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  • Trabalho de evento

    Biological sequence analysis using complex networks and entropy maximization: a case study in SARS-CoV-2 (2023)

    Pimenta-Zanon, Matheus H. ; de Souza, Vinicius Augusto; Hashimoto, Ronaldo Fumio ; Lopes, Fabricio Martins

    Source: Ambient intelligence in health care : proccedings. 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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    • ABNT

      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: 08 jun. 2023.

    • APA

      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 : proccedings. 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 : proccedings. 2023 ;[citado 2023 jun. 08 ] 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 : proccedings. 2023 ;[citado 2023 jun. 08 ] Available from: https://doi.org/10.1007/978-981-19-6068-0_44

  • Artigo de periodico

    The C-SHIFT algorithm for normalizing covariances (2023)

    Chunikhina, Evgenia ; Logan, Paul; Kovchegov, Yevgeniy ; Iambartsev, Anatoli ; Mondal, Debashis ; Morgun, Andrey

    Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics. Unidade: IME

    Subjects: BIOINFORMÁTICA, ESTATÍSTICA APLICADA

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      CHUNIKHINA, Evgenia et al. The C-SHIFT algorithm for normalizing covariances. IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. 20, n. 1, p. 720-730, 2023Tradução . . Disponível em: http://dx.doi.org/10.1109/TCBB.2022.3151840. Acesso em: 08 jun. 2023.

    • APA

      Chunikhina, E., Logan, P., Kovchegov, Y., Iambartsev, A., Mondal, D., & Morgun, A. (2023). The C-SHIFT algorithm for normalizing covariances. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20( 1), 720-730. doi:10.1109/TCBB.2022.3151840

    • NLM

      Chunikhina E, Logan P, Kovchegov Y, Iambartsev A, Mondal D, Morgun A. The C-SHIFT algorithm for normalizing covariances [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2023 ; 20( 1): 720-730.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1109/TCBB.2022.3151840

    • Vancouver

      Chunikhina E, Logan P, Kovchegov Y, Iambartsev A, Mondal D, Morgun A. The C-SHIFT algorithm for normalizing covariances [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2023 ; 20( 1): 720-730.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1109/TCBB.2022.3151840

  • Artigo de periodico

    Population-based change-point detection for the identification of homozygosity islands (2023)

    Prates, Lucas de Oliveira; Lemes, Renan Barbosa ; Hünemeier, Tábita ; Leonardi, Florencia Graciela

    Source: Bioinformatics. Unidades: IB, IME

    Assunto: BIOINFORMÁTICA

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      PRATES, Lucas de Oliveira et al. Population-based change-point detection for the identification of homozygosity islands. Bioinformatics, v. 39, n. 4, p. 1-8, 2023Tradução . . Disponível em: https://doi.org/10.1093/bioinformatics/btad170. Acesso em: 08 jun. 2023.

    • APA

      Prates, L. de O., Lemes, R. B., Hünemeier, T., & Leonardi, F. G. (2023). Population-based change-point detection for the identification of homozygosity islands. Bioinformatics, 39( 4), 1-8. doi:10.1093/bioinformatics/btad170

    • NLM

      Prates L de O, Lemes RB, Hünemeier T, Leonardi FG. Population-based change-point detection for the identification of homozygosity islands [Internet]. Bioinformatics. 2023 ; 39( 4): 1-8.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1093/bioinformatics/btad170

    • Vancouver

      Prates L de O, Lemes RB, Hünemeier T, Leonardi FG. Population-based change-point detection for the identification of homozygosity islands [Internet]. Bioinformatics. 2023 ; 39( 4): 1-8.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1093/bioinformatics/btad170

  • Artigo de periodico

    Genome-wide promoter methylation profling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival (2022)

    Rius, Flávia Eichemberger ; Papaiz, Debora D'Angelo ; Azevedo, Hátylas ; Ayub, Ana Luísa P ; Pessoa, Diogo de Oliveira ; Oliveira, Tiago Franco de ; Loureiro, Ana Paula de Melo ; Andrade, Fernando; Fujita, André ; Reis, Eduardo Moraes ; Mason, Christopher E; Jasiulionis, Miriam Galvonas

    Source: Clinical Epigenetics. Unidades: IME, FCF, IQ

    Subjects: GENOMAS, MELANOMA, BIOINFORMÁTICA

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    • ABNT

      RIUS, Flávia Eichemberger et al. Genome-wide promoter methylation profling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival. Clinical Epigenetics, v. 14, n. artigo 68, p. 1-20, 2022Tradução . . Disponível em: https://doi.org/10.1186/s13148-022-01291-x. Acesso em: 08 jun. 2023.

