Modelo oculto de Markov la piedra angular de la proteómica moderna

Autores:
Castellanos, Isabel Cristina
Tipo de recurso:
Article of journal
Fecha de publicación:
2024
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
OAI Identifier:
oai:repositorio.uptc.edu.co:001/18728
Acceso en línea:
https://repositorio.uptc.edu.co/handle/001/18728
https://doi.org/10.19053/01217488.v15.n2.2024.15663
Palabra clave:
Modelo oculto de Markov (HMM), bioinformática, dominios, proteínas.
Hidden Markov Model (HMM), bioinformatics, domain, proteins
Rights
openAccess
License
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
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dc.title.es-ES.fl_str_mv Modelo oculto de Markov la piedra angular de la proteómica moderna
title Modelo oculto de Markov la piedra angular de la proteómica moderna
spellingShingle Modelo oculto de Markov la piedra angular de la proteómica moderna
Modelo oculto de Markov (HMM), bioinformática, dominios, proteínas.
Hidden Markov Model (HMM), bioinformatics, domain, proteins
title_short Modelo oculto de Markov la piedra angular de la proteómica moderna
title_full Modelo oculto de Markov la piedra angular de la proteómica moderna
title_fullStr Modelo oculto de Markov la piedra angular de la proteómica moderna
title_full_unstemmed Modelo oculto de Markov la piedra angular de la proteómica moderna
title_sort Modelo oculto de Markov la piedra angular de la proteómica moderna
dc.creator.fl_str_mv Castellanos, Isabel Cristina
dc.contributor.author.spa.fl_str_mv Castellanos, Isabel Cristina
dc.subject.none.fl_str_mv Modelo oculto de Markov (HMM), bioinformática, dominios, proteínas.
Hidden Markov Model (HMM), bioinformatics, domain, proteins
topic Modelo oculto de Markov (HMM), bioinformática, dominios, proteínas.
Hidden Markov Model (HMM), bioinformatics, domain, proteins
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-12-11 00:00:00
2026-04-16T17:12:26Z
dc.date.available.none.fl_str_mv 2024-12-11 00:00:00
dc.date.issued.none.fl_str_mv 2024-12-11
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.doi.none.fl_str_mv 10.19053/01217488.v15.n2.2024.15663
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https://doi.org/10.19053/01217488.v15.n2.2024.15663
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dc.relation.references.none.fl_str_mv B. Aslam, M. Basit, M. A. Nisar, M. Khurshid, and M. H. Rasool, “Proteomics: Technologies and their applications,” Journal of Chromatographic Science, vol. 55, no. 2. 2017. doi: 10.1093/chromsci/bmw167. [2] D. R. Bentley, “The human genome project - An overview,” Medicinal Research Reviews, vol. 20, no. 3. 2000. doi: 10.1002/(sici)1098-1128(200005)20:3<189::aid-med2>3.0.co;2-%23. [3] S. P. Melo et al., “Transcription of meiotic-like-pathway genes in Giardia intestinalis,” Mem Inst Oswaldo Cruz, vol. 103, no. 4, 2008, doi: 10.1590/S0074-02762008000400006. [4] I. C. Castellanos, E. P. Calvo, and M. Wasserman, “A new gene inventory of the ubiquitin and ubiquitin-like conjugation pathways in giardia intestinalis,” Mem Inst Oswaldo Cruz, vol. 115, 2020, doi: 10.1590/0074-02760190242. [5] D. I. Resnicow, J. C. Deacon, H. M. Warrick, J. A. Spudich, and L. A. Leinwand, “Functional diversity among a family of human skeletal muscle myosin motors,” Proc Natl Acad Sci U S A, vol. 107, no. 3, 2010, doi: 10.1073/pnas.0913527107. [6] P. C. Hernández, L. Morales, I. C. Castellanos, M. Wasserman, and