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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">dt</journal-id><journal-title-group><journal-title xml:lang="ru">Цифровая трансформация</journal-title><trans-title-group xml:lang="en"><trans-title>Digital Transformation</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2522-9613</issn><issn pub-type="epub">2524-2822</issn><publisher><publisher-name>Educational Establishment “Belarusian State University of Informatics and Radioelectronics”</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">dt-635</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ТЕХНИЧЕСКИЕ НАУКИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>TECHNICAL SCIENCES</subject></subj-group></article-categories><title-group><article-title>Программное обеспечение и возможности современных языков программирования для изучения биоинформатики и вычислительной вакцинологии новой коронавирусной инфекции</article-title><trans-title-group xml:lang="en"><trans-title>Software and Resources of Modern Programming Languages for Bioinformatics and Computational Vaccinology Research of the New Coronavirus Infection</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Спринджук</surname><given-names>М. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Sprindzuk</surname><given-names>M. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>к. т. н., старший научный сотрудник лаборатории математической кибернетики</p><p>ул. Сурганова, д. 6, 220012, г. Минск</p></bio><bio xml:lang="en"><p>TechSciPhD, Senior Researcher, laboratory of mathematical Cybernetics</p><p>Surganovа Str., 6, 220012 Minsk</p></bio><email xlink:type="simple">stepanenkomatvei@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Владыко</surname><given-names>А. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Vladyko</surname><given-names>A. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>д. м. н., профессор, главный научный сотрудник лаборатории биотехнологии и иммунодиагностики</p><p>ул. Филимонова, д. 23, 220114, г. Минск</p></bio><bio xml:lang="en"><p>Doctor of Sciences (Medical), Professor, chief researcher of the biotechnology and immunodiagnosis laboratory</p><p>Filimonova Str., 23, 220114 Minsk</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Титов</surname><given-names>Л. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Titov</surname><given-names>L. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>д. м. н., профессор, член – корреспондент НАН Беларуси, заведующий лабораторией клинической и экспериментальной микробиологии</p><p>ул. Филимонова, д. 23, 220114, г. Минск</p></bio><bio xml:lang="en"><p>Doctor of Sciences (Medical), Professor, Corresponding Member of the NAS of Belarus, Head of the Laboratory for Clinical and Experimental Microbiology</p><p>Filimonova Str., 23, 220114 Minsk</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кончиц</surname><given-names>А. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Konchits</surname><given-names>A. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>к. б. н., ведущий научный сотрудник лаборатории лесной селекции и семеноводства</p><p>ул. Пролетарская, д. 71, 246001, г. Гомель</p></bio><bio xml:lang="en"><p>BioSciPhD Leading Researcher, Forest Tree Breeding and Seed Production Laboratory</p><p>71 Proletarskaya Str., 246001 Gomel</p></bio><email xlink:type="simple">konchits@yandex.ru</email><xref ref-type="aff" rid="aff-3"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Объединенный институт проблем информатики НАН Беларуси</institution></aff><aff xml:lang="en"><institution>United Institute for Informatics Problems of the NAS of Belarus</institution></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>РНПЦ эпидемиологии и микробиологии</institution></aff><aff xml:lang="en"><institution>RRPC for Epidemiology and Microbiology, Republic of Belarus</institution></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru"><institution>Институт леса НАН Беларуси</institution></aff><aff xml:lang="en"><institution>Forest Research Institute of the NAS of Belarus</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>08</day><month>10</month><year>2021</year></pub-date><volume>0</volume><issue>3</issue><fpage>47</fpage><lpage>57</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Спринджук М.В., Владыко А.С., Титов Л.П., Кончиц А.П., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Спринджук М.В., Владыко А.С., Титов Л.П., Кончиц А.П.</copyright-holder><copyright-holder xml:lang="en">Sprindzuk M.V., Vladyko A.S., Titov L.P., Konchits A.P.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://dt.bsuir.by/jour/article/view/635">https://dt.bsuir.by/jour/article/view/635</self-uri><abstract><p>Обзорная статья сосредоточена на вопросах применения программного обеспечения для целей геномики, иммуноинформатики, вычислительной вакцинологии, математической эпидемиологии и филогенеза новой коронавирусной инфекции. Приводится разработанная авторами классификация программного обеспечения для изучения COVID-19.</p></abstract><trans-abstract xml:lang="en"><p>The review paper focuses on the application of software for the purposes of genomics, immunoinformatics, computational vaccinology, mathematical epidemiology and phylogeny of the new coronavirus infection. Authors provide a classification of software for the investigation of COVID-19.