divergens.<\/jats:italic> There is no subunit vaccine. Potential therapeutic targets against babesiosis include members of the exportome. This study investigates the novel use of protein secondary structure characteristics and machine learning algorithms to predict exportome membership probabilities. The premise of the approach is to detect characteristic differences that can help classify one protein type from another. Structural properties such as a protein\u2019s local conformational classification states, backbone torsion angles \u03d5 (phi) and \u03c8 (psi), solvent-accessible surface area, contact number, and half-sphere exposure are explored here as potential distinguishing protein characteristics. The presented methods that exploit these structural properties via machine learning are shown to have the capacity to detect exportome from non-exportome <jats:italic>Babesia bovis<\/jats:italic> proteins with an 86\u201392% accuracy (based on 10-fold cross validation and independent testing). These methods are encapsulated in freely available Linux pipelines setup for automated, high-throughput processing. Furthermore, proposed therapeutic candidates for laboratory investigation are provided for <jats:italic>B. bovis, B. bigemina<\/jats:italic>, and two other haemoprotozoan species, <jats:italic>Babesia canis<\/jats:italic>, and <jats:italic>Plasmodium falciparum.<\/jats:italic><\/jats:p>","DOI":"10.3389\/fgene.2021.716132","type":"journal-article","created":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T13:42:09Z","timestamp":1627047729000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Predicting Protein Therapeutic Candidates for Bovine Babesiosis Using Secondary Structure Properties and Machine Learning"],"prefix":"10.3389","volume":"12","author":[{"given":"Stephen J.","family":"Goodswen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul J.","family":"Kennedy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John T.","family":"Ellis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2021,7,23]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1016\/j.parint.2017.07.004","article-title":"Molecular identification and antigenic characterization of Babesia divergens Erythrocyte Binding Protein (BdEBP) as a potential vaccine candidate.","volume":"66","author":"Abd El-Salam El-Sayed","year":"2017","journal-title":"Parasitol. Int."},{"key":"B2","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/s1097-2765(00)80411-6","article-title":"The ves multigene family of B-bovis encodes components of rapid antigenic variation at the infected erythrocyte surface.","volume":"5","author":"Allred","year":"2000","journal-title":"Mol. Cell"},{"key":"B3","doi-asserted-by":"publisher","first-page":"3389","DOI":"10.1093\/nar\/25.17.3389","article-title":"Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.","volume":"25","author":"Altschul","year":"1997","journal-title":"Nucleic Acids Res."},{"key":"B4","doi-asserted-by":"publisher","first-page":"3387","DOI":"10.1093\/bioinformatics\/btx431","article-title":"DeepLoc: prediction of protein subcellular localization using deep learning.","volume":"33","author":"Armenteros","year":"2017","journal-title":"Bioinformatics"},{"key":"B5","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1038\/s41587-019-0036-z","article-title":"SignalP 5.0 improves signal peptide predictions using deep neural networks.","volume":"37","author":"Armenteros","year":"","journal-title":"Nat. Biotechnol."},{"key":"B6","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1038\/s41587-019-0036-z","article-title":"SignalP 5.0 improves signal peptide predictions using deep neural networks.","volume":"37","author":"Armenteros","year":"","journal-title":"Nat. Biotechnol."},{"key":"B7","doi-asserted-by":"publisher","first-page":"D415","DOI":"10.1093\/nar\/gkp941","article-title":"EuPathDB: a portal to eukaryotic pathogen databases.","volume":"38","author":"Aurrecoechea","year":"2010","journal-title":"Nucleic Acids Res."},{"key":"B8","doi-asserted-by":"publisher","first-page":"D204","DOI":"10.1093\/nar\/gku989","article-title":"UniProt: a hub for protein information.","volume":"43","author":"Bateman","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"B9","doi-asserted-by":"publisher","first-page":"1401","DOI":"10.1371\/journal.ppat.0030148","article-title":"Genome sequence of babesia bovis and comparative analysis of apicomplexan hemoprotozoa.","volume":"3","author":"Brayton","year":"2007","journal-title":"PLoS Pathog."