    • APA

      Rius, F. E., Papaiz, D. D. 'A., Azevedo, H., Ayub, A. L. P., Pessoa, D. de O., Oliveira, T. F. de, et al. (2022). Genome-wide promoter methylation profling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival. Clinical Epigenetics, 14( artigo 68), 1-20. doi:10.1186/s13148-022-01291-x

    • NLM

      Rius FE, Papaiz DD'A, Azevedo H, Ayub ALP, Pessoa D de O, Oliveira TF de, Loureiro AP de M, Andrade F, Fujita A, Reis EM, Mason CE, Jasiulionis MG. Genome-wide promoter methylation profling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival [Internet]. Clinical Epigenetics. 2022 ; 14( artigo 68): 1-20.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1186/s13148-022-01291-x

    • Vancouver

      Rius FE, Papaiz DD'A, Azevedo H, Ayub ALP, Pessoa D de O, Oliveira TF de, Loureiro AP de M, Andrade F, Fujita A, Reis EM, Mason CE, Jasiulionis MG. Genome-wide promoter methylation profling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival [Internet]. Clinical Epigenetics. 2022 ; 14( artigo 68): 1-20.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1186/s13148-022-01291-x

  • Artigo de periodico

    SARS‑CoV‑2 host prediction based on virus‑host genetic features (2022)

    Kawashima, IrinaYuri ; Lopez, Maria Claudia Negret ; Cunha, Marielton dos Passos ; Hashimoto, Ronaldo Fumio

    Source: Scientific Reports. Unidades: IME, BIOINFORMÁTICA

    Subjects: GEOMETRIA E MODELAGEM COMPUTACIONAL, BIOINFORMÁTICA

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    • ABNT

      KAWASHIMA, IrinaYuri 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: 08 jun. 2023.

    • APA

      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 2023 jun. 08 ] 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 2023 jun. 08 ] Available from: https://doi.org/10.1038/s41598-022-08350-6

  • Artigo de periodico

    Heart rate variability predicts the subject-driven cognitive states (2022)

    Farfán, Carlos Enrique Paucar ; Bruel, Pedro ; Goldman, Alfredo ; Takahashi, Daniel Yasumasa ; Fujita, André

    Source: Research Square. Unidade: IME

    Assunto: BIOINFORMÁTICA

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    • ABNT

      FARFÁN, Carlos Enrique Paucar et al. Heart rate variability predicts the subject-driven cognitive states. Research Square, 2022Tradução . . Disponível em: https://doi.org/10.21203/rs.3.rs-1957712/v1. Acesso em: 08 jun. 2023.

    • APA

      Farfán, C. E. P., Bruel, P., Goldman, A., Takahashi, D. Y., & Fujita, A. (2022). Heart rate variability predicts the subject-driven cognitive states. Research Square. doi:10.21203/rs.3.rs-1957712/v1

    • NLM

      Farfán CEP, Bruel P, Goldman A, Takahashi DY, Fujita A. Heart rate variability predicts the subject-driven cognitive states [Internet]. Research Square. 2022 ;[citado 2023 jun. 08 ] Available from: https://doi.org/10.21203/rs.3.rs-1957712/v1

    • Vancouver

      Farfán CEP, Bruel P, Goldman A, Takahashi DY, Fujita A. Heart rate variability predicts the subject-driven cognitive states [Internet]. Research Square. 2022 ;[citado 2023 jun. 08 ] Available from: https://doi.org/10.21203/rs.3.rs-1957712/v1

  • Artigo de periodico

    A Boolean model of the proliferative role of the lncRNA XIST in non-small cell lung cancer cells (2022)

    Gupta, Shantanu ; Silveira, Daner Acunha ; Hashimoto, Ronaldo Fumio ; Mombach, Jose Carlos M.