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>SARS-CoV-2</kwd><kwd>COVID-19</kwd><kwd>коронавирус</kwd><kwd>эпидемия</kwd><kwd>пандемия</kwd><kwd>автоматизированные системы обработки данных</kwd><kwd>программное обеспечение</kwd><kwd>медицинская кибернетика</kwd><kwd>геномика</kwd><kwd>транскриптомика</kwd><kwd>системы медицинского назначения</kwd><kwd>иммуноинформатика</kwd></kwd-group><kwd-group xml:lang="en"><kwd>SARS-CoV-2</kwd><kwd>COVID-19</kwd><kwd>coronavirus</kwd><kwd>epidemic</kwd><kwd>pandemic</kwd><kwd>automated data processing systems</kwd><kwd>software</kwd><kwd>medical cybernetics</kwd><kwd>genomics</kwd><kwd>transcriptomics</kwd><kwd>medical systems</kwd><kwd>immunoinformatics</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Tomar, Marton. Immunoinformatics. – P [S.l.]: Springer US, 2020. – 409 p.</mixed-citation><mixed-citation xml:lang="en">Tomar, Marton. Immunoinformatics. – P [S.l.]: Springer US, 2020. – 409 p.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">De, R.K., Tomar, N. Immunoinformatics. – New York: Humana Press, 2014. – P xix, 586 pages.</mixed-citation><mixed-citation xml:lang="en">De, R.K., Tomar, N. Immunoinformatics. – New York: Humana Press, 2014. – P xix, 586 pages.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Schönbach, C., Ranganathan, S., Brusic, V. Immunoinformatics. – New York: Springer, 2008. – xix, 200 p.</mixed-citation><mixed-citation xml:lang="en">Schönbach, C., Ranganathan, S., Brusic, V. Immunoinformatics. – New York: Springer, 2008. – xix, 200 p.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Flower, D.R. Bioinformatics for vaccinology. – Chichester, West Sussex, England; Hoboken, NJ: John Wiley &amp; Sons, 2008. – 314 p.</mixed-citation><mixed-citation xml:lang="en">Flower, D.R. Bioinformatics for vaccinology. – Chichester, West Sussex, England; Hoboken, NJ: John Wiley &amp; Sons, 2008. – 314 p.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Prabhakar, H., Kapoor, I., Mahajan, C. Clinical synopsis of COVID-19: evolving and challenging. – 1 online resource (XIV, 260 pages).</mixed-citation><mixed-citation xml:lang="en">Prabhakar, H., Kapoor, I., Mahajan, C. Clinical synopsis of COVID-19: evolving and challenging. – 1 online resource (XIV, 260 pages).</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Chandra, P., Roy, S. Diagnostic strategies for COVID-19 and other coronaviruses. – Singapore: Springer, 2020. – 1 online resource (viii, 199 pages).</mixed-citation><mixed-citation xml:lang="en">Chandra, P., Roy, S. Diagnostic strategies for COVID-19 and other coronaviruses. – Singapore: Springer, 2020. – 1 online resource (viii, 199 pages).</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Saxena, S.K. Coronavirus disease 2019 (COVID-19): epidemiology, pathogenesis, diagnosis, and therapeutics. – 1 online resource (224 pages).</mixed-citation><mixed-citation xml:lang="en">Saxena, S.K. Coronavirus disease 2019 (COVID-19): epidemiology, pathogenesis, diagnosis, and therapeutics. – 1 online resource (224 pages).</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Plotkin, S.A., Orenstein, W.A., Offit, P.A. Plotkin's vaccines. – Philadelphia, PA: Elsevier, 2018. – xxi, 1691 pages.</mixed-citation><mixed-citation xml:lang="en">Plotkin, S.A., Orenstein, W.A., Offit, P.A. Plotkin's vaccines. – Philadelphia, PA: Elsevier, 2018. – xxi, 1691 pages.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Enjuanes, L. Coronavirus replication and reverse genetics. – Berlin; New York: Springer, 2005. – vii, 257 p.</mixed-citation><mixed-citation xml:lang="en">Enjuanes, L. Coronavirus replication and reverse genetics. – Berlin; New York: Springer, 2005. – vii, 257 p.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Varshney, D., Singh, M., SpringerLink (Online service). Lyophilized Biologics and Vaccines Modality – Based Approaches. – New York, NY: Springer New York: Imprint: Springer, 2015. – XI, 401 p. 99 illus., 68 illus. in color.</mixed-citation><mixed-citation xml:lang="en">Varshney, D., Singh, M., SpringerLink (Online service). Lyophilized Biologics and Vaccines Modality – Based Approaches. – New York, NY: Springer New York: Imprint: Springer, 2015. – XI, 401 p. 99 illus., 68 illus. in color.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Nunnally, B.K., Turula, V.E., Sitrin, R.D., SpringerLink (Online service). Vaccine Analysis: Strategies, Principles, and Control. – Berlin, Heidelberg: Springer Berlin Heidelberg: Imprint: Springer, 2015. – XII, 665 p. 124 illus., 76 illus. in color.</mixed-citation><mixed-citation xml:lang="en">Nunnally, B.K., Turula, V.E., Sitrin, R.D., SpringerLink (Online service). Vaccine Analysis: Strategies, Principles, and Control. – Berlin, Heidelberg: Springer Berlin Heidelberg: Imprint: Springer, 2015. – XII, 665 p. 124 illus., 76 illus. in color.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Maier, H.J., Bickerton, E., Britton, P. Coronaviruses methods and protocols. – New York: Humana Press; Springer, 2015. – xi, 285 pages.</mixed-citation><mixed-citation xml:lang="en">Maier, H.J., Bickerton, E., Britton, P. Coronaviruses methods and protocols. – New York: Humana Press; Springer, 2015. – xi, 285 pages.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Kiyono, H., Ogra, P.L., McGhee, J.R. Mucosal vaccines. – San Diego: Academic Press, 1996. – xix, 479 p.</mixed-citation><mixed-citation xml:lang="en">Kiyono, H., Ogra, P.L., McGhee, J.R. Mucosal vaccines. – San Diego: Academic Press, 1996. – xix, 479 p.