},{"key":"B10","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/a:1010933404324","article-title":"Random forests.","volume":"45","author":"Breiman","year":"2001","journal-title":"Machine Learn."},{"key":"B11","doi-asserted-by":"publisher","first-page":"W402","DOI":"10.1093\/nar\/gkz297","article-title":"The PSIPRED protein analysis workbench: 20 years on.","volume":"47","author":"Buchan","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"B12","doi-asserted-by":"publisher","first-page":"899","DOI":"10.1083\/jcb.200509122","article-title":"A Maurer\u2019s cleft-associated protein is essential for expression of the major malaria virulence antigen on the surface of infected red blood cells.","volume":"172","author":"Cooke","year":"2006","journal-title":"J. Cell Biol."},{"key":"B13","doi-asserted-by":"publisher","first-page":"W389","DOI":"10.1093\/nar\/gkv332","article-title":"JPred4: a protein secondary structure prediction server.","volume":"43","author":"Drozdetskiy","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-03445-x","article-title":"Genome-wide analysis of gene expression and protein secretion of Babesia canis during virulent infection identifies potential pathogenicity factors.","volume":"7","author":"Eichenberger","year":"2017","journal-title":"Sci. Rep."},{"key":"B15","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/j.ttbdis.2013.12.011","article-title":"The glycosylphosphatidylinositol-anchored protein repertoire of Babesia bovis and its significance for erythrocyte invasion.","volume":"5","author":"Elisa Rodriguez","year":"2014","journal-title":"Ticks Tick Borne Dis."},{"key":"B16","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1038\/nprot.2007.131","article-title":"Locating proteins in the cell using TargetP, SignalP and related tools.","volume":"2","author":"Emanuelsson","year":"2007","journal-title":"Nat. Protocols"},{"key":"B17","doi-asserted-by":"publisher","first-page":"1293","DOI":"10.1093\/bioinformatics\/btz712","article-title":"MUFold-SSW: a new web server for predicting protein secondary structures, torsion angles and turns.","volume":"36","author":"Fang","year":"2020","journal-title":"Bioinformatics"},{"key":"B18","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.1109\/tcbb.2018.2814586","article-title":"Prediction of protein backbone torsion angles using deep residual inception neural networks.","volume":"16","author":"Fang","year":"2019","journal-title":"Ieee Acm Trans. Comput. Biol. Bioinform."},{"key":"B19","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.ijpara.2011.10.004","article-title":"Expression and strain variation of the novel \u201csmall open reading frame\u201d (smorf) multigene family in Babesia bovis.","volume":"42","author":"Ferreri","year":"2012","journal-title":"Int. J. Parasitol."},{"key":"B20","doi-asserted-by":"publisher","first-page":"1563","DOI":"10.1017\/s0031182014000961","article-title":"Vaccines against bovine babesiosis: where we are now and possible roads ahead.","volume":"141","author":"Florin-Christensen","year":"2014","journal-title":"Parasitology"},{"key":"B21","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1006\/jcss.1997.1504","article-title":"A decision-theoretic generalization of on-line learning and an application to boosting.","volume":"55","author":"Freund","year":"1997","journal-title":"J. Comput. Syst. Sci."},{"key":"B22","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1214\/aos\/1016218223","article-title":"Additive logistic regression: a statistical view of boosting.","volume":"28","author":"Friedman","year":"2000","journal-title":"Ann. Statist."},{"key":"B23","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.molbiopara.2004.02.006","article-title":"A Babesia bovis merozoite protein with a domain architecture highly similar to the thrombospondin-related anonymous protein (TRAP) present in Plasmodium sporozoites.","volume":"136","author":"Gaffar","year":"2004","journal-title":"Mol. Biochem. Parasitol."},{"key":"B24","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1016\/j.ijpara.2013.01.002","article-title":"Bioinformatic prediction of the exportome of Babesia bovis and identification of novel proteins in parasite-infected red blood cells.","volume":"43","author":"Gohil","year":"2013","journal-title":"Int. J. Parasitol."},{"key":"B25","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1016\/j.pt.2010.06.012","article-title":"Recent insights into alteration of red blood cells by Babesia bovis: moovin\u2019 forward.","volume":"26","author":"Gohil","year":"2010","journal-title":"Trends Parasitol."