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Artigo de periodico
Integrating comparative genomics and risk classification by assessing virulence, antimicrobial resistance, and plasmid spread in microbial communities with gSpreadComp (2025)
Kasmanas, Jonas Coelho ; Magnúsdóttir, Stefanía ; Zhang, Junyan; Smalla, Kornelia ; Schloter, Michael ; Stadler, Peter Florian ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Rocha, Ulisses Nunes da
Fonte: GigaScience. Unidade: ICMC
Assuntos: BIOINFORMÁTICA, GENÔMICA, VIRULÊNCIA, RESISTÊNCIA MICROBIANA ÀS DROGAS, BIOTA INTESTINAL, DIETA
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KASMANAS, Jonas Coelho et al. Integrating comparative genomics and risk classification by assessing virulence, antimicrobial resistance, and plasmid spread in microbial communities with gSpreadComp. GigaScience, v. 14, p. 1-17, 2025Tradução . . Disponível em: https://doi.org/10.1093/gigascience/giaf072. Acesso em: 23 nov. 2025.
APA
Kasmanas, J. C., Magnúsdóttir, S., Zhang, J., Smalla, K., Schloter, M., Stadler, P. F., et al. (2025). Integrating comparative genomics and risk classification by assessing virulence, antimicrobial resistance, and plasmid spread in microbial communities with gSpreadComp. GigaScience, 14, 1-17. doi:10.1093/gigascience/giaf072
NLM
Kasmanas JC, Magnúsdóttir S, Zhang J, Smalla K, Schloter M, Stadler PF, Carvalho ACP de LF de, Rocha UN da. Integrating comparative genomics and risk classification by assessing virulence, antimicrobial resistance, and plasmid spread in microbial communities with gSpreadComp [Internet]. GigaScience. 2025 ; 14 1-17.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/gigascience/giaf072
Vancouver
Kasmanas JC, Magnúsdóttir S, Zhang J, Smalla K, Schloter M, Stadler PF, Carvalho ACP de LF de, Rocha UN da. Integrating comparative genomics and risk classification by assessing virulence, antimicrobial resistance, and plasmid spread in microbial communities with gSpreadComp [Internet]. GigaScience. 2025 ; 14 1-17.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/gigascience/giaf072
Artigo de periodico
BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning (2024)
Florentino, Bruno Rafael ; Bonidia, Robson Parmezan ; Sanches, Natan Henrique ; Rocha, Ulisses Nunes da ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Fonte: Computational and Structural Biotechnology Journal. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ALGORITMOS ÚTEIS E ESPECÍFICOS, BIOINFORMÁTICA, GENÔMICA
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FLORENTINO, Bruno Rafael et al. BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning. Computational and Structural Biotechnology Journal, v. 23, p. 2267-2276, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.csbj.2024.05.031. Acesso em: 23 nov. 2025.
APA
Florentino, B. R., Bonidia, R. P., Sanches, N. H., Rocha, U. N. da, & Carvalho, A. C. P. de L. F. de. (2024). BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning. Computational and Structural Biotechnology Journal, 23, 2267-2276. doi:10.1016/j.csbj.2024.05.031
NLM
Florentino BR, Bonidia RP, Sanches NH, Rocha UN da, Carvalho ACP de LF de. BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning [Internet]. Computational and Structural Biotechnology Journal. 2024 ; 23 2267-2276.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1016/j.csbj.2024.05.031
Vancouver
Florentino BR, Bonidia RP, Sanches NH, Rocha UN da, Carvalho ACP de LF de. BioPrediction-RPI: democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning [Internet]. Computational and Structural Biotechnology Journal. 2024 ; 23 2267-2276.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1016/j.csbj.2024.05.031
Artigo de periodico
MuDoGeR: multi-domain genome recovery from metagenomes made easy (2024)
Rocha, Ulisses Nunes da ; Kasmanas, Jonas Coelho ; Kallies, René ; Saraiva, João Pedro ; Toscan, Rodolfo Brizola; Štefanič, Polonca; Bicalho, Marcos Fleming; Corrêa, Felipe Borim ; Baştürk, Merve Nida; Fousekis, Efthymios; Barbosa, Luiz Miguel Viana; Plewka, Julia ; Probst, Alexander J ; Baldrian, Petr ; Stadler, Peter F
Fonte: Molecular Ecology Resources. Unidade: ICMC
Assuntos: BIOINFORMÁTICA, GENÔMICA
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ROCHA, Ulisses Nunes da et al. MuDoGeR: multi-domain genome recovery from metagenomes made easy. Molecular Ecology Resources, v. 24, n. 2, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1111/1755-0998.13904. Acesso em: 23 nov. 2025.
