{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:56:58Z","timestamp":1777492618976,"version":"3.51.4"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T00:00:00Z","timestamp":1626912000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T00:00:00Z","timestamp":1626912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2021,9]]},"DOI":"10.1007\/s11517-021-02412-z","type":"journal-article","created":{"date-parts":[[2021,7,21]],"date-time":"2021-07-21T22:07:20Z","timestamp":1626905240000},"page":"1723-1734","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Computational predictions for protein sequences of COVID-19 virus via machine learning algorithms"],"prefix":"10.1007","volume":"59","author":[{"given":"Heba M.","family":"Afify","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad S.","family":"Zanaty","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,7,22]]},"reference":[{"issue":"4","key":"2412_CR1","doi-asserted-by":"publisher","first-page":"2006","DOI":"10.26355\/eurrev_202002_20378","volume":"24","author":"S Kannan","year":"2020","unstructured":"Kannan S, Shaik Syed Ali P, Sheeza A, Hemalatha K (2020) COVID-19 (novel coronavirus 2019) \u2013 recent trends. SARS Eur Rev Med Pharmacol Sci 24(4):2006\u20132011. https:\/\/doi.org\/10.26355\/eurrev_202002_20378","journal-title":"SARS Eur Rev Med Pharmacol Sci"},{"key":"2412_CR2","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1038\/s41586-020-2012-7","volume":"579","author":"P Zhou","year":"2020","unstructured":"Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W et al (2020) A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579:270\u2013273. https:\/\/doi.org\/10.1038\/s41586-020-2012-7","journal-title":"Nature"},{"issue":"8","key":"2412_CR3","doi-asserted-by":"publisher","first-page":"692","DOI":"10.1056\/NEJMp2000929","volume":"382","author":"VJ Munster","year":"2020","unstructured":"Munster VJ, Koopmans M, van Doremalen N, van Riel D, de Wit E (2020) A novel coronavirus emerging in china - key questions for impact assessment. N Engl J Med 382(8):692\u2013694. https:\/\/doi.org\/10.1056\/NEJMp2000929","journal-title":"N Engl J Med"},{"issue":"13","key":"2412_CR4","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1056\/NEJMoa2001316","volume":"382","author":"Q Li","year":"2020","unstructured":"Li Q, Guan X, Wu P et al (2020) Early transmission dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N Engl J Med 382(13):1199\u20131207. https:\/\/doi.org\/10.1056\/NEJMoa2001316","journal-title":"N Engl J Med"},{"key":"2412_CR5","unstructured":"Centers for Disease Control and Prevention (2019) Novel coronavirus (2019-nCoV), Wuhan, China (2019). https:\/\/www.cdc.gov\/coronavirus\/2019-nCoV\/summary.html"},{"issue":"4","key":"2412_CR6","doi-asserted-by":"publisher","first-page":"e0232391","DOI":"10.1371\/journal.pone.0232391","volume":"15","author":"GS Randhawa","year":"2020","unstructured":"Randhawa GS, Soltysiak MPM, El Roz H, de Souza CPE, Hill KA, Kari L (2020) Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study. PLoS ONE 15(4):e0232391. https:\/\/doi.org\/10.1371\/journal.pone.0232391","journal-title":"PLoS ONE"},{"key":"2412_CR7","unstructured":"NCBI virus: https:\/\/www.ncbi.nlm.nih.gov\/labs\/virus\/vssi\/#\/virus?SeqType_s=Nucleotide&VirusLineage_ss=Severe%20acute%20respiratory%20syndrome%20coronavirus%202%20(SARS-CoV2),%20taxid:2697049. [dataset]"},{"key":"2412_CR8","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1038\/s41586-020-2286-9","volume":"583","author":"DE Gordon","year":"2020","unstructured":"Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K, White KM et al (2020) A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature 583:459\u2013468. https:\/\/doi.org\/10.1038\/s41586-020-2286-9","journal-title":"Nature"},{"key":"2412_CR9","doi-asserted-by":"publisher","first-page":"1581","DOI":"10.1007\/s10096-016-2716-7","volume":"35","author":"R Sen","year":"2016","unstructured":"Sen R, Nayak L, De RK (2016) A review on host-pathogen interactions: classification and prediction. Eur J Clin Microbiol Infect Dis 35:1581\u20131599. https:\/\/doi.org\/10.1007\/s10096-016-2716-7","journal-title":"Eur J Clin Microbiol Infect Dis"},{"key":"2412_CR10","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.dib.2016.05.014","volume":"8","author":"H Huang","year":"2016","unstructured":"Huang H, Alvarez S, Nusinow DA (2016) Data on the identification of protein interactors with the Evening Complex and PCH1 in Arabidopsis using tandem affinity purification and mass spectrometry (TAP\u2013MS). Data Brief 8:56\u201360. https:\/\/doi.org\/10.1016\/j.dib.2016.05.014","journal-title":"Data Brief"},{"key":"2412_CR11","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1101\/pdb.prot086157","volume":"5","author":"J Mehla","year":"2015","unstructured":"Mehla J, Caufield JH, Uetz P (2015) Mapping protein-protein interactions using yeast two-hybrid assays. Cold Spring Harb Protoc 5:442\u2013452. https:\/\/doi.org\/10.1101\/pdb.prot086157","journal-title":"Cold Spring Harb Protoc"},{"issue":"6868","key":"2412_CR12","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1038\/415180a","volume":"415","author":"Y Ho","year":"2002","unstructured":"Ho Y, Gruhler A, Heilbut A, Bader GD, Moore L, Adams SL, Millar A, Taylor P, Bennett K, Boutilier K (2002) Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415(6868):180\u2013183. https:\/\/doi.org\/10.1038\/415180a","journal-title":"Nature"},{"issue":"1","key":"2412_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12033-007-0069-2","volume":"38","author":"L Skrabanek","year":"2008","unstructured":"Skrabanek L, Saini HK, Bader GD, Enright AJ (2008) Computational prediction of protein-protein interactions. Mol Biotechnol 38(1):1\u201317. https:\/\/doi.org\/10.1007\/s12033-007-0069-2","journal-title":"Mol Biotechnol"},{"issue":"Suppl 15","key":"2412_CR14","doi-asserted-by":"publisher","first-page":"S9","DOI":"10.1186\/1471-2105-15-S15-S9","volume":"15","author":"ZH You","year":"2014","unstructured":"You ZH, Zhu L, Zheng CH, Yu HJ, Deng SP, Ji Z (2014) Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set. BMC Bioinform 15(Suppl 15):S9. https:\/\/doi.org\/10.1186\/1471-2105-15-S15-S9","journal-title":"BMC Bioinform"},{"issue":"1","key":"2412_CR15","doi-asserted-by":"publisher","first-page":"899","DOI":"10.2174\/1574893611666151119221435","volume":"11","author":"J Zeng","year":"2016","unstructured":"Zeng J, Li D, Wu Y, Zou Q, Liu X (2016) An empirical study of features fusion techniques for protein-protein interaction prediction. Curr Bioinform 11(1):899\u2013901. https:\/\/doi.org\/10.2174\/1574893611666151119221435","journal-title":"Curr Bioinform"},{"issue":"5","key":"2412_CR16","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.3390\/ijms18051029","volume":"18","author":"Y Wang","year":"2017","unstructured":"Wang Y, You Z, Li X, Chen X, Jiang T, Zhang J (2017) PCVMZM: using the probabilistic classification vector machines model combined with a zernike moments descriptor to predict protein-protein interactions from protein sequences. Int J Mol Sci 18(5):1029. https:\/\/doi.org\/10.3390\/ijms18051029","journal-title":"Int J Mol Sci"},{"key":"2412_CR17","doi-asserted-by":"publisher","unstructured":"He H, Zhao J, Sun