J. Chaparro-Olaya, “Myosin B of Plasmodium falciparum (PfMyoB): in silico prediction of its three-dimensional structure and its possible interaction with MTIP,” Parasitol Res, vol. 116, no. 4, 2017, doi: 10.1007/s00436-017-5417-y. [7] S. Yoodee and V. Thongboonkerd, “Bioinformatics and computational analyses of kidney stone modulatory proteins lead to solid experimental evidence and therapeutic potential,” Biomedicine \& Pharmacotherapy, vol. 159, p. 114217, 2023. [8] T. F. Smith and M. S. Waterman, “Identification of common molecular subsequences,” J Mol Biol, vol. 147, no. 1, pp. 195–197, 1981. [9] G. Myers, “What’s Behind Blast,” 2013. doi: 10.1007/978-1-4471-5298-9_1. [10] S. F. Altschul, W. Gish, W. Miller, E. W. Myers, and D. J. Lipman, “Basic local alignment search tool,” J Mol Biol, vol. 215, no. 3, 1990, doi: 10.1016/S0022-2836(05)80360-2. [11] R. Giegerich, “A systematic approach to dynamic programming in bioinformatics,” Bioinformatics, vol. 16, no. 8. 2000. doi: 10.1093/bioinformatics/16.8.665. [12] ncbi, “Entries for the BLOSUM62 matrix at a scale of ln(2)/2.0,” ftp://ftp.ncbi.nlm.nih.gov/blast/matrices, Feb. 22, 2023. [13] M. P. Styczynski, K. L. Jensen, I. Rigoutsos, and G. Stephanopoulos, “BLOSUM62 miscalculations improve search performance,” Nature Biotechnology, vol. 26, no. 3. 2008. doi: 10.1038/nbt0308-274. [14] S. Henikoff and J. G. Henikoff, “Amino acid substitution matrices from protein blocks,” Proc Natl Acad Sci U S A, vol. 89, no. 22, 1992, doi: 10.1073/pnas.89.22.10915. [15] S. F. Altschul et al., “Gapped BLAST and PSI-BLAST: A new generation of protein database search programs,” Nucleic Acids Research, vol. 25, no. 17. 1997. doi: 10.1093/nar/25.17.3389. [16] A. A. Markov, “Rasprostranenie zakona bol’shih chisel na velichiny, zavisyaschie drug ot druga,” Izvestiya Fiziko-matematicheskogo obschestva pri Kazanskom universitete, vol. 2-ya seriy, 1906. [17] L. R. Rabiner, “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,” Proceedings of the IEEE, vol. 77, no. 2, 1989, doi: 10.1109/5.18626. [18] A. Krogh, M. Brown, I. S. Mian, K. Sjölander, and D. Haussler, “Hidden Markov Models in computational biology applications to protein modeling,” J Mol Biol, vol. 235, no. 5, 1994, doi: 10.1006/jmbi.1994.1104. [19] M. Gribskov, R. Lothy, and D. Eisenberg, “Profile analysis,” Methods Enzymol, vol. 183, no. C, 1990, doi: 10.1016/0076-6879(90)83011-W. [20] G. D. Forney, “The Viterbi Algorithm,” Proceedings of the IEEE, vol. 61, no. 3, 1973, doi: 10.1109/PROC.1973.9030. [21] R. D. Finn et al., “Pfam: clans, web tools and services.,” Nucleic Acids Res, vol. 34, no. Database issue, 2006, doi: 10.1093/nar/gkj149. [22] S. El-Gebali et al., “The Pfam protein families database in 2019,” Nucleic Acids Res, vol. 47, no. D1, 2019, doi: 10.1093/nar/gky995. [23] J. Mistry et al., “Pfam: The protein families database in 2021,” Nucleic Acids Res, vol. 49, no. D1, 2021, doi: 10.1093/nar/gkaa913. [24] S. R. Eddy, “What is a hidden Markov model?,” Nature Biotechnology, vol. 22, no. 10. 2004. doi: 10.1038/nbt1004-1315. [25] S. C. Potter, A. Luciani, S. R. Eddy, Y. Park, R. Lopez, and R. D. Finn, “HMMER web server: 2018 update,” Nucleic Acids Res, vol. 46, no. W1, 2018, doi: 10.1093/nar/gky448. [26] K. Karplus, C. Barrett, and R. Hughey, “Hidden Markov models for detecting remote protein homologies,” Bioinformatics, vol. 14, no. 10, 1998, doi: 10.1093/bioinformatics/14.10.846.