APA
Rocha, U. N. da, Kasmanas, J. C., Kallies, R., Saraiva, J. P., Toscan, R. B., Štefanič, P., et al. (2024). MuDoGeR: multi-domain genome recovery from metagenomes made easy. Molecular Ecology Resources, 24( 2), 1-12. doi:10.1111/1755-0998.13904
NLM
Rocha UN da, Kasmanas JC, Kallies R, Saraiva JP, Toscan RB, Štefanič P, Bicalho MF, Corrêa FB, Baştürk MN, Fousekis E, Barbosa LMV, Plewka J, Probst AJ, Baldrian P, Stadler PF. MuDoGeR: multi-domain genome recovery from metagenomes made easy [Internet]. Molecular Ecology Resources. 2024 ; 24( 2): 1-12.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1111/1755-0998.13904
Vancouver
Rocha UN da, Kasmanas JC, Kallies R, Saraiva JP, Toscan RB, Štefanič P, Bicalho MF, Corrêa FB, Baştürk MN, Fousekis E, Barbosa LMV, Plewka J, Probst AJ, Baldrian P, Stadler PF. MuDoGeR: multi-domain genome recovery from metagenomes made easy [Internet]. Molecular Ecology Resources. 2024 ; 24( 2): 1-12.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1111/1755-0998.13904
Artigo de periodico
BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification (2024)
Santos, Anderson Paulo Avila ; Almeida, Breno Lívio Silva de ; Bonidia, Robson Parmezan ; Stadler, Peter F ; Štefanič, Polonca; Mandic-Mulec, Ines; Rocha, Ulisses Nunes da ; Sanches, Danilo Sipoli ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Fonte: RNA Biology. Unidades: ICMC, EESC E ICMC
Assuntos: BIOINFORMÁTICA, APRENDIZAGEM PROFUNDA, REDES NEURAIS, RNA, REGULAÇÃO GÊNICA, GENÔMICA
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ABNT
SANTOS, Anderson Paulo Avila et al. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification. RNA Biology, v. 21, n. 1, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1080/15476286.2024.2329451. Acesso em: 23 nov. 2025.
APA
Santos, A. P. A., Almeida, B. L. S. de, Bonidia, R. P., Stadler, P. F., Štefanič, P., Mandic-Mulec, I., et al. (2024). BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification. RNA Biology, 21( 1), 1-12. doi:10.1080/15476286.2024.2329451
NLM
Santos APA, Almeida BLS de, Bonidia RP, Stadler PF, Štefanič P, Mandic-Mulec I, Rocha UN da, Sanches DS, Carvalho ACP de LF de. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification [Internet]. RNA Biology. 2024 ; 21( 1): 1-12.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1080/15476286.2024.2329451
Vancouver
Santos APA, Almeida BLS de, Bonidia RP, Stadler PF, Štefanič P, Mandic-Mulec I, Rocha UN da, Sanches DS, Carvalho ACP de LF de. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification [Internet]. RNA Biology. 2024 ; 21( 1): 1-12.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1080/15476286.2024.2329451
Artigo de periodico
The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review (2024)
Silva-Sousa, Thayna; Usuda, Julia Nakanishi ; Al-Arawe, Nada ; Frias, Francisca; Hinterseher, Irene ; Catar, Rusan ; Luecht, Christian; Riesner, Katarina ; Hackel, Alexander; Schimke, Lena Friederike ; Dias, Haroldo Dutra ; Filgueiras, Igor Salerno ; Fischer, Stefan; Riemekasten, Gabriela ; Ringdén, Olle ; Penack, Olaf ; Winkler, Tobias; Duda, Georg ; Moll, Guido ; Aakaya, Helder Takashi Imoto ; Fonseca, Dennyson Leandro Mathias da ; Cabral-Marques, Otávio ; Camara, Niels Olsen Saraiva
Fonte: Stem Cells. Unidades: FCF, ICB, FM
Assuntos: IMUNOLOGIA, BIOINFORMÁTICA, INTELIGÊNCIA ARTIFICIAL, CÉLULAS-TRONCO
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ABNT
SILVA-SOUSA, Thayna et al. The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review. Stem Cells, v. 42, n. 11, p. 929-944, 2024Tradução . . Disponível em: https://doi.org/10.1093/stmcls/sxae054. Acesso em: 23 nov. 2025.