    Source: Biology. Unidade: IME

    Subjects: GEOMETRIA E MODELAGEM COMPUTACIONAL, BIOINFORMÁTICA

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    • ABNT

      GUPTA, Shantanu et al. A Boolean model of the proliferative role of the lncRNA XIST in non-small cell lung cancer cells. Biology, v. 11, n. artigo 480, p. 1-14, 2022Tradução . . Disponível em: https://doi.org/10.3390/biology11040480. Acesso em: 08 jun. 2023.

    • APA

      Gupta, S., Silveira, D. A., Hashimoto, R. F., & Mombach, J. C. M. (2022). A Boolean model of the proliferative role of the lncRNA XIST in non-small cell lung cancer cells. Biology, 11( artigo 480), 1-14. doi:10.3390/biology11040480

    • NLM

      Gupta S, Silveira DA, Hashimoto RF, Mombach JCM. A Boolean model of the proliferative role of the lncRNA XIST in non-small cell lung cancer cells [Internet]. Biology. 2022 ; 11( artigo 480): 1-14.[citado 2023 jun. 08 ] Available from: https://doi.org/10.3390/biology11040480

    • Vancouver

      Gupta S, Silveira DA, Hashimoto RF, Mombach JCM. A Boolean model of the proliferative role of the lncRNA XIST in non-small cell lung cancer cells [Internet]. Biology. 2022 ; 11( artigo 480): 1-14.[citado 2023 jun. 08 ] Available from: https://doi.org/10.3390/biology11040480

  • Artigo de periodico

    Totoro: identifying active reactions during the transient state for metabolic perturbations (2022)

    Ferrarini, Mariana Galvão ; Ziska, Irene; Andrade, Ricardo; Julien-Laferrière, Alice ; Duchemin, Louis ; César Júnior, Roberto Marcondes ; Mary, Arnaud ; Vinga, Susana ; Sagot, Marie-France

    Source: Frontiers in Genetics. Unidade: IME

    Subjects: BIOINFORMÁTICA, METABOLÔMICA

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    • ABNT

      FERRARINI, Mariana Galvão et al. Totoro: identifying active reactions during the transient state for metabolic perturbations. Frontiers in Genetics, v. 13, 2022Tradução . . Disponível em: https://doi.org/10.3389/fgene.2022.815476. Acesso em: 08 jun. 2023.

    • APA

      Ferrarini, M. G., Ziska, I., Andrade, R., Julien-Laferrière, A., Duchemin, L., César Júnior, R. M., et al. (2022). Totoro: identifying active reactions during the transient state for metabolic perturbations. Frontiers in Genetics, 13. doi:10.3389/fgene.2022.815476

    • NLM

      Ferrarini MG, Ziska I, Andrade R, Julien-Laferrière A, Duchemin L, César Júnior RM, Mary A, Vinga S, Sagot M-F. Totoro: identifying active reactions during the transient state for metabolic perturbations [Internet]. Frontiers in Genetics. 2022 ; 13[citado 2023 jun. 08 ] Available from: https://doi.org/10.3389/fgene.2022.815476

    • Vancouver

      Ferrarini MG, Ziska I, Andrade R, Julien-Laferrière A, Duchemin L, César Júnior RM, Mary A, Vinga S, Sagot M-F. Totoro: identifying active reactions during the transient state for metabolic perturbations [Internet]. Frontiers in Genetics. 2022 ; 13[citado 2023 jun. 08 ] Available from: https://doi.org/10.3389/fgene.2022.815476

  • Artigo de periodico

    A multi-agent approach used to predict long-term glucose oscillation in individuals with type 1 diabetes (2022)

    Pereira, João Paulo Aragão ; Brandão, Anarosa Alves Franco ; Bevilacqua, Joyce da Silva; Giannella, Maria Lucia Cardillo Correa

    Source: Applied Sciences. Unidades: EP, IME, FM

    Subjects: DIABETES MELLITUS, DIABETES MELLITUS NÃO INSULINO-DEPENDENTE, BIOINFORMÁTICA, PREDIÇÃO

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    • ABNT

      PEREIRA, João Paulo Aragão et al. A multi-agent approach used to predict long-term glucose oscillation in individuals with type 1 diabetes. Applied Sciences, v. 12, n. 19O, 2022Tradução . . Disponível em: https://doi.org/10.3390/app12199641. Acesso em: 08 jun. 2023.