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Vanniasinkam, T., Tikoo, S.K., Samal, S.K. Viral vectors in veterinary vaccine development: a textbook. – Cham, Switzerland: Springer, 2021. – 1 online resource (xi, 230 pages).</mixed-citation><mixed-citation xml:lang="en">Vanniasinkam, T., Tikoo, S.K., Samal, S.K. Viral vectors in veterinary vaccine development: a textbook. – Cham, Switzerland: Springer, 2021. – 1 online resource (xi, 230 pages).</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Hwang, W., Lei, W., Katritsis, N.M. et al. Current and prospective computational approaches and challenges for developing COVID-19 vaccines // Advanced Drug Delivery Reviews. – 2021. epub.</mixed-citation><mixed-citation xml:lang="en">Hwang, W., Lei, W., Katritsis, N.M. et al. Current and prospective computational approaches and challenges for developing COVID-19 vaccines // Advanced Drug Delivery Reviews. – 2021. epub.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Sohail, M.S., Ahmed, S.F., Quadeer, A.A., McKay, M.R. In silico T cell epitope identification for SARS– CoV– 2: Progress and perspectives // Adv Drug Deliv Rev. – 2021. – Vol. 171, – P. 29-47.</mixed-citation><mixed-citation xml:lang="en">Sohail, M.S., Ahmed, S.F., Quadeer, A.A., McKay, M.R. In silico T cell epitope identification for SARS– CoV– 2: Progress and perspectives // Adv Drug Deliv Rev. – 2021. – Vol. 171, – P. 29-47.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Noorimotlagh, Z., Karami, C., Mirzaee, S.A. et al. Immune and bioinformatics identification of T cell and B cell epitopes in the protein structure of SARS–CoV–2: A systematic review // Int Immunopharmacol. – 2020. – Vol. 86. – P. 106738.</mixed-citation><mixed-citation xml:lang="en">Noorimotlagh, Z., Karami, C., Mirzaee, S.A. et al. Immune and bioinformatics identification of T cell and B cell epitopes in the protein structure of SARS–CoV–2: A systematic review // Int Immunopharmacol. – 2020. – Vol. 86. – P. 106738.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Baruah, V., Bose, S. Immunoinformatics aided identification of T cell and B cell epitopes in the surface glycoprotein of 2019 nCoV // Journal of medical virology. – 2020. – Vol. 92, No. 5. – P. 495-500.</mixed-citation><mixed-citation xml:lang="en">Baruah, V., Bose, S. Immunoinformatics aided identification of T cell and B cell epitopes in the surface glycoprotein of 2019 nCoV // Journal of medical virology. – 2020. – Vol. 92, No. 5. – P. 495-500.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Oliveira, S.C., de Magalhães, M.T., Homan, E.J. Immunoinformatic Analysis of SARS–CoV–2 Nucleocapsid Protein and Identification of COVID–19 Vaccine Targets // Frontiers in immunology. – 2020. – Vol. 11. – P. 2758.</mixed-citation><mixed-citation xml:lang="en">Oliveira, S.C., de Magalhães, M.T., Homan, E.J. Immunoinformatic Analysis of SARS–CoV–2 Nucleocapsid Protein and Identification of COVID–19 Vaccine Targets // Frontiers in immunology. – 2020. – Vol. 11. – P. 2758.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Feng, Y., Qiu, M., Zou, S. et al. Multi–epitope vaccine design using an immunoinformatics approach for 2019 novel coronavirus in China (SARS–CoV–2) // BioRxiv. – 2020. – Vol. 1, No. 1. – P. 1-12.</mixed-citation><mixed-citation xml:lang="en">Feng, Y., Qiu, M., Zou, S. et al. Multi–epitope vaccine design using an immunoinformatics approach for 2019 novel coronavirus in China (SARS–CoV–2) // BioRxiv. – 2020. – Vol. 1, No. 1. – P. 1-12.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Wang, X., Xu, W., Tong, D. et al. A chimeric multi– epitope DNA vaccine elicited specific antibody response against severe acute respiratory syndrome – associated coronavirus which attenuated the virulence of SARS–CoV in vitro // Immunology letters. – 2008. – Vol. 119, No. 1– 2. – P. 71-77.</mixed-citation><mixed-citation xml:lang="en">Wang, X., Xu, W., Tong, D. et al. A chimeric multi– epitope DNA vaccine elicited specific antibody response against severe acute respiratory syndrome – associated coronavirus which attenuated the virulence of SARS–CoV in vitro // Immunology letters. – 2008. – Vol. 119, No. 1– 2. – P. 71-77.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Belikova Y., Samsonov Y., Abakushina E. Modern vaccines and coronavirus infections. Research and Practical Medicine Journal, 2020, Vol 7, No. 4. pp. 135-154. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Belikova Y., Samsonov Y., Abakushina E. Modern vaccines and coronavirus infections. Research and Practical Medicine Journal, 2020, Vol 7, No. 4. pp. 135-154. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Kononov A., Mishchenko V., Dumova B. et al. Antigenic properties of bovine coronavirus vaccine with various adjuvants. Proceedings of the Federal Center for Animal Health, 2009, Vol 7, pp. 50-55. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Kononov A., Mishchenko V., Dumova B. et al. Antigenic properties of bovine coronavirus vaccine with various adjuvants. Proceedings of the Federal Center for Animal Health, 2009, Vol 7, pp. 50-55. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Kharchenko E. P. Coronavirus SARS-Cov-2: the complexity of pathogenesis, the search for vaccines and future pandemics. Epidemiology and Vaccine Prevention, 2020, Vol 19, No. 3. pp. 4-20. