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  • Source: Heliyon. Unidades: FCF, IME, Interunidades em Bioinformática, EESC

    Subjects: GENÉTICA, GENÉTICA, BIOINFORMÁTICA

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      CANO, Lyang Higa et al. Gene network analysis of Plasmodium falciparum ubiquitin-proteasomal system pathways reveals co-expression of the E1, E2 and E3 enzymes during intraerythrocytic cycle. Heliyon, v. 11, n. artigo e44019, p. 1-12, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.heliyon.2025.e44019. Acesso em: 28 nov. 2025.
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      Cano, L. H., Ahmed, W., Lima, W. R., Martins, D. C., Parreira, K. S., Garcia, C. R. da S., & Hashimoto, R. F. (2025). Gene network analysis of Plasmodium falciparum ubiquitin-proteasomal system pathways reveals co-expression of the E1, E2 and E3 enzymes during intraerythrocytic cycle. Heliyon, 11( artigo e44019), 1-12. doi:10.1016/j.heliyon.2025.e44019
    • NLM

      Cano LH, Ahmed W, Lima WR, Martins DC, Parreira KS, Garcia CR da S, Hashimoto RF. Gene network analysis of Plasmodium falciparum ubiquitin-proteasomal system pathways reveals co-expression of the E1, E2 and E3 enzymes during intraerythrocytic cycle [Internet]. Heliyon. 2025 ; 11( artigo e44019): 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.heliyon.2025.e44019
    • Vancouver

      Cano LH, Ahmed W, Lima WR, Martins DC, Parreira KS, Garcia CR da S, Hashimoto RF. Gene network analysis of Plasmodium falciparum ubiquitin-proteasomal system pathways reveals co-expression of the E1, E2 and E3 enzymes during intraerythrocytic cycle [Internet]. Heliyon. 2025 ; 11( artigo e44019): 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.heliyon.2025.e44019
  • Source: Pattern Recognition Letters. Unidade: IME

    Assunto: SENSORIAMENTO REMOTO

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      ALVES, Wonder Alexandre Luz et al. Multichannel image classification based on adaptive attribute profiles. Pattern Recognition Letters, v. 187, p. 107-114, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2024.11.015. Acesso em: 28 nov. 2025.
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      Alves, W. A. L., Campos, W. S., Gobber, C. F., Silva, D. J., & Hashimoto, R. F. (2025). Multichannel image classification based on adaptive attribute profiles. Pattern Recognition Letters, 187, 107-114. doi:10.1016/j.patrec.2024.11.015
    • NLM

      Alves WAL, Campos WS, Gobber CF, Silva DJ, Hashimoto RF. Multichannel image classification based on adaptive attribute profiles [Internet]. Pattern Recognition Letters. 2025 ; 187 107-114.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.patrec.2024.11.015
    • Vancouver

      Alves WAL, Campos WS, Gobber CF, Silva DJ, Hashimoto RF. Multichannel image classification based on adaptive attribute profiles [Internet]. Pattern Recognition Letters. 2025 ; 187 107-114.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.patrec.2024.11.015
  • Source: International Journal of Molecular Sciences. Unidade: IME

    Subjects: MEDICAMENTO, RNA, GEOMETRIA E MODELAGEM COMPUTACIONAL, NEOPLASIAS, BIOINFORMÁTICA

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      GUPTA, Shantanu et al. LncRNA PTENP1/miR-21/PTEN axis modulates EMT and drug resistance in cancer: dynamic Boolean modeling for cell Fates in DNA damage response. International Journal of Molecular Sciences, v. 25, n. artigo 8264, p. 1-17, 2024Tradução . . Disponível em: https://doi.org/10.3390/ijms25158264. Acesso em: 28 nov. 2025.
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      Gupta, S., Silveira, D. A., Lorenzoni, P. R., Mombach, J. C. M., & Hashimoto, R. F. (2024). LncRNA PTENP1/miR-21/PTEN axis modulates EMT and drug resistance in cancer: dynamic Boolean modeling for cell Fates in DNA damage response. International Journal of Molecular Sciences, 25( artigo 8264), 1-17. doi:10.3390/ijms25158264
    • NLM