    • APA

      Pereira, J. P. A., Brandão, A. A. F., Bevilacqua, J. da S., & Giannella, M. L. C. C. (2022). A multi-agent approach used to predict long-term glucose oscillation in individuals with type 1 diabetes. Applied Sciences, 12( 19O). doi:10.3390/app12199641

    • NLM

      Pereira JPA, Brandão AAF, Bevilacqua J da S, Giannella MLCC. A multi-agent approach used to predict long-term glucose oscillation in individuals with type 1 diabetes [Internet]. Applied Sciences. 2022 ; 12( 19O):[citado 2023 jun. 08 ] Available from: https://doi.org/10.3390/app12199641

    • Vancouver

      Pereira JPA, Brandão AAF, Bevilacqua J da S, Giannella MLCC. A multi-agent approach used to predict long-term glucose oscillation in individuals with type 1 diabetes [Internet]. Applied Sciences. 2022 ; 12( 19O):[citado 2023 jun. 08 ] Available from: https://doi.org/10.3390/app12199641

  • Artigo de periodico

    CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts (2021)

    Nachtigall, Pedro Gabriel ; Kashiwabara, André Yoshiaki ; Durham, Alan Mitchell

    Source: Briefings in Bioinformatics. Unidade: IME

    Subjects: BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO

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    • ABNT

      NACHTIGALL, Pedro Gabriel e KASHIWABARA, André Yoshiaki e DURHAM, Alan Mitchell. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, v. 22, n. 3, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbaa045. Acesso em: 08 jun. 2023.

    • APA

      Nachtigall, P. G., Kashiwabara, A. Y., & Durham, A. M. (2021). CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, 22( 3), 1-11. doi:10.1093/bib/bbaa045

    • NLM

      Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1093/bib/bbaa045

    • Vancouver

      Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1093/bib/bbaa045

  • Parte de monografia/livro

    Computational analysis of transposable elements and circRNAs in plants (2021)

    Oliveira, Liliane Santana; Patera, Andressa Caroline; Domingues, Douglas Silva ; Sanches, Danilo Sipoli; Lopes, Fabricio Martins ; Bugatti, Pedro Henrique ; Saito, Priscila Tiemi Maeda; Maracaja-Coutinho, Vinicius ; Durham, Alan Mitchell ; Paschoal, Alexandre Rossi

    Source: Plant circular RNAs : methods and protocols. Unidade: IME

    Assunto: BIOINFORMÁTICA

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    • ABNT

      OLIVEIRA, Liliane Santana et al. Computational analysis of transposable elements and circRNAs in plants. Plant circular RNAs : methods and protocols. Tradução . New York: Humana, 2021. . Disponível em: https://doi.org/10.1007/978-1-0716-1645-1_9. Acesso em: 08 jun. 2023.

    • APA

      Oliveira, L. S., Patera, A. C., Domingues, D. S., Sanches, D. S., Lopes, F. M., Bugatti, P. H., et al. (2021). Computational analysis of transposable elements and circRNAs in plants. In Plant circular RNAs : methods and protocols. New York: Humana. doi:10.1007/978-1-0716-1645-1_9

    • NLM

      Oliveira LS, Patera AC, Domingues DS, Sanches DS, Lopes FM, Bugatti PH, Saito PTM, Maracaja-Coutinho V, Durham AM, Paschoal AR. Computational analysis of transposable elements and circRNAs in plants [Internet]. In: Plant circular RNAs : methods and protocols. New York: Humana; 2021. [citado 2023 jun. 08 ] Available from: https://doi.org/10.1007/978-1-0716-1645-1_9