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Kharchenko E. P. Coronavirus SARS-Cov-2: the complexity of pathogenesis, the search for vaccines and future pandemics. Epidemiology and Vaccine Prevention, 2020, Vol 19, No. 3. pp. 4-20. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Ozharovskaya T., Zubkova O., Dolzhikova I. et al. Immunogenicity of various forms of glycoprotein S of the Middle East respiratory syndrome coronavirus. Acta Naturae (Russian version), 2019, Vol 11, No. 1 (40). pp. 38-47. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Ozharovskaya T., Zubkova O., Dolzhikova I. et al. Immunogenicity of various forms of glycoprotein S of the Middle East respiratory syndrome coronavirus. Acta Naturae (Russian version), 2019, Vol 11, No. 1 (40). pp. 38-47. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Chepurnov A. A., Sharshov K. A., Kazachinskaya E. I. et al. Antigenic properties of SARS-CoV-2 / human / RUS / Nsk-FRCFTM-1/202 coronavirus isolate isolated from a patient in Novosibirsk. Journal of Infectology, 2020, Vol 12, No. 3. pp. 42-50. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Chepurnov A. A., Sharshov K. A., Kazachinskaya E. I. et al. Antigenic properties of SARS-CoV-2 / human / RUS / Nsk-FRCFTM-1/202 coronavirus isolate isolated from a patient in Novosibirsk. Journal of Infectology, 2020, Vol 12, No. 3. pp. 42-50. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Kharchenko E.P. SARS-CoV-2 coronavirus: features of structural proteins, contagiousness and possible immune collisions. Epidemiology and Vaccine Prevention, 2020, Vol 19, No. 2. pp. 13-30. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Kharchenko E.P. SARS-CoV-2 coronavirus: features of structural proteins, contagiousness and possible immune collisions. Epidemiology and Vaccine Prevention, 2020, Vol 19, No. 2. pp. 13-30. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Titova M.A. Approaches to modeling immunogenic peptides: author. dis. for a job. learned. step. Cand. chem. Sciences: 02.00.10 / Titova Maya Adolfovna. - M., 2003, 23 p. M., 2003..(In Russian).</mixed-citation><mixed-citation xml:lang="en">Titova M.A. Approaches to modeling immunogenic peptides: author. dis. for a job. learned. step. Cand. chem. Sciences: 02.00.10 / Titova Maya Adolfovna. - M., 2003, 23 p. M., 2003..(In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Hu, T., Li, J., Zhou, H. et al. Bioinformatics resources for SARS–CoV–2 discovery and surveillance // Briefings in Bioinformatics. – 2021. – Vol. 22, No. 2. – P. 631-641.</mixed-citation><mixed-citation xml:lang="en">Hu, T., Li, J., Zhou, H. et al. Bioinformatics resources for SARS–CoV–2 discovery and surveillance // Briefings in Bioinformatics. – 2021. – Vol. 22, No. 2. – P. 631-641.</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Hufsky, F., Lamkiewicz, K., Almeida, A. et al. Computational strategies to combat COVID–19: useful tools to accelerate SARS–CoV–2 and coronavirus research // Briefings in Bioinformatics. – 2020. – Vol. 22, No. 2. – P. 642-663.</mixed-citation><mixed-citation xml:lang="en">Hufsky, F., Lamkiewicz, K., Almeida, A. et al. Computational strategies to combat COVID–19: useful tools to accelerate SARS–CoV–2 and coronavirus research // Briefings in Bioinformatics. – 2020. – Vol. 22, No. 2. – P. 642-663.</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Kangabam, R., Sahoo, S., Ghosh, A. et al. Next– generation computational tools and resources for coronavirus research: From detection to vaccine discovery // Computers in biology and medicine. – 2020. – Vol. 1, No. 1. – P. 104-115.</mixed-citation><mixed-citation xml:lang="en">Kangabam, R., Sahoo, S., Ghosh, A. et al. Next– generation computational tools and resources for coronavirus research: From detection to vaccine discovery // Computers in biology and medicine. – 2020. – Vol. 1, No. 1. – P. 104-115.</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Kiyotani, K., Toyoshima, Y., Nemoto, K., Nakamura, Y. Bioinformatic prediction of potential T cell epitopes for SARS-Cov–2 // Journal of human genetics. – 2020. – Vol. 65, No. 7. – P. 569-575.</mixed-citation><mixed-citation xml:lang="en">Kiyotani, K., Toyoshima, Y., Nemoto, K., Nakamura, Y. Bioinformatic prediction of potential T cell epitopes for SARS-Cov–2 // Journal of human genetics. – 2020. – Vol. 65, No. 7. – P. 569-575.</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Ogishi, M., Yotsuyanagi, H. Quantitative Prediction of the Landscape of T Cell Epitope Immunogenicity in Sequence Space // Frontiers in Immunology. – 2019. – Vol. 10, No. 827. – P. 1-20.</mixed-citation><mixed-citation xml:lang="en">Ogishi, M., Yotsuyanagi, H. Quantitative Prediction of the Landscape of T Cell Epitope Immunogenicity in Sequence Space // Frontiers in Immunology. – 2019. – Vol. 10, No. 827. – P. 1-20.</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Ong, E., Wang, H., Wong, M.U. et al. Vaxign– ML: supervised machine learning reverse vaccinology model for improved prediction of bacterial protective antigens // Bioinformatics. – 2020. – Vol. 36, No. 10. – P. 3185-3191.</mixed-citation><mixed-citation xml:lang="en">Ong, E., Wang, H., Wong, M.U. et al. Vaxign– ML: supervised machine learning reverse vaccinology model for improved prediction of bacterial protective antigens // Bioinformatics. – 2020. – Vol. 36, No. 10. – P. 3185-3191.