G (2019) Computational prediction of MoRFs based on protein sequences and minimax probability machine. BMC Bioinformatics 20(529). https:\/\/doi.org\/10.1186\/s12859-019-3111-z","DOI":"10.1186\/s12859-019-3111-z"},{"issue":"11","key":"2412_CR18","doi-asserted-by":"publisher","first-page":"4337","DOI":"10.1073\/pnas.0607879104","volume":"104","author":"J Shen","year":"2007","unstructured":"Shen J, Zhang J, Luo X, Zhu W, Yu K, Chen K, Li Y, Jiang H (2007) Predicting protein-protein interactions based only on sequences information. Proc Natl Acad Sci U S A 104(11):4337\u20134341. https:\/\/doi.org\/10.1073\/pnas.0607879104","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"1","key":"2412_CR19","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1186\/s12859-015-0828-1","volume":"16","author":"H Wang","year":"2015","unstructured":"Wang H, Hu X (2015) Accurate prediction of nuclear receptors with conjoint triad feature. BMC Bioinf 16(1):402. https:\/\/doi.org\/10.1186\/s12859-015-0828-1","journal-title":"BMC Bioinf"},{"issue":"4","key":"2412_CR20","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1021\/acs.jproteome.0c00129","volume":"19","author":"C Zhang","year":"2020","unstructured":"Zhang C, Zheng W, Huang X, Bell EW, Zhou X, Zhang Y (2020) Protein structure and sequence reanalysis of 2019-nCoV genome refutes snakes as its intermediate host and the unique similarity between its spike protein insertions and HIV-1. J Proteome Res 19(4):1351\u20131360. https:\/\/doi.org\/10.1021\/acs.jproteome.0c00129","journal-title":"J Proteome Res"},{"issue":"1","key":"2412_CR21","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s40249-020-00649-8","volume":"9","author":"X Li Qiang","year":"2020","unstructured":"Li Qiang X, Xu V, Fang G, Liu W-B, Kou Z (2020) Using the spike protein feature to predict infection risk and monitor the evolutionary dynamic of coronavirus. Infect Dis Poverty 9(1):33. https:\/\/doi.org\/10.1186\/s40249-020-00649-8","journal-title":"Infect Dis Poverty"},{"key":"2412_CR22","doi-asserted-by":"publisher","unstructured":"Zhou Y, Hou Y, Shen J, Huang Y, Martin W, Cheng F (2020) Network-based drug repurposing for novel coronavirus 2019-nCoV\/SARS-CoV-2. Cell Discov 6(14). https:\/\/doi.org\/10.1038\/s41421-020-0153-3","DOI":"10.1038\/s41421-020-0153-3"},{"issue":"31","key":"2412_CR23","doi-asserted-by":"publisher","first-page":"4895","DOI":"10.1016\/j.vaccine.2010.05.031","volume":"28","author":"MP Girard","year":"2010","unstructured":"Girard MP, Tam JS, Assossou OM, Kieny MP (2010) The 2009 A (H1N1) influenza virus pandemic: A review. Vaccine 28(31):4895\u20134902. https:\/\/doi.org\/10.1016\/j.vaccine.2010.05.031","journal-title":"Vaccine"},{"key":"2412_CR24","doi-asserted-by":"publisher","first-page":"1391265","DOI":"10.1155\/2018\/1391265","volume":"2018","author":"S Alguwaizani","year":"2018","unstructured":"Alguwaizani S, Park B, Zhou X, Huang DS, Han K (2018) Predicting interactions between virus and host proteins using repeat patterns and composition of amino acids. J Healthc Eng 2018:1391265. https:\/\/doi.org\/10.1155\/2018\/1391265","journal-title":"J Healthc Eng"},{"key":"2412_CR25","unstructured":"Golemis E, Adams PD (2005) Protein-protein interactions: a molecular cloning manual, 2nd edn. CSHL Press, New York"},{"key":"2412_CR26","doi-asserted-by":"publisher","first-page":"012031","DOI":"10.1088\/1742-6596\/1218\/1\/012031","volume":"1218","author":"M Isa Irawan","year":"2019","unstructured":"Isa Irawan M, Mukhlash I, Rizky A, RirisatiDewi A (2019) Application of Needleman-Wunch Algorithm to identify mutation in DNA sequences of corona virus. J Phys