    • Vancouver

      Oliveira LS, Patera AC, Domingues DS, Sanches DS, Lopes FM, Bugatti PH, Saito PTM, Maracaja-Coutinho V, Durham AM, Paschoal AR. Computational analysis of transposable elements and circRNAs in plants [Internet]. In: Plant circular RNAs : methods and protocols. New York: Humana; 2021. [citado 2023 jun. 08 ] Available from: https://doi.org/10.1007/978-1-0716-1645-1_9

  • Artigo de periodico

    TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes (2021)

    Oliveira, Mauro de Medeiros ; Bonadio, Ígor ; Melo, Alícia Lie de ; Souza, Gláucia Mendes ; Durham, Alan Mitchell

    Source: Briefings in Bioinformatics. Unidades: IQ, IME, BIOINFORMÁTICA

    Subjects: TRANSCRIÇÃO GÊNICA, BIOINFORMÁTICA

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    • ABNT

      OLIVEIRA, Mauro de Medeiros et al. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes. Briefings in Bioinformatics, v. 22, n. 6, p. 1-12, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbab198. Acesso em: 08 jun. 2023.

    • APA

      Oliveira, M. de M., Bonadio, Í., Melo, A. L. de, Souza, G. M., & Durham, A. M. (2021). TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes. Briefings in Bioinformatics, 22( 6), 1-12. doi:10.1093/bib/bbab198

    • NLM

      Oliveira M de M, Bonadio Í, Melo AL de, Souza GM, Durham AM. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes [Internet]. Briefings in Bioinformatics. 2021 ; 22( 6): 1-12.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1093/bib/bbab198

    • Vancouver

      Oliveira M de M, Bonadio Í, Melo AL de, Souza GM, Durham AM. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes [Internet]. Briefings in Bioinformatics. 2021 ; 22( 6): 1-12.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1093/bib/bbab198

  • Artigo de periodico

    Noninvasive prenatal paternity determination using microhaplotypes: a pilot study (2020)

    Wang, Jaqueline Yu Ting; Whittle, Martin R. ; Puga, Renato David ; Yambartsev, Anatoli ; Fujita, André ; Nakaya, Helder Takashi Imoto

    Source: BMC Medical Genomics. Unidades: IME, FCF, BIOINFORMÁTICA

    Subjects: DIAGNÓSTICO PRÉ-NATAL, PATERNIDADE, BIOINFORMÁTICA, HAPLOTIPOS

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    • ABNT

      WANG, Jaqueline Yu Ting et al. Noninvasive prenatal paternity determination using microhaplotypes: a pilot study. BMC Medical Genomics, v. 13, n. art. 157, p. 1-8, 2020Tradução . . Disponível em: https://doi.org/10.1186/s12920-020-00806-w. Acesso em: 08 jun. 2023.

    • APA

      Wang, J. Y. T., Whittle, M. R., Puga, R. D., Yambartsev, A., Fujita, A., & Nakaya, H. T. I. (2020). Noninvasive prenatal paternity determination using microhaplotypes: a pilot study. BMC Medical Genomics, 13( art. 157), 1-8. doi:10.1186/s12920-020-00806-w

    • NLM

      Wang JYT, Whittle MR, Puga RD, Yambartsev A, Fujita A, Nakaya HTI. Noninvasive prenatal paternity determination using microhaplotypes: a pilot study [Internet]. BMC Medical Genomics. 2020 ; 13( art. 157): 1-8.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1186/s12920-020-00806-w

    • Vancouver

      Wang JYT, Whittle MR, Puga RD, Yambartsev A, Fujita A, Nakaya HTI. Noninvasive prenatal paternity determination using microhaplotypes: a pilot study [Internet]. BMC Medical Genomics. 2020 ; 13( art. 157): 1-8.[citado 2023 jun. 08 ] Available from: https://doi.org/10.1186/s12920-020-00806-w

  • Artigo de periodico

    A semi-parametric statistical test to compare complex networks (2020)