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Xiang, Z., He, Y. Genome– wide prediction of vaccine targets for human herpes simplex viruses using Vaxign reverse vaccinology // BMC Bioinformatics. – 2013. – Vol. 14, No.1. – P. S2.</mixed-citation><mixed-citation xml:lang="en">Xiang, Z., He, Y. Genome– wide prediction of vaccine targets for human herpes simplex viruses using Vaxign reverse vaccinology // BMC Bioinformatics. – 2013. – Vol. 14, No.1. – P. S2.</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">He, Y., Xiang, Z., Mobley, H.L. Vaxign: the first web– based vaccine design program for reverse vaccinology and applications for vaccine development // J Biomed Biotechnol. – 2010. – Vol. 10, No. Epub 2010 Jul 4. – P. 297505.</mixed-citation><mixed-citation xml:lang="en">He, Y., Xiang, Z., Mobley, H.L. Vaxign: the first web– based vaccine design program for reverse vaccinology and applications for vaccine development // J Biomed Biotechnol. – 2010. – Vol. 10, No. Epub 2010 Jul 4. – P. 297505.</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Vita, R., Overton, J.A., Greenbaum, J.A. et al. The immune epitope database (IEDB) 3.0 // Nucleic Acids Res. –Vol. 43, No. 1. – P. D405-12.</mixed-citation><mixed-citation xml:lang="en">Vita, R., Overton, J.A., Greenbaum, J.A. et al. The immune epitope database (IEDB) 3.0 // Nucleic Acids Res. –Vol. 43, No. 1. – P. D405-12.</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">El– Manzalawy, Y., Dobbs, D., Honavar, V. Predicting linear B–cell epitopes using string kernels // J Mol Recognit. – 2008. – Vol. 21, No. 4. – P. 243-55.</mixed-citation><mixed-citation xml:lang="en">El– Manzalawy, Y., Dobbs, D., Honavar, V. Predicting linear B–cell epitopes using string kernels // J Mol Recognit. – 2008. – Vol. 21, No. 4. – P. 243-55.</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Seemann, T. Prokka: rapid prokaryotic genome annotation // Bioinformatics. – 2014. – Vol. 30, No. 14. – P. 2068-9.</mixed-citation><mixed-citation xml:lang="en">Seemann, T. Prokka: rapid prokaryotic genome annotation // Bioinformatics. – 2014. – Vol. 30, No. 14. – P. 2068-9.</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Huerta-Cepas, J., Szklarczyk, D., Heller, D. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses // Nucleic Acids Res. – 2018. – Vol. 47, No. D1. – P. D309-D314.</mixed-citation><mixed-citation xml:lang="en">Huerta-Cepas, J., Szklarczyk, D., Heller, D. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses // Nucleic Acids Res. – 2018. – Vol. 47, No. D1. – P. D309-D314.</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Jones, P., Binns, D., Chang, H.Y. et al. InterProScan 5: genome–scale protein function classification // Bioinformatics. 2014. – Vol. 30, No. 9. – P. 1236-40.</mixed-citation><mixed-citation xml:lang="en">Jones, P., Binns, D., Chang, H.Y. et al. InterProScan 5: genome–scale protein function classification // Bioinformatics. 2014. – Vol. 30, No. 9. – P. 1236-40.</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Mulder, N., Apweiler, R. InterPro and InterProScan: tools for protein sequence classification and comparison // Methods Mol Biol. – 2007. – Vol.396. – P. 59-70.</mixed-citation><mixed-citation xml:lang="en">Mulder, N., Apweiler, R. InterPro and InterProScan: tools for protein sequence classification and comparison // Methods Mol Biol. – 2007. – Vol.396. – P. 59-70.</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Syed, A., Upton, C. Java GUI for InterProScan (JIPS): a tool to help process multiple InterProScans and perform ortholog analysis // BMC Bioinformatics. – 2006. – Vol. 7. – P. 462.</mixed-citation><mixed-citation xml:lang="en">Syed, A., Upton, C. Java GUI for InterProScan (JIPS): a tool to help process multiple InterProScans and perform ortholog analysis // BMC Bioinformatics. – 2006. – Vol. 7. – P. 462.</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Quevillon, E., Silventoinen, V., Pillai, S. et al. InterProScan: protein domains identifier // Nucleic Acids Res. – 2005. – Vol. 33, No. 1. – P. W116- 20.</mixed-citation><mixed-citation xml:lang="en">Quevillon, E., Silventoinen, V., Pillai, S. et al. InterProScan: protein domains identifier // Nucleic Acids Res. – 2005. – Vol. 33, No. 1. – P. W116- 20.</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Katoh, K., Standley, D.M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability // Mol Biol Evol. – 2013. – Vol. 30, No. 4. – P. 772-80.</mixed-citation><mixed-citation xml:lang="en">Katoh, K., Standley, D.M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability // Mol Biol Evol. – 2013. – Vol. 30, No. 4. – P. 772-80.</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">Katoh, K., Frith, M.C. Adding unaligned sequences into an existing alignment using MAFFT and LAST // Bioinformatics. – 2012. – Vol. 28, No. 23. – P. 3144-6.</mixed-citation><mixed-citation xml:lang="en">Katoh, K., Frith, M.C. Adding unaligned sequences into an existing alignment using MAFFT and LAST // Bioinformatics. – 2012. – Vol. 28, No. 23. – P. 3144-6.</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Katoh, K., Toh, H. Parallelization of the MAFFT multiple sequence alignment program // Bioinformatics. – 2010. – Vol. 26, No. 15. – P. 1899-900.</mixed-citation><mixed-citation xml:lang="en">Katoh, K., Toh, H. Parallelization of the MAFFT multiple sequence alignment program // Bioinformatics. – 2010. – Vol. 26, No. 15. – P. 1899-900.