chebЧебышевский сборникChebyshevskii Sbornik2226-8383Tula State Lev Tolstoy Pedagogical University10.22405/2226-8383-2019-20-2-93-107cheb-597Research ArticleСтатьиArticleНовый подход к поиску строковой медианы и визуализация строковых кластеровNew approach to searching for string median and visualization of string clustersГорбачевДмитрий ВикторовичGorbachevDmitry Viktorovichdvgmail@mail.ruОфицеровЕвгений ПетровичOfitserovEvgenii Petrovicheofitserov@gmail.com20192001202020293107Copyright © Горбачев Д.В., Офицеров Е.П., 20192019Горбачев Д.В., Офицеров Е.П.Gorbachev D.V., Ofitserov E.P.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.chebsbornik.ru/jour/article/view/597
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ReferencesГасфилд Д. Строки, деревья и последовательности в алгоритмах: Информатика и вычислительная биология. СПб.: Невский Диалект, БХВ-Петербург, 2003.Gusfield D. Algorithms on strings, trees, and sequences: Computer science and computational biology. New York: Cambridge University Press, 1997.Офицеров Е.П. Статистическая модель периферической селекции Т-клеточных рецепторов // Известия ТулГУ. Технические науки. 2017. Вып. 2. С. 138–143.Ofitserov E.P. Statistical model of T-cell receptor pereferic selection // Izvestiya of Tula State University. Technical sciences. 2017. No. 2. P. 138–143.Офицеров Е.П. Глубокая модель селекции Т-клеточных рецепторов // Известия ТулГУ. Технические науки. 2017. Вып. 12. Ч. 2. С. 350–355.Ofitserov E.P. Deep model of T-cell receptor selection // Izvestiya of Tula State University. Technical sciences. 2017. No. 12, part 2. P. 350–355.Офицеров Е.П. Классификация последовательностей на основе коротких мотивов. Чебышевский сборник. 2018. Том 19, №:1. С. 187–199. doi: 10.22405/2226-8383-2018-19-1-187-199Ofitserov E.P. Motif based sequence classification // Chebyshevskii Sbornik. 2018. Vol. 19, no. 1. P. 187–199. (In Russ.) https://doi.org/10.22405/2226-8383-2018-19-1-187-199Офицеров Е.П. Программный комплекс для решения задач машинного обучения на строковых данных при помощи дифференцируемого редакционного расстояния // Известия ТулГУ. Технические науки. 2019. Вып. 5. С. 370–376.Ofitserov E.P. Software package for solving machine learning problems on string data using soft edit distance // Izvestiya of Tula State University. Technical sciences. 2019. No. 5. P. 370–376.Ту Дж., Гонсалес Р. Принципы распознавания образов. М.: Мир, 1978.Tou J.T., Gonzalez R.C. Pattern recognition principles. Addison-Wesley Publishing Company, 1974.Boyd S., Vandenberghe L. Convex Optimization. Cambridge University Press, 2004.Boyd S., Vandenberghe L. Convex Optimization. Cambridge University Press, 2004.Casacuberta F., de Antonio M. A greedy algorithm for computing approximate median strings // In: VII Simposium Nacional de Reconocimiento de Formas y An’alisis de Im’agenes. 1997. P. 193–198.Casacuberta F., de Antonio M. A greedy algorithm for computing approximate median strings // In: VII Simposium Nacional de Reconocimiento de Formas y An’alisis de Im’agenes. 1997. P. 193–198.De la Higuera C., Casacuberta F. Topology of strings: Median string is NP-complete // Theoretical Computer Science. 2000. Vol. 230, no. 1–2. P. 39–48. doi: 10.1016/s0304-3975(97)00240-5De la Higuera C., Casacuberta F. Topology of strings: Median string is NP-complete // Theoretical Computer Science. 2000. Vol. 230, no. 1–2. P. 39–48. doi: 10.1016/s0304-3975(97)00240-5Hayashida M., Koyano H. Finding median and center strings for a probability distribution on a set of strings under Levenshtein distance based on integer linear programming // In: Fred A., Gamboa H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2016. Communications in Computer and Information Science. Springer, Cham. 2017. Vol 690. P. 108–121.Hayashida M., Koyano H. Finding median and center strings for a probability distribution on a set of strings under Levenshtein distance based on integer linear programming // In: Fred A., Gamboa H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2016. Communications in Computer and Information Science. Springer, Cham. 2017. Vol 690. P. 108–121.Kruzslicz F. Improved greedy algorithm for computing approximate median strings // Acta Cybernetica. 1999. Vol. 14, no. 2. P. 331–339.Kruzslicz F. Improved greedy algorithm for computing approximate median strings // Acta Cybernetica. 1999. Vol. 14, no. 2. P. 331–339.MartÍnez-Hinarejos C.D., Juan A., Casacuberta F. Use of median string for classification // Proc. 15th Int. Conf. on Pattern Recognition. ICPR-2000, Barcelona, Spain. 2000. Vol. 2. P. 903–906. doi: 10.1109/ICPR.2000.906220MartÍnez-Hinarejos C.D., Juan A., Casacuberta F. Use of median string for classification // Proc. 15th Int. Conf. on Pattern Recognition. ICPR-2000, Barcelona, Spain. 2000. Vol. 2. P. 903–906. doi: 10.1109/ICPR.2000.906220Van der Maaten L., Hinton G. Visualizing data using t-SNE // J. Mach. Learn. Res. 2008. Vol. 9. P. 2579–2605.Van der Maaten L., Hinton G. Visualizing data using t-SNE // J. Mach. Learn. Res. 2008. Vol. 9. P. 2579–2605.Ofitserov E., Tsvetkov V., Nazarov V. Soft edit distance for differentiable comparison of symbolic sequences // arXiv:1904.12562. 2019.Ofitserov E., Tsvetkov V., Nazarov V. Soft edit distance for differentiable comparison of symbolic sequences // arXiv:1904.12562. 2019.Olivares-Rodr’ıguez C., Oncina J. A stochastic approach to median string computation // In: da Vitoria Lobo N. et al. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science. Springer, Berlin, Heidelberg. 2008. Vol. 5342. P. 431–440.Olivares-Rodr’ıguez C., Oncina J. A stochastic approach to median string computation // In: da Vitoria Lobo N. et al. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science. Springer, Berlin, Heidelberg. 2008. Vol. 5342. P. 431–440.Ruder S. An overview of gradient descent optimization algorithms // arXiv:1609.04747. 2016.Ruder S. An overview of gradient descent optimization algorithms // arXiv:1609.04747. 2016.Sammon J.W. A nonlinear mapping for data structure analysis // IEEE Transactions on Computers, 18(5):401–409, 1969.Sammon J.W. A nonlinear mapping for data structure analysis // IEEE Transactions on Computers, 18(5):401–409, 1969.Torgerson W.S. Multidimensional scaling I: Theory and method // Psychometrika. 1952. Vol. 17. P. 401–419.Torgerson W.S. Multidimensional scaling I: Theory and method // Psychometrika. 1952. Vol. 17. P. 401–419.Wang L., Jiang T. On the complexity of multiple sequence alignment // J. Computat. Biol. 1994. Vol. 1, no. 4. P. 337–348.Wang L., Jiang T. On the complexity of multiple sequence alignment // J. Computat. Biol. 1994. Vol. 1, no. 4. P. 337–348.
The authors declare that there are no conflicts of interest present.