},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pntd.0007680","article-title":"Comparative and functional genomics of the protozoan parasite Babesia divergens highlighting the invasion and egress processes.","volume":"13","author":"Gonzalez","year":"2019","journal-title":"PLoS Neglected Tropical Dis."},{"key":"B27","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1093\/bib\/bbs066","article-title":"A guide to in silico vaccine discovery for eukaryotic pathogens.","volume":"14","author":"Goodswen","year":"","journal-title":"Brief. Bioinform."},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-14-315","article-title":"A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms.","volume":"14","author":"Goodswen","year":"","journal-title":"BMC Bioinform."},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.3390\/pathogens10060660","article-title":"Applying machine learning to predict the exportome of bovine and canine babesia species that cause babesiosis.","volume":"10","author":"Goodswen","year":"2021","journal-title":"Pathogens"},{"key":"B30","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1016\/j.ijpara.2012.09.009","article-title":"Evolution of apicomplexan secretory organelles.","volume":"42","author":"Gubbels","year":"2012","journal-title":"Int. J. Parasitol."},{"key":"B31","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1111\/j.1462-5822.2010.01455.x","article-title":"New insights into protein export in malaria parasites.","volume":"12","author":"Haase","year":"2010","journal-title":"Cell. Microbiol."},{"key":"B32","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1128\/cmr.00005-17","article-title":"Toxoplasma effectors targeting host signaling and transcription.","volume":"30","author":"Hakimi","year":"2017","journal-title":"Clin. Microbiol. Rev."},{"key":"B33","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1002\/prot.20379","article-title":"An amino acid has two sides: a new 2D measure provides a different view of solvent exposure.","volume":"59","author":"Hamelryck","year":"2005","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"B34","doi-asserted-by":"publisher","first-page":"2403","DOI":"10.1093\/bioinformatics\/bty1006","article-title":"Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks.","volume":"35","author":"Hanson","year":"2019","journal-title":"Bioinformatics"},{"key":"B35","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1093\/bioinformatics\/btv665","article-title":"Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins.","volume":"32","author":"Heffernan","year":"2016","journal-title":"Bioinformatics"},{"key":"B36","doi-asserted-by":"publisher","first-page":"2210","DOI":"10.1002\/jcc.25534","article-title":"Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning.","volume":"39","author":"Heffernan","year":"2018","journal-title":"J. Comput. Chem."},{"key":"B37","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/0166-6851(94)00200-7","article-title":"Genetic and antigenic characterization of Babesia bovis merozoite spherical body protein Bb-1.","volume":"69","author":"Hines","year":"1995","journal-title":"Mol. Biochem. Parasitol."},{"key":"B38","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1128\/cmr.13.3.451-469.2000","article-title":"Babesiosis.","volume":"13","author":"Homer","year":"2000","journal-title":"Clin. Microbiol. Rev."},{"key":"B39","doi-asserted-by":"publisher","first-page":"W585","DOI":"10.1093\/nar\/gkm259","article-title":"WoLF PSORT: protein localization predictor.","volume":"35","author":"Horton","year":"2007","journal-title":"Nucleic Acids Res."},{"key":"B40","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1016\/j.ijpara.2008.03.001","article-title":"Babesiosis: recent insights into an ancient disease.","volume":"38","author":"Hunfeld","year":"2008","journal-title":"Int. J. Parasitol."},{"key":"B41","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1006\/jmbi.1999.3091","article-title":"Protein secondary structure prediction based on position-specific scoring matrices.","volume":"292","author":"Jones","year":"1999","journal-title":"J. Mol. Biol."},{"key":"B42","doi-asserted-by":"publisher","first-page":"2577","DOI":"10.1002\/bip.360221211","article-title":"Dictionary of protein secondary structure - pattern-recognition of hydrogen-bonded and geometrical features.","volume":"22","author":"Kabsch","year":"1983","journal-title":"Biopolymers"},{"key":"B43","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1016\/j.jmb.2004.03.016","article-title":"A combined transmembrane topology and signal peptide prediction method.","volume":"338","author":"Kall","year":"2004","journal-title":"J. Mol. Biol."