      Gupta S, Silveira DA, Lorenzoni PR, Mombach JCM, Hashimoto RF. LncRNA PTENP1/miR-21/PTEN axis modulates EMT and drug resistance in cancer: dynamic Boolean modeling for cell Fates in DNA damage response [Internet]. International Journal of Molecular Sciences. 2024 ; 25( artigo 8264): 1-17.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/ijms25158264
    • Vancouver

      Gupta S, Silveira DA, Lorenzoni PR, Mombach JCM, Hashimoto RF. LncRNA PTENP1/miR-21/PTEN axis modulates EMT and drug resistance in cancer: dynamic Boolean modeling for cell Fates in DNA damage response [Internet]. International Journal of Molecular Sciences. 2024 ; 25( artigo 8264): 1-17.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/ijms25158264
  • Source: Ambient intelligence in health care : proceedings. Conference titles: International Conference on Ambient Intelligence in Health Care - ICAIHC. Unidade: IME

    Subjects: REDES COMPLEXAS, ENTROPIA, COVID-19, ANÁLISE SEQUENCIAL, BIOINFORMÁTICA, RECONHECIMENTO DE PADRÕES

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      PIMENTA-ZANON, Matheus H. et al. Biological sequence analysis using complex networks and entropy maximization: a case study in SARS-CoV-2. 2023, Anais.. Heidelberg: Springer, 2023. Disponível em: https://doi.org/10.1007/978-981-19-6068-0_44. Acesso em: 28 nov. 2025.
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      Pimenta-Zanon, M. H., de Souza, V. A., Hashimoto, R. F., & Lopes, F. M. (2023). Biological sequence analysis using complex networks and entropy maximization: a case study in SARS-CoV-2. In Ambient intelligence in health care : proceedings. Heidelberg: Springer. doi:10.1007/978-981-19-6068-0_44
    • NLM

      Pimenta-Zanon MH, de Souza VA, Hashimoto RF, Lopes FM. Biological sequence analysis using complex networks and entropy maximization: a case study in SARS-CoV-2 [Internet]. Ambient intelligence in health care : proceedings. 2023 ;[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-981-19-6068-0_44
    • Vancouver

      Pimenta-Zanon MH, de Souza VA, Hashimoto RF, Lopes FM. Biological sequence analysis using complex networks and entropy maximization: a case study in SARS-CoV-2 [Internet]. Ambient intelligence in health care : proceedings. 2023 ;[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-981-19-6068-0_44
  • Conference titles: Brazilian Symposium on Bioinformatics - BSB. Unidades: IME, IQ, Interunidades em Bioinformática

    Subjects: PROBLEMAS INVERSOS, REDES NEURAIS, APRENDIZADO COMPUTACIONAL

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      SOUSA, Ronaldo Nogueira de et al. Exploring identifiability in hybrid models of cell signaling pathways. 2023, Anais.. Cham: Springer, 2023. Disponível em: https://doi.org/10.1007/978-3-031-42715-2_14. Acesso em: 28 nov. 2025.
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      Sousa, R. N. de, Campos, C. G. S., Wang, W., Hashimoto, R. F., Armelin, H. A., & Reis, M. S. (2023). Exploring identifiability in hybrid models of cell signaling pathways. In . Cham: Springer. doi:10.1007/978-3-031-42715-2_14
    • NLM

      Sousa RN de, Campos CGS, Wang W, Hashimoto RF, Armelin HA, Reis MS. Exploring identifiability in hybrid models of cell signaling pathways [Internet]. 2023 ;[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-3-031-42715-2_14
    • Vancouver

      Sousa RN de, Campos CGS, Wang W, Hashimoto RF, Armelin HA, Reis MS. Exploring identifiability in hybrid models of cell signaling pathways [Internet]. 2023 ;[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/978-3-031-42715-2_14
  • Source: Scientific Reports. Unidades: IME, Interunidades em Bioinformática