</mixed-citation></citation-alternatives></ref><ref id="cit48"><label>48</label><citation-alternatives><mixed-citation xml:lang="ru">Katoh, K., Asimenos, G., Toh, H. Multiple alignment of DNA sequences with MAFFT // Methods Mol Biol. – 2009. – Vol. 537. – P. 39-64.</mixed-citation><mixed-citation xml:lang="en">Katoh, K., Asimenos, G., Toh, H. Multiple alignment of DNA sequences with MAFFT // Methods Mol Biol. – 2009. – Vol. 537. – P. 39-64.</mixed-citation></citation-alternatives></ref><ref id="cit49"><label>49</label><citation-alternatives><mixed-citation xml:lang="ru">Hung, C.L., Lin, Y.S., Lin, C.Y. et al. CUDA ClustalW: An efficient parallel algorithm for progressive multiple sequence alignment on Multi– GPUs // Comput Biol Chem. – Vol. 58. – P. 62-8.</mixed-citation><mixed-citation xml:lang="en">Hung, C.L., Lin, Y.S., Lin, C.Y. et al. CUDA ClustalW: An efficient parallel algorithm for progressive multiple sequence alignment on Multi– GPUs // Comput Biol Chem. – Vol. 58. – P. 62-8.</mixed-citation></citation-alternatives></ref><ref id="cit50"><label>50</label><citation-alternatives><mixed-citation xml:lang="ru">Hung, J.H., Weng, Z. Sequence Alignment and Homology Search with BLAST and ClustalW // Cold Spring Harb Protoc. 2016. – Vol. 16, No. 11. – P. 1-10.</mixed-citation><mixed-citation xml:lang="en">Hung, J.H., Weng, Z. Sequence Alignment and Homology Search with BLAST and ClustalW // Cold Spring Harb Protoc. 2016. – Vol. 16, No. 11. – P. 1-10.</mixed-citation></citation-alternatives></ref><ref id="cit51"><label>51</label><citation-alternatives><mixed-citation xml:lang="ru">Vangala, R.K., Singh, L., Gupta, R.P. BioParishodhana: A novel graphical interface integrating BLAST, ClustalW, primer3 and restriction digestion tools // Bioinformation. – 2012. – Vol. 8, No. 13. – P. 639-43.</mixed-citation><mixed-citation xml:lang="en">Vangala, R.K., Singh, L., Gupta, R.P. BioParishodhana: A novel graphical interface integrating BLAST, ClustalW, primer3 and restriction digestion tools // Bioinformation. – 2012. – Vol. 8, No. 13. – P. 639-43.</mixed-citation></citation-alternatives></ref><ref id="cit52"><label>52</label><citation-alternatives><mixed-citation xml:lang="ru">Zaal, D., Nota, B. ADOMA: A Command Line Tool to Modify ClustalW Multiple Alignment Output // Mol Inform. – 2016. – Vol. 35, No. 1. – P. 42-4.</mixed-citation><mixed-citation xml:lang="en">Zaal, D., Nota, B. ADOMA: A Command Line Tool to Modify ClustalW Multiple Alignment Output // Mol Inform. – 2016. – Vol. 35, No. 1. – P. 42-4.</mixed-citation></citation-alternatives></ref><ref id="cit53"><label>53</label><citation-alternatives><mixed-citation xml:lang="ru">Darling, A.E., Treangen, T.J., Messeguer, X., Perna, N.T. Analyzing patterns of microbial evolution using the mauve genome alignment system // Methods Mol Biol. – 2007. – Vol. 396. – P. 135-52.</mixed-citation><mixed-citation xml:lang="en">Darling, A.E., Treangen, T.J., Messeguer, X., Perna, N.T. Analyzing patterns of microbial evolution using the mauve genome alignment system // Methods Mol Biol. – 2007. – Vol. 396. – P. 135-52.</mixed-citation></citation-alternatives></ref><ref id="cit54"><label>54</label><citation-alternatives><mixed-citation xml:lang="ru">Darling, A.C., Mau, B., Blattner, F.R., Perna, N.T. Mauve: multiple alignment of conserved genomic sequence with rearrangements // Genome Res. – 2004. – Vol. 14, No. 7. – P. 1394-403.</mixed-citation><mixed-citation xml:lang="en">Darling, A.C., Mau, B., Blattner, F.R., Perna, N.T. Mauve: multiple alignment of conserved genomic sequence with rearrangements // Genome Res. – 2004. – Vol. 14, No. 7. – P. 1394-403.</mixed-citation></citation-alternatives></ref><ref id="cit55"><label>55</label><citation-alternatives><mixed-citation xml:lang="ru">Angiuoli, S.V., Salzberg, S.L. Mugsy: fast multiple alignment of closely related whole genomes // Bioinformatics. – 2010. – Vol. 27, No. 3. – P. 33-42.</mixed-citation><mixed-citation xml:lang="en">Angiuoli, S.V., Salzberg, S.L. Mugsy: fast multiple alignment of closely related whole genomes // Bioinformatics. – 2010. – Vol. 27, No. 3. – P. 33-42.</mixed-citation></citation-alternatives></ref><ref id="cit56"><label>56</label><citation-alternatives><mixed-citation xml:lang="ru">Cleemput, S., Dumon, W., Fonseca, V. et al. Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes // Bioinformatics. – Vol. 36, No. 11. – P. 3552-3555.</mixed-citation><mixed-citation xml:lang="en">Cleemput, S., Dumon, W., Fonseca, V. et al. Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes // Bioinformatics. – Vol. 36, No. 11. – P. 3552-3555.</mixed-citation></citation-alternatives></ref><ref id="cit57"><label>57</label><citation-alternatives><mixed-citation xml:lang="ru">Vilsker, M., Moosa, Y., Nooij, S. et al. Genome Detective: an automated system for virus identification from high-throughput sequencing data // Bioinformatics. – 2018. – Vol. 35, No. 5. – P. 871-873.</mixed-citation><mixed-citation xml:lang="en">Vilsker, M., Moosa, Y., Nooij, S. et al. Genome Detective: an automated system for virus identification from high-throughput sequencing data // Bioinformatics. – 2018. – Vol. 35, No. 5. – P. 871-873.</mixed-citation></citation-alternatives></ref><ref id="cit58"><label>58</label><citation-alternatives><mixed-citation xml:lang="ru">Gupta, S., Kapoor, P., Chaudhary, K. et al. Peptide toxicity prediction // Methods Mol Biol. – Vol. 1268. – P. 143-57.