Conf Ser 1218:012031. https:\/\/doi.org\/10.1088\/1742-6596\/1218\/1\/012031","journal-title":"J Phys Conf Ser"},{"key":"2412_CR27","doi-asserted-by":"publisher","unstructured":"Desautels T, Zemla A, Lau E, Franco M, Faissol D (2020) Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing. bioRxiv. https:\/\/doi.org\/10.1101\/2020.04.03.024885","DOI":"10.1101\/2020.04.03.024885"},{"key":"2412_CR28","doi-asserted-by":"publisher","unstructured":"Dey L, Chakraborty S, Mukhopadhyay A (2020) Machine learning techniques for sequence-based prediction of viral\u2013host interactions between SARS-CoV-2 and human proteins. Biomed J. https:\/\/doi.org\/10.1016\/j.bj.2020.08.003","DOI":"10.1016\/j.bj.2020.08.003"},{"key":"2412_CR29","doi-asserted-by":"publisher","first-page":"1075","DOI":"10.1038\/s10038-020-0808-9","volume":"65","author":"Y Toyoshima","year":"2020","unstructured":"Toyoshima Y, Nemoto K, Matsumoto S, Nakamura Y, Kiyotani K (2020) SARS-CoV-2 genomic variations associated with mortality rate of COVID-19. J Hum Genet 65:1075\u20131082. https:\/\/doi.org\/10.1038\/s10038-020-0808-9","journal-title":"J Hum Genet"},{"issue":"58","key":"2412_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12936-017-1734-y","volume":"16","author":"A Wiebe","year":"2017","unstructured":"Wiebe A, Longbottom J, Gleave K, Shearer FM, Sinka ME, Massey NC et al (2017) Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance. Malar J 16(58):1\u201310. https:\/\/doi.org\/10.1186\/s12936-017-1734-y","journal-title":"Malar J"},{"key":"2412_CR31","unstructured":"Aghajanbaglo S, Moosavi S, Rahgozar M, Rahimi A (2014) Predicting protein-protein interactions based on rotation of proteins in 3D-space, The Second International Workshop on Parallelism in Bioinformatics (PBio 2014), as part of IEEE Cluster"},{"issue":"1","key":"2412_CR32","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1080\/21655979.2018.1470721","volume":"9","author":"H Wang","year":"2018","unstructured":"Wang H, Wu P (2018) Prediction of RNA-protein interactions using conjoint triad feature and chaos game representation. Bioengineered 9(1):242\u2013251. https:\/\/doi.org\/10.1080\/21655979.2018.1470721","journal-title":"Bioengineered"},{"issue":"11","key":"2412_CR33","doi-asserted-by":"publisher","first-page":"2373","DOI":"10.3390\/ijms18112373","volume":"18","author":"J Wang","year":"2017","unstructured":"Wang J, Zhang L, Jia L, Ren Y, Yu G (2017) Protein-protein interactions prediction using a novel local conjoint triad descriptor of amino acid sequences. Int J Mol Sci 18(11):2373. https:\/\/doi.org\/10.3390\/ijms18112373","journal-title":"Int J Mol Sci"},{"key":"2412_CR34","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.mbs.2019.04.002","volume":"313","author":"X Wang","year":"2019","unstructured":"Wang X, Wang R, Wei Y, Gui Y (2019) A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence. Math Biosci 313:41\u201347. https:\/\/doi.org\/10.1016\/j.mbs.2019.04.002","journal-title":"Math Biosci"},{"key":"2412_CR35","unstructured":"Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Zakrzewski VG, Montgomery JA, Stratmann RE, Burant JC, et al (2003) GAUSSIAN 03 (Gaussian, Pittsburgh, PA), Revision C.02"},{"issue":"2836236","key":"2412_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2020\/2836236","volume":"2020","author":"M K\u00fcrsad U\u00e7ar","year":"2020","unstructured":"K\u00fcrsad U\u00e7ar M, Nour M, Sindi H, Polat K (2020) The effect of training and testing process on machine learning in biomedical datasets. Math Probl Eng 2020(2836236):1\u201317. https:\/\/doi.org\/10.1155\/2020\/2836236","journal-title":"Math