    Subjects: GEOMETRIA E MODELAGEM COMPUTACIONAL, BIOINFORMÁTICA

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      KAWASHIMA, Irina Yuri et al. SARS‑CoV‑2 host prediction based on virus‑host genetic features. Scientific Reports, v. 12, n. artigo 4576, p. 1-9, 2022Tradução . . Disponível em: https://doi.org/10.1038/s41598-022-08350-6. Acesso em: 28 nov. 2025.
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      Kawashima, I. Y., Lopez, M. C. N., Cunha, M. dos P., & Hashimoto, R. F. (2022). SARS‑CoV‑2 host prediction based on virus‑host genetic features. Scientific Reports, 12( artigo 4576), 1-9. doi:10.1038/s41598-022-08350-6
    • NLM

      Kawashima IY, Lopez MCN, Cunha M dos P, Hashimoto RF. SARS‑CoV‑2 host prediction based on virus‑host genetic features [Internet]. Scientific Reports. 2022 ; 12( artigo 4576): 1-9.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1038/s41598-022-08350-6
    • Vancouver

      Kawashima IY, Lopez MCN, Cunha M dos P, Hashimoto RF. SARS‑CoV‑2 host prediction based on virus‑host genetic features [Internet]. Scientific Reports. 2022 ; 12( artigo 4576): 1-9.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1038/s41598-022-08350-6
  • Source: São Paulo Journal of Mathematical Sciences. Unidade: IME

    Subjects: METODOLOGIA E TÉCNICAS DE COMPUTAÇÃO, PROCESSAMENTO DE IMAGENS

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      BARRERA, Junior et al. From mathematical morphology to machine learning of image operators. São Paulo Journal of Mathematical Sciences, 2022Tradução . . Disponível em: https://doi.org/10.1007/s40863-022-00303-1. Acesso em: 28 nov. 2025.
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      Barrera, J., Hashimoto, R. F., Hirata, N. S. T., Hirata Júnior, R., & Reis, M. S. (2022). From mathematical morphology to machine learning of image operators. São Paulo Journal of Mathematical Sciences. doi:10.1007/s40863-022-00303-1
    • NLM

      Barrera J, Hashimoto RF, Hirata NST, Hirata Júnior R, Reis MS. From mathematical morphology to machine learning of image operators [Internet]. São Paulo Journal of Mathematical Sciences. 2022 ;[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s40863-022-00303-1
    • Vancouver

      Barrera J, Hashimoto RF, Hirata NST, Hirata Júnior R, Reis MS. From mathematical morphology to machine learning of image operators [Internet]. São Paulo Journal of Mathematical Sciences. 2022 ;[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s40863-022-00303-1
  • Source: Pattern Recognition Letters. Unidade: IME

    Assunto: PROCESSAMENTO DE IMAGENS

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      GOBBER, Charles F e HASHIMOTO, Ronaldo Fumio e ALVES, Wonder Alexandre Luz. An efficient algorithm to update non-flat and incremental attributes in morphological trees. Pattern Recognition Letters, v. 163, p. 47-54, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2022.09.005. Acesso em: 28 nov. 2025.
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      Gobber, C. F., Hashimoto, R. F., & Alves, W. A. L. (2022). An efficient algorithm to update non-flat and incremental attributes in morphological trees. Pattern Recognition Letters, 163, 47-54. doi:10.1016/j.patrec.2022.09.005
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      Gobber CF, Hashimoto RF, Alves WAL. An efficient algorithm to update non-flat and incremental attributes in morphological trees [Internet]. Pattern Recognition Letters. 2022 ; 163 47-54.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.patrec.2022.09.005
    • Vancouver

      Gobber CF, Hashimoto RF, Alves WAL. An efficient algorithm to update non-flat and incremental attributes in morphological trees [Internet]. Pattern Recognition Letters. 2022 ; 163 47-54.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.patrec.2022.09.005
  • Source: IEEE-ACM Transactions on Computational Biology and Bioinformatics. Unidade: IME