APA
Silva-Sousa, T., Usuda, J. N., Al-Arawe, N., Frias, F., Hinterseher, I., Catar, R., et al. (2024). The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review. Stem Cells, 42( 11), 929-944. doi:10.1093/stmcls/sxae054
NLM
Silva-Sousa T, Usuda JN, Al-Arawe N, Frias F, Hinterseher I, Catar R, Luecht C, Riesner K, Hackel A, Schimke LF, Dias HD, Filgueiras IS, Fischer S, Riemekasten G, Ringdén O, Penack O, Winkler T, Duda G, Moll G, Aakaya HTI, Fonseca DLM da, Cabral-Marques O, Camara NOS. The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review [Internet]. Stem Cells. 2024 ; 42( 11): 929-944.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/stmcls/sxae054
Vancouver
Silva-Sousa T, Usuda JN, Al-Arawe N, Frias F, Hinterseher I, Catar R, Luecht C, Riesner K, Hackel A, Schimke LF, Dias HD, Filgueiras IS, Fischer S, Riemekasten G, Ringdén O, Penack O, Winkler T, Duda G, Moll G, Aakaya HTI, Fonseca DLM da, Cabral-Marques O, Camara NOS. The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review [Internet]. Stem Cells. 2024 ; 42( 11): 929-944.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/stmcls/sxae054
Artigo de periodico
The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes (2023)
Santos, Anderson Paulo Avila ; Nata'ala, Muhammad Kabiru ; Kasmanas, Jonas Coelho ; Bartholomäus, Alexander ; Keller-Costa, Tina ; Jurburg, Stephanie D ; Tal, Tamara ; Camarinha-Silva, Amélia ; Saraiva, João Pedro ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Stadler, Peter F ; Sanches, Danilo Sipoli ; Rocha, Ulisses Nunes da
Fonte: Animal Microbiome. Unidade: ICMC
Assuntos: BIOINFORMÁTICA, GENÔMICA, ECOLOGIA MICROBIANA, METADADOS, BASES DE DADOS
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ABNT
SANTOS, Anderson Paulo Avila et al. The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes. Animal Microbiome, v. 5, p. 1-13, 2023Tradução . . Disponível em: https://doi.org/10.1186/s42523-023-00267-3. Acesso em: 23 nov. 2025.