},{"key":"B44","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1038\/nprot.2015.053","article-title":"The Phyre2 web portal for protein modeling, prediction and analysis.","volume":"10","author":"Kelley","year":"2015","journal-title":"Nat. Protocols"},{"key":"B45","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/j.ijpara.2003.12.009","article-title":"Toxoplasma gondii: the model apicomplexan.","volume":"34","author":"Kim","year":"2004","journal-title":"Int. J. Parasitol."},{"key":"B46","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1002\/prot.25674","article-title":"NetSurfP-2.0: improved prediction of protein structural features by integrated deep learning.","volume":"87","author":"Klausen","year":"2019","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"B47","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1006\/jmbi.2000.4315","article-title":"Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes.","volume":"305","author":"Krogh","year":"2001","journal-title":"J. Mol. Biol."},{"key":"B48","doi-asserted-by":"publisher","first-page":"1784","DOI":"10.1111\/j.1462-5822.2012.01840.x","article-title":"Plasmodium falciparum-encoded exported hsp70\/hsp40 chaperone\/co-chaperone complexes within the host erythrocyte.","volume":"14","author":"Kuelzer","year":"2012","journal-title":"Cell. Microbiol."},{"key":"B49","doi-asserted-by":"publisher","first-page":"1658","DOI":"10.1093\/bioinformatics\/btl158","article-title":"Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences.","volume":"22","author":"Li","year":"2006","journal-title":"Bioinformatics"},{"key":"B50","doi-asserted-by":"publisher","first-page":"2592","DOI":"10.1093\/bioinformatics\/btu352","article-title":"SSpro\/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity.","volume":"30","author":"Magnan","year":"2014","journal-title":"Bioinformatics"},{"key":"B51","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1038\/nrmicro2110","article-title":"Malaria parasite proteins that remodel the host erythrocyte.","volume":"7","author":"Maier","year":"2009","journal-title":"Nat. Rev. Microbiol."},{"key":"B52","doi-asserted-by":"publisher","DOI":"10.1186\/1472-6807-5-17","article-title":"Protein secondary structure assignment revisited: a detailed analysis of different assignment methods.","volume":"5","author":"Martin","year":"2005","journal-title":"BMC Struct. Biol."},{"key":"B53","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1145\/272991.272995","article-title":"Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator.","volume":"8","author":"Matsumoto","year":"1998","journal-title":"ACM Trans. Model. Comput. Simul."},{"key":"B54","doi-asserted-by":"publisher","first-page":"1504","DOI":"10.2174\/092986712799828355","article-title":"Current advances in detection and treatment of babesiosis.","volume":"19","author":"Mosqueda","year":"2012","journal-title":"Curr. Med. Chem."},{"key":"B55","doi-asserted-by":"publisher","first-page":"5021","DOI":"10.1128\/iai.71.9.5021-5032.2003","article-title":"Stimulation of T-helper cell gamma interferon and immunoglobulin G responses specific for Babesia bovis rhoptry-associated protein 1 (RAP-1) or a RAP-1 protein lacking the carboxy-terminal repeat region is insufficient to provide protective immunity against virulent B-bovis challenge.","volume":"71","author":"Norimine","year":"2003","journal-title":"Infect. Immun."},{"key":"B56","doi-asserted-by":"publisher","first-page":"4420","DOI":"10.1096\/fj.14-256057","article-title":"A plasmodium falciparum PHIST protein binds the virulence factor PfEMP1 and comigrates to knobs on the host cell surface.","volume":"28","author":"Oberli","year":"2014","journal-title":"FASEB J."},{"key":"B57","doi-asserted-by":"publisher","first-page":"2037","DOI":"10.4049\/jimmunol.164.4.2037","article-title":"Selection of Babesia bovis-infected erythrocytes for adhesion to endothelial cells coselects for altered variant erythrocyte surface antigen isoforms.","volume":"164","author":"O\u2019Connor","year":"2000","journal-title":"J. Immunol."},{"key":"B58","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/j.ijpara.2020.12.010","article-title":"The key to egress? Babesia bovis perforin-like protein 1 (PLP1) with hemolytic capacity is required for blood stage replication and is involved in the exit of the parasite from the host cell.","volume":"51","author":"Paoletta","year":"2021","journal-title":"Int. J. Parasitol."