    Fujita, André ; Lira, Eduardo Silva ; Santos, Suzana de Siqueira ; Bando, Sílvia Yumi ; Soares, Gabriela Eleuterio ; Takahashi, Daniel Yasumasa

    Source: Journal of Complex Networks. Unidades: IME, FM, EEFERP

    Subjects: INFERÊNCIA PARAMÉTRICA, BIOINFORMÁTICA

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    • ABNT

      FUJITA, André et al. A semi-parametric statistical test to compare complex networks. Journal of Complex Networks, v. 8, n. 2, 2020Tradução . . Disponível em: http://dx.doi.org/10.1093/comnet/cnz028. Acesso em: 08 jun. 2023.

    • APA

      Fujita, A., Lira, E. S., Santos, S. de S., Bando, S. Y., Soares, G. E., & Takahashi, D. Y. (2020). A semi-parametric statistical test to compare complex networks. Journal of Complex Networks, 8( 2). doi:10.1093/comnet/cnz028

    • NLM

      Fujita A, Lira ES, Santos S de S, Bando SY, Soares GE, Takahashi DY. A semi-parametric statistical test to compare complex networks [Internet]. Journal of Complex Networks. 2020 ; 8( 2):[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1093/comnet/cnz028

    • Vancouver

      Fujita A, Lira ES, Santos S de S, Bando SY, Soares GE, Takahashi DY. A semi-parametric statistical test to compare complex networks [Internet]. Journal of Complex Networks. 2020 ; 8( 2):[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1093/comnet/cnz028

  • Parte de monografia/livro

    Network analysis of neuropsychiatry disorders (2020)

    Castro Guzman, Grover Enrique ; Balardin, Joana Bisol ; Biazoli Junior, Claudinei Eduardo; Sato, João Ricardo ; Fujita, André

    Source: Precision medicine for investigators, practitioners and providers. Unidade: IME

    Subjects: DIAGNÓSTICO POR COMPUTADOR, BIOINFORMÁTICA, PSIQUIATRIA, ENTROPIA

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      CASTRO GUZMAN, Grover Enrique et al. Network analysis of neuropsychiatry disorders. Precision medicine for investigators, practitioners and providers. Tradução . San Diego: Elsevier, 2020. . Disponível em: https://doi.org/10.1016/B978-0-12-819178-1.00039-3. Acesso em: 08 jun. 2023.

    • APA

      Castro Guzman, G. E., Balardin, J. B., Biazoli Junior, C. E., Sato, J. R., & Fujita, A. (2020). Network analysis of neuropsychiatry disorders. In Precision medicine for investigators, practitioners and providers. San Diego: Elsevier. doi:10.1016/B978-0-12-819178-1.00039-3

    • NLM

      Castro Guzman GE, Balardin JB, Biazoli Junior CE, Sato JR, Fujita A. Network analysis of neuropsychiatry disorders [Internet]. In: Precision medicine for investigators, practitioners and providers. San Diego: Elsevier; 2020. [citado 2023 jun. 08 ] Available from: https://doi.org/10.1016/B978-0-12-819178-1.00039-3

    • Vancouver

      Castro Guzman GE, Balardin JB, Biazoli Junior CE, Sato JR, Fujita A. Network analysis of neuropsychiatry disorders [Internet]. In: Precision medicine for investigators, practitioners and providers. San Diego: Elsevier; 2020. [citado 2023 jun. 08 ] Available from: https://doi.org/10.1016/B978-0-12-819178-1.00039-3

  • Artigo de periodico

    Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells (2020)

    Pereira, Túlio Felipe; Levin, Gabriel ; DeOcesano-Pereira, Carlos ; Caodaglio, Amanda Schiersner ; Fujita, André ; Tonso, Aldo ; Sogayar, Mari Cleide

    Source: BMC Research Notes. Unidades: IME, EP, IQ, BIOTECNOLOGIA, FM

    Subjects: BIOINFORMÁTICA, PROLIFERAÇÃO CELULAR

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      PEREIRA, Túlio Felipe et al. Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells. BMC Research Notes, v. 13, n. 1, p. 1-7, 2020Tradução . . Disponível em: http://dx.doi.org/10.1186/s13104-020-4914-8. Acesso em: 08 jun. 2023.