APA
Santos, A. P. A., Nata'ala, M. K., Kasmanas, J. C., Bartholomäus, A., Keller-Costa, T., Jurburg, S. D., et al. (2023). The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes. Animal Microbiome, 5, 1-13. doi:10.1186/s42523-023-00267-3
NLM
Santos APA, Nata'ala MK, Kasmanas JC, Bartholomäus A, Keller-Costa T, Jurburg SD, Tal T, Camarinha-Silva A, Saraiva JP, Carvalho ACP de LF de, Stadler PF, Sanches DS, Rocha UN da. The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes [Internet]. Animal Microbiome. 2023 ; 5 1-13.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1186/s42523-023-00267-3
Vancouver
Santos APA, Nata'ala MK, Kasmanas JC, Bartholomäus A, Keller-Costa T, Jurburg SD, Tal T, Camarinha-Silva A, Saraiva JP, Carvalho ACP de LF de, Stadler PF, Sanches DS, Rocha UN da. The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes [Internet]. Animal Microbiome. 2023 ; 5 1-13.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1186/s42523-023-00267-3
Artigo de periodico
Information theory for biological sequence classification: a novel feature extraction technique based on Tsallis entropy (2022)
Bonidia, Robson Parmezan ; Santos, Anderson Paulo Avila ; Almeida, Breno Lívio Silva de ; Stadler, Peter F ; Rocha, Ulisses Nunes da ; Sanches, Danilo Sipoli ; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Entropy. Unidades: ICMC, EESC E ICMC
Assuntos: BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO, TEORIA DA INFORMAÇÃO
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ABNT
BONIDIA, Robson Parmezan et al. Information theory for biological sequence classification: a novel feature extraction technique based on Tsallis entropy. Entropy, v. 24, n. 10, p. 1-17, 2022Tradução . . Disponível em: https://doi.org/10.3390/e24101398. Acesso em: 23 nov. 2025.
APA
Bonidia, R. P., Santos, A. P. A., Almeida, B. L. S. de, Stadler, P. F., Rocha, U. N. da, Sanches, D. S., & Carvalho, A. C. P. de L. F. de. (2022). Information theory for biological sequence classification: a novel feature extraction technique based on Tsallis entropy. Entropy, 24( 10), 1-17. doi:10.3390/e24101398
NLM
Bonidia RP, Santos APA, Almeida BLS de, Stadler PF, Rocha UN da, Sanches DS, Carvalho ACP de LF de. Information theory for biological sequence classification: a novel feature extraction technique based on Tsallis entropy [Internet]. Entropy. 2022 ; 24( 10): 1-17.[citado 2025 nov. 23 ] Available from: https://doi.org/10.3390/e24101398
Vancouver
Bonidia RP, Santos APA, Almeida BLS de, Stadler PF, Rocha UN da, Sanches DS, Carvalho ACP de LF de. Information theory for biological sequence classification: a novel feature extraction technique based on Tsallis entropy [Internet]. Entropy. 2022 ; 24( 10): 1-17.[citado 2025 nov. 23 ] Available from: https://doi.org/10.3390/e24101398
Artigo de periodico
findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM (2022)
Chojnowski, Grzegorz ; Simpkin, Adam J.; Leonardo, Diego Antonio; Seifert-Davila, Wolfram ; Vivas-Ruiz, Dan E.; Keegan, Ronan M.; Rigden, Daniel J.
Fonte: IUCrJ. Unidade: IFSC
Assuntos: PROTEÍNAS, BIOINFORMÁTICA, REDES NEURAIS
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ABNT
CHOJNOWSKI, Grzegorz et al. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM. IUCrJ, v. 9, n. Ja 2022, p. 86-97, 2022Tradução . . Disponível em: https://doi.org/10.1107/S2052252521011088. Acesso em: 23 nov. 2025.
APA
Chojnowski, G., Simpkin, A. J., Leonardo, D. A., Seifert-Davila, W., Vivas-Ruiz, D. E., Keegan, R. M., & Rigden, D. J. (2022). findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM. IUCrJ, 9( Ja 2022), 86-97. doi:10.1107/S2052252521011088
NLM
Chojnowski G, Simpkin AJ, Leonardo DA, Seifert-Davila W, Vivas-Ruiz DE, Keegan RM, Rigden DJ. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM [Internet]. IUCrJ. 2022 ; 9( Ja 2022): 86-97.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1107/S2052252521011088
Vancouver
Chojnowski G, Simpkin AJ, Leonardo DA, Seifert-Davila W, Vivas-Ruiz DE, Keegan RM, Rigden DJ. findMySequence: a neural-network-based approach for identification of unknown proteins in X-ray crystallography and cryo-EM [Internet]. IUCrJ. 2022 ; 9( Ja 2022): 86-97.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1107/S2052252521011088
Artigo de periodico
MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes (2022)
Nata'ala, Muhammad Kabiru ; Santos, Anderson Paulo Avila ; Kasmanas, Jonas Coelho ; Bartholomäus, Alexander ; Saraiva, João Pedro ; Silva, Sandra Godinho ; Keller-Costa, Tina ; Costa, Rodrigo; Gomes, Newton Carlos Marcial ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Stadler, Peter F ; Sanches, Danilo Sipoli ; Rocha, Ulisses Nunes da
Fonte: Environmental Microbiome. Unidade: ICMC
Assuntos: BIOINFORMÁTICA, GENÔMICA, METADADOS, BANCO DE DADOS, ECOLOGIA MICROBIANA
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NATA'ALA, Muhammad Kabiru et al. MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes. Environmental Microbiome, v. 17, p. 1-10, 2022Tradução . . Disponível em: https://doi.org/10.1186/s40793-022-00449-7. Acesso em: 23 nov. 2025.