},{"key":"B59","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-9-392","article-title":"PredGPI: a GPI-anchor predictor.","volume":"9","author":"Pierleoni","year":"2008","journal-title":"BMC Bioinform."},{"key":"B60","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1002\/prot.10069","article-title":"Prediction of coordination number and relative solvent accessibility in proteins.","volume":"47","author":"Pollastri","year":"2002","journal-title":"Proteins Struct. Funct. Bioinform."},{"key":"B61","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/s0022-2836(63)80023-6","article-title":"Stereochemistry of polypeptide chain configurations.","volume":"7","author":"Ramachandran","year":"1963","journal-title":"J. Mol. Biol."},{"key":"B62","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1016\/j.pt.2019.06.002","article-title":"Babesiosis vaccines: lessons learned, challenges ahead, and future glimpses.","volume":"35","author":"Rathinasamy","year":"2019","journal-title":"Trends Parasitol."},{"key":"B63","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1006\/jsbi.2001.4336","article-title":"Review: protein secondary structure prediction continues to rise.","volume":"134","author":"Rost","year":"2001","journal-title":"J. Struct. Biol."},{"key":"B64","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/s0166-6851(99)00167-x","article-title":"A unique Babesia bovis spherical body protein is conserved among geographic isolates and localizes to the infected erythrocyte membrane.","volume":"105","author":"Ruef","year":"2000","journal-title":"Mol. Biochem. Parasitol."},{"key":"B65","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/mmi.13024","article-title":"The Plasmodium falciparum exportome contains non-canonical PEXEL\/HT proteins.","volume":"97","author":"Schulze","year":"2015","journal-title":"Mol. Microbiol."},{"key":"B66","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1034\/j.1600-0854.2003.00117.x","article-title":"Toxoplasma gondii: perfecting an intracellular life style.","volume":"4","author":"Sibley","year":"2003","journal-title":"Traffic"},{"key":"B67","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.ijpara.2018.11.002","article-title":"Unravelling the cellular and molecular pathogenesis of bovine babesiosis: is the sky the limit?","volume":"49","author":"Suarez","year":"2019","journal-title":"Int. J. Parasitol."},{"key":"B68","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.vetpar.2011.05.032","article-title":"Emerging perspectives in the research of bovine babesiosis and anaplasmosis.","volume":"180","author":"Suarez","year":"2011","journal-title":"Veterinary Parasitol."},{"key":"B69","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.molbiopara.2011.02.006","article-title":"Secretion of a new spherical body protein of Babesia bovis into the cytoplasm of infected erythrocytes.","volume":"178","author":"Terkawi","year":"2011","journal-title":"Mol. Biochem. Parasitol."},{"key":"B70","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-48786-x","article-title":"Deeper profiles and cascaded recurrent and convolutional neural networks for state-of-the-art protein secondary structure prediction.","volume":"9","author":"Torrisi","year":"2019","journal-title":"Sci. Rep."},{"key":"B71","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.tibtech.2007.12.006","article-title":"Computer-aided biotechnology: from immuno-informatics to reverse vaccinology.","volume":"26","author":"Vivona","year":"2008","journal-title":"Trends Biotechnol."},{"key":"B72","doi-asserted-by":"publisher","DOI":"10.1038\/srep18962","article-title":"Protein secondary structure prediction using deep convolutional neural fields.","volume":"6","author":"Wang","year":"2016","journal-title":"Sci. Rep."},{"key":"B73","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1093\/bib\/bbw129","article-title":"Sixty-five years of the long march in protein secondary structure prediction: the final stretch?","volume":"19","author":"Yang","year":"2018","journal-title":"Brief. Bioinform."}],"container-title":["Frontiers in Genetics"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fgene.2021.716132\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T13:42:17Z","timestamp":1627047737000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fgene.2021.716132\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,23]]},"references-count":73,"alternative-id":["10.3389\/fgene.2021.716132"],"URL":"https:\/\/doi.org\/10.3389\/fgene.2021.716132","relation":{},"ISSN":["1664-8021"],"issn-type":[{"value":"1664-8021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,23]]},"article-number":"716132"}}