</mixed-citation><mixed-citation xml:lang="en">Gupta, S., Kapoor, P., Chaudhary, K. et al. Peptide toxicity prediction // Methods Mol Biol. – Vol. 1268. – P. 143-57.</mixed-citation></citation-alternatives></ref><ref id="cit59"><label>59</label><citation-alternatives><mixed-citation xml:lang="ru">Gupta, S., Kapoor, P., Chaudhary, K. et al. In silico approach for predicting toxicity of peptides and proteins // PLoS One. – 2013. – Vol. 8, No. 9. – P. e. 73957.</mixed-citation><mixed-citation xml:lang="en">Gupta, S., Kapoor, P., Chaudhary, K. et al. In silico approach for predicting toxicity of peptides and proteins // PLoS One. – 2013. – Vol. 8, No. 9. – P. e. 73957.</mixed-citation></citation-alternatives></ref><ref id="cit60"><label>60</label><citation-alternatives><mixed-citation xml:lang="ru">Krutz, N.L., Winget, J., Ryan, C.A. et al. Proteomic and Bioinformatic Analyses for the Identification of Proteins With Low Allergenic Potential for Hazard Assessment // Toxicol Sci. – – Vol. 170, No. 1. – P. 210-222.</mixed-citation><mixed-citation xml:lang="en">Krutz, N.L., Winget, J., Ryan, C.A. et al. Proteomic and Bioinformatic Analyses for the Identification of Proteins With Low Allergenic Potential for Hazard Assessment // Toxicol Sci. – – Vol. 170, No. 1. – P. 210-222.</mixed-citation></citation-alternatives></ref><ref id="cit61"><label>61</label><citation-alternatives><mixed-citation xml:lang="ru">Maurer– Stroh, S., Krutz, N.L., Kern, P.S. et al. AllerCatPro– prediction of protein allergenicity potential from the protein sequence // Bioinformatics. – 2019. – Vol. 35, No. 17. – P. 3020-3027.</mixed-citation><mixed-citation xml:lang="en">Maurer– Stroh, S., Krutz, N.L., Kern, P.S. et al. AllerCatPro– prediction of protein allergenicity potential from the protein sequence // Bioinformatics. – 2019. – Vol. 35, No. 17. – P. 3020-3027.</mixed-citation></citation-alternatives></ref><ref id="cit62"><label>62</label><citation-alternatives><mixed-citation xml:lang="ru">Sharma, N., Patiyal, S., Dhall, A. et al. AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes // Brief Bioinform. – 2020. – Vol. 1, № 1. – P. 1-7.</mixed-citation><mixed-citation xml:lang="en">Sharma, N., Patiyal, S., Dhall, A. et al. AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes // Brief Bioinform. – 2020. – Vol. 1, № 1. – P. 1-7.</mixed-citation></citation-alternatives></ref><ref id="cit63"><label>63</label><citation-alternatives><mixed-citation xml:lang="ru">Neeharika, D., Sunkar, S. Computational approach for the identification of putative allergens from Cucurbitaceae family members // J Food Sci Technol. – 2021. – Vol 58, No. 1. – P. 267-280.</mixed-citation><mixed-citation xml:lang="en">Neeharika, D., Sunkar, S. Computational approach for the identification of putative allergens from Cucurbitaceae family members // J Food Sci Technol. – 2021. – Vol 58, No. 1. – P. 267-280.</mixed-citation></citation-alternatives></ref><ref id="cit64"><label>64</label><citation-alternatives><mixed-citation xml:lang="ru">Sircar, G., Saha, B., Bhattacharya, S.G., Saha, S. In silico prediction of allergenic proteins // Methods Mol Biol. – 2014. Vol. 1184. – P. 375-88.</mixed-citation><mixed-citation xml:lang="en">Sircar, G., Saha, B., Bhattacharya, S.G., Saha, S. In silico prediction of allergenic proteins // Methods Mol Biol. – 2014. Vol. 1184. – P. 375-88.</mixed-citation></citation-alternatives></ref><ref id="cit65"><label>65</label><citation-alternatives><mixed-citation xml:lang="ru">Saha, S., Raghava, G.P. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes // Nucleic Acids Res. 2006. – Vol. 34, No. Web Server issue. – P. W. 202-9.</mixed-citation><mixed-citation xml:lang="en">Saha, S., Raghava, G.P. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes // Nucleic Acids Res. 2006. – Vol. 34, No. Web Server issue. – P. W. 202-9.</mixed-citation></citation-alternatives></ref><ref id="cit66"><label>66</label><citation-alternatives><mixed-citation xml:lang="ru">Pagadala, N.S., Syed, K., Tuszynski, J. Software for molecular docking: a review // Biophys Rev. – 2017. – Vol. 9, No. 2. – P. 91-102.</mixed-citation><mixed-citation xml:lang="en">Pagadala, N.S., Syed, K., Tuszynski, J. Software for molecular docking: a review // Biophys Rev. – 2017. – Vol. 9, No. 2. – P. 91-102.</mixed-citation></citation-alternatives></ref><ref id="cit67"><label>67</label><citation-alternatives><mixed-citation xml:lang="ru">Grote, A., Hiller, K., Scheer, M. et al. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host // Nucleic Acids Res. – 2005. – Vol. 33, No. Web Server issue. – P. W526-31.</mixed-citation><mixed-citation xml:lang="en">Grote, A., Hiller, K., Scheer, M. et al. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host // Nucleic Acids Res. – 2005. – Vol. 33, No. Web Server issue. – P. W526-31.</mixed-citation></citation-alternatives></ref><ref id="cit68"><label>68</label><citation-alternatives><mixed-citation xml:lang="ru">Zheng, W., Zhang, C., Bell, E.W., Zhang, Y. I – TASSER gateway: A protein structure and function prediction server powered by XSEDE // Future Gener Comput Syst. – 2019. – Vol. 99, – P. 73-85.</mixed-citation><mixed-citation xml:lang="en">Zheng, W., Zhang, C., Bell, E.W., Zhang, Y. I – TASSER gateway: A protein structure and function prediction server powered by XSEDE // Future Gener Comput Syst. – 2019. – Vol. 99, – P. 73-85.