Probl Eng"},{"key":"2412_CR37","doi-asserted-by":"crossref","unstructured":"Witten IH, Frank E, and Hall MA (2011) Credibility: evaluating what\u2019s been learned, in data mining: practical machine learning tools and techniques. Morgan Kaufmann, Burlington, pp 147\u2013187","DOI":"10.1016\/B978-0-12-374856-0.00005-5"},{"key":"2412_CR38","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1016\/S1532-0464(03)00034-0","volume":"35","author":"S Dreiseitla","year":"2002","unstructured":"Dreiseitla S, Ohno-Machado L (2002) Logistic regression and artificial neural network classification models: a methodology review. J Biomed Inform 35:352\u2013359. https:\/\/doi.org\/10.1016\/S1532-0464(03)00034-0","journal-title":"J Biomed Inform"},{"key":"2412_CR39","unstructured":"Cunningham P, Delany SJ (2007) k-Nearest neighbour classifiers, Technical Report UCD-CSI-2007\u20134, 1\u201317"},{"key":"2412_CR40","doi-asserted-by":"crossref","unstructured":"Evgeniou T, Pontil M (2001) Support vector machines: theory and applications, ACAI 1999: Machine Learning and Its Applications 249\u2013257","DOI":"10.1007\/3-540-44673-7_12"},{"key":"2412_CR41","unstructured":"Rish I (2001) An empirical study of the naive bayes classifier. In: IJCAI 2001 workshop on empirical methods in artificial intelligence, vol 3. IBM, New York, pp 41\u201346"},{"key":"2412_CR42","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.knosys.2015.02.019","volume":"82","author":"A Gutierrez-Rodr\u00edguez","year":"2015","unstructured":"Gutierrez-Rodr\u00edguez A, Mart\u00ednez-Trinidad JF, Garc\u00eda-Borroto M, Carrasco- Ochoa J (2015) Mining patterns for clustering on numerical datasets using unsupervised decision trees. Knowl. Based Syst 82:70\u201379. https:\/\/doi.org\/10.1016\/j.knosys.2015.02.019","journal-title":"Knowl. Based Syst"},{"key":"2412_CR43","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random Forests. Mach Learn 45:5\u201332. https:\/\/doi.org\/10.1023\/A:1010933404324","journal-title":"Mach Learn"},{"issue":"4","key":"2412_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/1043659620917724","volume":"31","author":"D Bruns","year":"2020","unstructured":"Bruns D, Kraguljac N, Bruns T (2020) COVID- 19: facts, cultural considerations, and risk of stigmatization. J Transcult Nurs 31(4):1\u20137. https:\/\/doi.org\/10.1177\/1043659620917724","journal-title":"J Transcult Nurs"},{"key":"2412_CR45","first-page":"e13525","volume":"00","author":"M Becerra-Flores","year":"2020","unstructured":"Becerra-Flores M, Cardozo T (2020) SARS-CoV-2 viral spike G614 mutation exhibits higher case fatality rate. Int J Clin Pract 00:e13525","journal-title":"Int J Clin Pract"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-021-02412-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-021-02412-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-021-02412-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,23]],"date-time":"2021-08-23T13:24:13Z","timestamp":1629725053000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-021-02412-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,22]]},"references-count":45,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2021,9]]}},"alternative-id":["2412"],"URL":"https:\/\/doi.org\/10.1007\/s11517-021-02412-z","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-34004\/v1","asserted-by":"object"},{"id-type":"doi","id":"10.21203\/rs.3.rs-34004\/v2","asserted-by":"object"}]},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,22]]},"assertion":[{"value":"28 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 July 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}