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spelling Castellanos, Isabel Cristina2024-12-11 00:00:002026-04-16T17:12:26Z2024-12-11 00:00:002024-12-110121-7488https://repositorio.uptc.edu.co/handle/001/1872810.19053/01217488.v15.n2.2024.156632462-7658https://doi.org/10.19053/01217488.v15.n2.2024.15663application/pdfUniversidad Pedagógica y Tecnológica de Colombiahttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.esinfo:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/15663Modelo oculto de Markov (HMM), bioinformática, dominios, proteínas.Hidden Markov Model (HMM), bioinformatics, domain, proteinsModelo oculto de Markov la piedra angular de la proteómica modernaArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85B. Aslam, M. Basit, M. A. Nisar, M. Khurshid, and M. H. Rasool, “Proteomics: Technologies and their applications,” Journal of Chromatographic Science, vol. 55, no. 2. 2017. doi: 10.1093/chromsci/bmw167. [2] D. R. Bentley, “The human genome project - An overview,” Medicinal Research Reviews, vol. 20, no. 3. 2000. doi: 10.1002/(sici)1098-1128(200005)20:3<189::aid-med2>3.0.co;2-%23. [3] S. P. Melo et al., “Transcription of meiotic-like-pathway genes in Giardia intestinalis,” Mem Inst Oswaldo Cruz, vol. 103, no. 4, 2008, doi: 10.1590/S0074-02762008000400006. [4] I. C. Castellanos, E. P. Calvo, and M. Wasserman, “A new gene inventory of the ubiquitin and ubiquitin-like conjugation pathways in giardia intestinalis,” Mem Inst Oswaldo Cruz, vol. 115, 2020, doi: 10.1590/0074-02760190242. [5] D. I. Resnicow, J. C. Deacon, H. M. Warrick, J. A. Spudich, and L. A. Leinwand, “Functional diversity among a family of human skeletal muscle myosin motors,” Proc Natl Acad Sci U S A, vol. 107, no. 3, 2010, doi: 10.1073/pnas.0913527107. [6] P. C. Hernández, L. Morales, I. C. Castellanos, M. Wasserman, and J. Chaparro-Olaya, “Myosin B of Plasmodium falciparum (PfMyoB): in silico prediction of its three-dimensional structure and its possible interaction with MTIP,” Parasitol Res, vol. 116, no. 4, 2017, doi: 10.1007/s00436-017-5417-y. [7] S. Yoodee and V. Thongboonkerd, “Bioinformatics and computational analyses of kidney stone modulatory proteins lead to solid experimental evidence and therapeutic potential,” Biomedicine \& Pharmacotherapy, vol. 159, p. 114217, 2023. [8] T. F. Smith and M. S. Waterman, “Identification of common molecular subsequences,” J Mol Biol, vol. 147, no. 1, pp. 195–197, 1981. [9] G. Myers, “What’s Behind Blast,” 2013. doi: 10.1007/978-1-4471-5298-9_1. [10] S. F. Altschul, W. Gish, W. Miller, E. W. Myers, and D. J. Lipman, “Basic local alignment search tool,” J Mol Biol, vol. 215, no. 3, 1990, doi: 10.1016/S0022-2836(05)80360-2. [11] R. Giegerich, “A systematic approach to dynamic programming in bioinformatics,” Bioinformatics, vol. 16, no. 8. 