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      Pereira, T. F., Levin, G., DeOcesano-Pereira, C., Caodaglio, A. S., Fujita, A., Tonso, A., & Sogayar, M. C. (2020). Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells. BMC Research Notes, 13( 1), 1-7. doi:10.1186/s13104-020-4914-8

    • NLM

      Pereira TF, Levin G, DeOcesano-Pereira C, Caodaglio AS, Fujita A, Tonso A, Sogayar MC. Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells [Internet]. BMC Research Notes. 2020 ;13( 1): 1-7.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1186/s13104-020-4914-8

    • Vancouver

      Pereira TF, Levin G, DeOcesano-Pereira C, Caodaglio AS, Fujita A, Tonso A, Sogayar MC. Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells [Internet]. BMC Research Notes. 2020 ;13( 1): 1-7.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1186/s13104-020-4914-8

  • Artigo de periodico

    Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer (2020)

    Andrade, Fernando; Nakata, Asuka; Gotoh, Noriko ; Fujita, André

    Source: Genetics and Molecular Biology. Unidades: IME, BIOINFORMÁTICA

    Subjects: BIOINFORMÁTICA, NEOPLASIAS, ANÁLISE DE SOBREVIVÊNCIA

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      ANDRADE, Fernando et al. Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer. Genetics and Molecular Biology, v. 43, n. 1, p. 1-11, 2020Tradução . . Disponível em: http://dx.doi.org/10.1590/1678-4685-gmb-2018-0269. Acesso em: 08 jun. 2023.

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      Andrade, F., Nakata, A., Gotoh, N., & Fujita, A. (2020). Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer. Genetics and Molecular Biology, 43( 1), 1-11. doi:10.1590/1678-4685-gmb-2018-0269

    • NLM

      Andrade F, Nakata A, Gotoh N, Fujita A. Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer [Internet]. Genetics and Molecular Biology. 2020 ; 43( 1): 1-11.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1590/1678-4685-gmb-2018-0269

    • Vancouver

      Andrade F, Nakata A, Gotoh N, Fujita A. Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer [Internet]. Genetics and Molecular Biology. 2020 ; 43( 1): 1-11.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1590/1678-4685-gmb-2018-0269

  • Artigo de periodico

    BioNetStat: a tool for biological networks differential analysis (2019)

    Jardim, Vinícius Carvalho; Santos, Suzana de Siqueira ; Fujita, André ; Buckeridge, Marcos Silveira

    Source: Frontiers in Genetics. Unidades: IME, IB, BIOINFORMÁTICA

    Assunto: BIOINFORMÁTICA

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      JARDIM, Vinícius Carvalho et al. BioNetStat: a tool for biological networks differential analysis. Frontiers in Genetics, v. 10, 2019Tradução . . Disponível em: http://dx.doi.org/10.3389/fgene.2019.00594. Acesso em: 08 jun. 2023.

    • APA

      Jardim, V. C., Santos, S. de S., Fujita, A., & Buckeridge, M. S. (2019). BioNetStat: a tool for biological networks differential analysis. Frontiers in Genetics, 10. doi:10.3389/fgene.2019.00594

    • NLM

      Jardim VC, Santos S de S, Fujita A, Buckeridge MS. BioNetStat: a tool for biological networks differential analysis [Internet]. Frontiers in Genetics. 2019 ; 10[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.3389/fgene.2019.00594

    • Vancouver

      Jardim VC, Santos S de S, Fujita A, Buckeridge MS. BioNetStat: a tool for biological networks differential analysis [Internet]. Frontiers in Genetics. 2019 ; 10[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.3389/fgene.2019.00594

  • Artigo de periodico

    Gene expression and promoter methylation of angiogenic and lymphangiogenic factors as prognostic markers in melanoma (2019)

    Monteiro, Ana Carolina; Muenzner, Julienne Kathrin; Andrade, Fernando; Rius, Flávia Eichemberger ; Ostalecki, Christian; Geppert, Carol Immanuel; Agaimy, Abbas ; Hartmann, Arndt ; Fujita, André ; Schneider‐Stock, Regine ; Jasiulionis, Miriam G

    Source: Molecular Oncology. Unidade: IME

    Assunto: BIOINFORMÁTICA

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      MONTEIRO, Ana Carolina et al. Gene expression and promoter methylation of angiogenic and lymphangiogenic factors as prognostic markers in melanoma. Molecular Oncology, v. 13, p. 1433-1449, 2019Tradução . . Disponível em: http://dx.doi.org/10.1002/1878-0261.12501. Acesso em: 08 jun. 2023.