</mixed-citation></citation-alternatives></ref><ref id="cit69"><label>69</label><citation-alternatives><mixed-citation xml:lang="ru">Roy, A., Kucukural, A., Zhang, Y. I – TASSER: a unified platform for automated protein structure and function prediction // Nat Protoc. – 2010. – Vol. 5, No. 4. – P. 725-38.</mixed-citation><mixed-citation xml:lang="en">Roy, A., Kucukural, A., Zhang, Y. I – TASSER: a unified platform for automated protein structure and function prediction // Nat Protoc. – 2010. – Vol. 5, No. 4. – P. 725-38.</mixed-citation></citation-alternatives></ref><ref id="cit70"><label>70</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang, Y. I– TASSER server for protein 3D structure prediction // BMC Bioinformatics. – 2008. – Vol. 9. – P. 40.</mixed-citation><mixed-citation xml:lang="en">Zhang, Y. I– TASSER server for protein 3D structure prediction // BMC Bioinformatics. – 2008. – Vol. 9. – P. 40.</mixed-citation></citation-alternatives></ref><ref id="cit71"><label>71</label><citation-alternatives><mixed-citation xml:lang="ru">Raborn, R.T., Brendel, V.P. Using RAMPAGE to Identify and Annotate Promoters in Insect Genomes // Methods Mol Biol. – 2019. – Vol. 1858, No. 1. – P. 99-116.</mixed-citation><mixed-citation xml:lang="en">Raborn, R.T., Brendel, V.P. Using RAMPAGE to Identify and Annotate Promoters in Insect Genomes // Methods Mol Biol. – 2019. – Vol. 1858, No. 1. – P. 99-116.</mixed-citation></citation-alternatives></ref><ref id="cit72"><label>72</label><citation-alternatives><mixed-citation xml:lang="ru">Collatz, M., Mock, F., Hölzer, M. et al. EpiDope: A Deep neural network for linear B–cell epitope prediction // bioRxiv. 2020. – No. 1. – P. 1-8.</mixed-citation><mixed-citation xml:lang="en">Collatz, M., Mock, F., Hölzer, M. et al. EpiDope: A Deep neural network for linear B–cell epitope prediction // bioRxiv. 2020. – No. 1. – P. 1-8.</mixed-citation></citation-alternatives></ref><ref id="cit73"><label>73</label><citation-alternatives><mixed-citation xml:lang="ru">Suprun, M., Ellis, R.J., Sampson, H.A., Suárez– Fariñas, M. bbeaR: an R package and framework for epitope – specific antibody profiling // Bioinformatics. – 2021. – Vol. 37, No. 1. – P. 131-133.</mixed-citation><mixed-citation xml:lang="en">Suprun, M., Ellis, R.J., Sampson, H.A., Suárez– Fariñas, M. bbeaR: an R package and framework for epitope – specific antibody profiling // Bioinformatics. – 2021. – Vol. 37, No. 1. – P. 131-133.</mixed-citation></citation-alternatives></ref><ref id="cit74"><label>74</label><citation-alternatives><mixed-citation xml:lang="ru">Ogishi, M., Yotsuyanagi, H. Quantitative prediction of the landscape of T cell epitope immunogenicity in sequence space // Frontiers in Immunology. – 2019. – Vol .10. – P. 827.</mixed-citation><mixed-citation xml:lang="en">Ogishi, M., Yotsuyanagi, H. Quantitative prediction of the landscape of T cell epitope immunogenicity in sequence space // Frontiers in Immunology. – 2019. – Vol .10. – P. 827.</mixed-citation></citation-alternatives></ref><ref id="cit75"><label>75</label><citation-alternatives><mixed-citation xml:lang="ru">Pittard, W.S., Li, S. The Essential Toolbox of Data Science: Python, R, Git, and Docker // Methods Mol Biol. – 2020. – Vol. 2104, No. 1. – P. 265-311.</mixed-citation><mixed-citation xml:lang="en">Pittard, W.S., Li, S. The Essential Toolbox of Data Science: Python, R, Git, and Docker // Methods Mol Biol. – 2020. – Vol. 2104, No. 1. – P. 265-311.</mixed-citation></citation-alternatives></ref><ref id="cit76"><label>76</label><citation-alternatives><mixed-citation xml:lang="ru">Kwon, C., Kim, J., Ahn, J. DockerBIO: web application for efficient use of bioinformatics Docker images // PeerJ. – 2018. – Vol. 6, No. 1. – P. e. 5954.</mixed-citation><mixed-citation xml:lang="en">Kwon, C., Kim, J., Ahn, J. DockerBIO: web application for efficient use of bioinformatics Docker images // PeerJ. – 2018. – Vol. 6, No. 1. – P. e. 5954.</mixed-citation></citation-alternatives></ref><ref id="cit77"><label>77</label><citation-alternatives><mixed-citation xml:lang="ru">Garofoli, A., Paradiso, V., Montazeri, H. et al. PipeIT: A Singularity Container for Molecular Diagnostic Somatic Variant Calling on the Ion Torrent Next– Generation Sequencing Platform // J. Mol Diagn. – 2019. – Vol. 21, No. 5. – P. 884-894.</mixed-citation><mixed-citation xml:lang="en">Garofoli, A., Paradiso, V., Montazeri, H. et al. PipeIT: A Singularity Container for Molecular Diagnostic Somatic Variant Calling on the Ion Torrent Next– Generation Sequencing Platform // J. Mol Diagn. – 2019. – Vol. 21, No. 5. – P. 884-894.</mixed-citation></citation-alternatives></ref><ref id="cit78"><label>78</label><citation-alternatives><mixed-citation xml:lang="ru">Samdani, A., Vetrivel, U. POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening // Comput Biol Chem. – 2018. – Vol. 74, No. 1. – P. 39-48.</mixed-citation><mixed-citation xml:lang="en">Samdani, A., Vetrivel, U. POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening // Comput Biol Chem. – 2018. – Vol. 74, No. 1. – P. 39-48.</mixed-citation></citation-alternatives></ref><ref id="cit79"><label>79</label><citation-alternatives><mixed-citation xml:lang="ru">Красильников, А.П. Микробиологический словарь-справочник. – 2– е изд., доп. и перераб. – Мн.: ООО "Асар", 1999. – 397 c.</mixed-citation><mixed-citation xml:lang="en">Красильников, А.П. Микробиологический словарь-справочник. – 2– е изд., доп. и перераб. – Мн.: ООО "Асар", 1999. – 397 c.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