2000. doi: 10.1093/bioinformatics/16.8.665. [12] ncbi, “Entries for the BLOSUM62 matrix at a scale of ln(2)/2.0,” ftp://ftp.ncbi.nlm.nih.gov/blast/matrices, Feb. 22, 2023. [13] M. P. Styczynski, K. L. Jensen, I. Rigoutsos, and G. Stephanopoulos, “BLOSUM62 miscalculations improve search performance,” Nature Biotechnology, vol. 26, no. 3. 2008. doi: 10.1038/nbt0308-274. [14] S. Henikoff and J. G. Henikoff, “Amino acid substitution matrices from protein blocks,” Proc Natl Acad Sci U S A, vol. 89, no. 22, 1992, doi: 10.1073/pnas.89.22.10915. [15] S. F. Altschul et al., “Gapped BLAST and PSI-BLAST: A new generation of protein database search programs,” Nucleic Acids Research, vol. 25, no. 17. 1997. doi: 10.1093/nar/25.17.3389. [16] A. A. Markov, “Rasprostranenie zakona bol’shih chisel na velichiny, zavisyaschie drug ot druga,” Izvestiya Fiziko-matematicheskogo obschestva pri Kazanskom universitete, vol. 2-ya seriy, 1906. [17] L. R. Rabiner, “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,” Proceedings of the IEEE, vol. 77, no. 2, 1989, doi: 10.1109/5.18626. [18] A. Krogh, M. Brown, I. S. Mian, K. Sjölander, and D. Haussler, “Hidden Markov Models in computational biology applications to protein modeling,” J Mol Biol, vol. 235, no. 5, 1994, doi: 10.1006/jmbi.1994.1104. [19] M. Gribskov, R. Lothy, and D. Eisenberg, “Profile analysis,” Methods Enzymol, vol. 183, no. C, 1990, doi: 10.1016/0076-6879(90)83011-W. [20] G. D. Forney, “The Viterbi Algorithm,” Proceedings of the IEEE, vol. 61, no. 3, 1973, doi: 10.1109/PROC.1973.9030. [21] R. D. Finn et al., “Pfam: clans, web tools and services.,” Nucleic Acids Res, vol. 34, no. Database issue, 2006, doi: 10.1093/nar/gkj149. [22] S. El-Gebali et al., “The Pfam protein families database in 2019,” Nucleic Acids Res, vol. 47, no. D1, 2019, doi: 10.1093/nar/gky995. [23] J. Mistry et al., “Pfam: The protein families database in 2021,” Nucleic Acids Res, vol. 49, no. D1, 2021, doi: 10.1093/nar/gkaa913. [24] S. R. Eddy, “What is a hidden Markov model?,” Nature Biotechnology, vol. 22, no. 10. 2004. doi: 10.1038/nbt1004-1315. [25] S. C. Potter, A. Luciani, S. R. Eddy, Y. Park, R. Lopez, and R. D. Finn, “HMMER web server: 2018 update,” Nucleic Acids Res, vol. 46, no. W1, 2018, doi: 10.1093/nar/gky448. [26] K. Karplus, C. Barrett, and R. Hughey, “Hidden Markov models for detecting remote protein homologies,” Bioinformatics, vol. 14, no. 10, 1998, doi: 10.1093/bioinformatics/14.10.846.217221215Ciencia en Desarrollohttps://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/download/15663/14990Núm. 2 , Año 2024 : Vol. 15 Núm. 2 (2024): Vol 15, Núm.2 (2024): Julio-DiciembrePublicationOREORE.xmltext/xml2569https://repositorio.uptc.edu.co/bitstreams/f768514b-6441-48fd-ab1c-7669be60b203/downloadfacf87f616d3c82c69db6ba9ff085221MD51falseAnonymousREAD001/18728oai:repositorio.uptc.edu.co:001/187282026-10-30 07:02:45.339https://creativecommons.org/licenses/by-nc-nd/4.0/deed.esmetadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com