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      Monteiro, A. C., Muenzner, J. K., Andrade, F., Rius, F. E., Ostalecki, C., Geppert, C. I., et al. (2019). Gene expression and promoter methylation of angiogenic and lymphangiogenic factors as prognostic markers in melanoma. Molecular Oncology, 13, 1433-1449. doi:10.1002/1878-0261.12501

    • NLM

      Monteiro AC, Muenzner JK, Andrade F, Rius FE, Ostalecki C, Geppert CI, Agaimy A, Hartmann A, Fujita A, Schneider‐Stock R, Jasiulionis MG. Gene expression and promoter methylation of angiogenic and lymphangiogenic factors as prognostic markers in melanoma [Internet]. Molecular Oncology. 2019 ; 13 1433-1449.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1002/1878-0261.12501

    • Vancouver

      Monteiro AC, Muenzner JK, Andrade F, Rius FE, Ostalecki C, Geppert CI, Agaimy A, Hartmann A, Fujita A, Schneider‐Stock R, Jasiulionis MG. Gene expression and promoter methylation of angiogenic and lymphangiogenic factors as prognostic markers in melanoma [Internet]. Molecular Oncology. 2019 ; 13 1433-1449.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1002/1878-0261.12501

  • Artigo de periodico

    CHD7 promotes glioblastoma cell motility and invasiveness through transcriptional modulation of an invasion signature (2019)

    Machado, Raquel Arminda Carvalho ; Schneider, Hannah; DeOcesano-Pereira, Carlos ; Lichtenstein, Flávio ; Andrade, Fernando; Fujita, André ; Lima, Marina Trombetta ; Weller, Michael; Bowman-Colin, Christian ; Sogayar, Mari Cleide

    Source: Scientific Reports. Unidades: IME, IQ, FM

    Assunto: BIOINFORMÁTICA

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      MACHADO, Raquel Arminda Carvalho et al. CHD7 promotes glioblastoma cell motility and invasiveness through transcriptional modulation of an invasion signature. Scientific Reports, v. 9, p. 1-13 art. 3952, 2019Tradução . . Disponível em: http://dx.doi.org/10.1038/s41598-019-39564-w. Acesso em: 08 jun. 2023.

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      Machado, R. A. C., Schneider, H., DeOcesano-Pereira, C., Lichtenstein, F., Andrade, F., Fujita, A., et al. (2019). CHD7 promotes glioblastoma cell motility and invasiveness through transcriptional modulation of an invasion signature. Scientific Reports, 9, 1-13 art. 3952. doi:10.1038/s41598-019-39564-w

    • NLM

      Machado RAC, Schneider H, DeOcesano-Pereira C, Lichtenstein F, Andrade F, Fujita A, Lima MT, Weller M, Bowman-Colin C, Sogayar MC. CHD7 promotes glioblastoma cell motility and invasiveness through transcriptional modulation of an invasion signature [Internet]. Scientific Reports. 2019 ; 9 1-13 art. 3952.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1038/s41598-019-39564-w

    • Vancouver

      Machado RAC, Schneider H, DeOcesano-Pereira C, Lichtenstein F, Andrade F, Fujita A, Lima MT, Weller M, Bowman-Colin C, Sogayar MC. CHD7 promotes glioblastoma cell motility and invasiveness through transcriptional modulation of an invasion signature [Internet]. Scientific Reports. 2019 ; 9 1-13 art. 3952.[citado 2023 jun. 08 ] Available from: http://dx.doi.org/10.1038/s41598-019-39564-w

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