    Subjects: ÁLGEBRAS DE BOOLE, EXPRESSÃO GÊNICA, ANÁLISE DE SÉRIES TEMPORAIS

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      HIGA, Carlos H. A e ANDRADE, Tales Pinheiro de e HASHIMOTO, Ronaldo Fumio. Growing seed genes from time series data and thresholded Boolean networks with perturbation. IEEE-ACM Transactions on Computational Biology and Bioinformatics, v. 10, n. 1, p. 37-49, 2013Tradução . . Disponível em: https://doi.org/10.1109/TCBB.2012.169. Acesso em: 28 nov. 2025.
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      Higa, C. H. A., Andrade, T. P. de, & Hashimoto, R. F. (2013). Growing seed genes from time series data and thresholded Boolean networks with perturbation. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 10( 1), 37-49. doi:10.1109/TCBB.2012.169
    • NLM

      Higa CHA, Andrade TP de, Hashimoto RF. Growing seed genes from time series data and thresholded Boolean networks with perturbation [Internet]. IEEE-ACM Transactions on Computational Biology and Bioinformatics. 2013 ; 10( 1): 37-49.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1109/TCBB.2012.169
    • Vancouver

      Higa CHA, Andrade TP de, Hashimoto RF. Growing seed genes from time series data and thresholded Boolean networks with perturbation [Internet]. IEEE-ACM Transactions on Computational Biology and Bioinformatics. 2013 ; 10( 1): 37-49.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1109/TCBB.2012.169
  • Source: Pattern recognition recent advances. Unidade: IME

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      RIBEIRO, João Henrique Burckas e HASHIMOTO, Ronaldo Fumio. Pattern recognition based on straight line segments. Pattern recognition recent advances. Tradução . Vienna: INTECH, 2010. . Disponível em: https://doi.org/10.5772/9351. Acesso em: 28 nov. 2025.
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      Ribeiro, J. H. B., & Hashimoto, R. F. (2010). Pattern recognition based on straight line segments. In Pattern recognition recent advances. Vienna: INTECH. doi:10.5772/9351
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      Ribeiro JHB, Hashimoto RF. Pattern recognition based on straight line segments [Internet]. In: Pattern recognition recent advances. Vienna: INTECH; 2010. [citado 2025 nov. 28 ] Available from: https://doi.org/10.5772/9351
    • Vancouver

      Ribeiro JHB, Hashimoto RF. Pattern recognition based on straight line segments [Internet]. In: Pattern recognition recent advances. Vienna: INTECH; 2010. [citado 2025 nov. 28 ] Available from: https://doi.org/10.5772/9351
  • Source: IEEE Journal of Selected Topics in Signal Processing. Unidade: IME

    Subjects: COMPUTAÇÃO GRÁFICA, GENES, BIOINFORMÁTICA

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      MARTINS JÚNIOR, David Correa et al. Intrinsically multivariate predictive genes. IEEE Journal of Selected Topics in Signal Processing, v. 2, n. 3, p. 424-439, 2008Tradução . . Disponível em: https://doi.org/10.1109/JSTSP.2008.923841. Acesso em: 28 nov. 2025.
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      Martins Júnior, D. C., Braga-Neto, U. de M., Hashimoto, R. F., Bittner, M. L., & Dougherty, E. R. (2008). Intrinsically multivariate predictive genes. IEEE Journal of Selected Topics in Signal Processing, 2( 3), 424-439. doi:10.1109/JSTSP.2008.923841
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      Martins Júnior DC, Braga-Neto U de M, Hashimoto RF, Bittner ML, Dougherty ER. Intrinsically multivariate predictive genes [Internet]. IEEE Journal of Selected Topics in Signal Processing. 2008 ; 2( 3): 424-439.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1109/JSTSP.2008.923841
    • Vancouver

      Martins Júnior DC, Braga-Neto U de M, Hashimoto RF, Bittner ML, Dougherty ER. Intrinsically multivariate predictive genes [Internet]. IEEE Journal of Selected Topics in Signal Processing. 2008 ; 2( 3): 424-439.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1109/JSTSP.2008.923841

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