APA
Nata'ala, M. K., Santos, A. P. A., Kasmanas, J. C., Bartholomäus, A., Saraiva, J. P., Silva, S. G., et al. (2022). MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes. Environmental Microbiome, 17, 1-10. doi:10.1186/s40793-022-00449-7
NLM
Nata'ala MK, Santos APA, Kasmanas JC, Bartholomäus A, Saraiva JP, Silva SG, Keller-Costa T, Costa R, Gomes NCM, Carvalho ACP de LF de, Stadler PF, Sanches DS, Rocha UN da. MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes [Internet]. Environmental Microbiome. 2022 ; 17 1-10.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1186/s40793-022-00449-7
Vancouver
Nata'ala MK, Santos APA, Kasmanas JC, Bartholomäus A, Saraiva JP, Silva SG, Keller-Costa T, Costa R, Gomes NCM, Carvalho ACP de LF de, Stadler PF, Sanches DS, Rocha UN da. MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes [Internet]. Environmental Microbiome. 2022 ; 17 1-10.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1186/s40793-022-00449-7
Artigo de periodico
BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria (2022)
Bonidia, Robson Parmezan ; Santos, Anderson Paulo Avila ; Almeida, Breno Lívio Silva de; Stadler, Peter F ; Rocha, Ulisses Nunes da ; Sanches, Danilo Sipoli ; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Briefings in Bioinformatics. Unidades: ICMC, EESC E ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO
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ABNT
BONIDIA, Robson Parmezan et al. BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria. Briefings in Bioinformatics, v. 23, n. 4, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.1093/bib/bbac218. Acesso em: 23 nov. 2025.
APA
Bonidia, R. P., Santos, A. P. A., Almeida, B. L. S. de, Stadler, P. F., Rocha, U. N. da, Sanches, D. S., & Carvalho, A. C. P. de L. F. de. (2022). BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria. Briefings in Bioinformatics, 23( 4), 1-13. doi:10.1093/bib/bbac218
NLM
Bonidia RP, Santos APA, Almeida BLS de, Stadler PF, Rocha UN da, Sanches DS, Carvalho ACP de LF de. BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria [Internet]. Briefings in Bioinformatics. 2022 ; 23( 4): 1-13.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/bib/bbac218
Vancouver
Bonidia RP, Santos APA, Almeida BLS de, Stadler PF, Rocha UN da, Sanches DS, Carvalho ACP de LF de. BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria [Internet]. Briefings in Bioinformatics. 2022 ; 23( 4): 1-13.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/bib/bbac218
Trabalho de evento-anais periodico
Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches (2021)
Almeida, Breno Lívio Silva de; Queiroz, Alvaro Pedroso; Santos, Anderson Paulo Avila ; Bonidia, Robson Parmezan ; Rocha, Ulisses Nunes da ; Sanches, Danilo Sipoli ; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Lecture Notes in Bioinformatics. Nome do evento: Brazilian Symposium on Bioinformatics - BSB. Unidades: ICMC, EESC E ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA
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ABNT
ALMEIDA, Breno Lívio Silva de et al. Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches. Lecture Notes in Bioinformatics. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91814-9_8. Acesso em: 23 nov. 2025. , 2021
APA
Almeida, B. L. S. de, Queiroz, A. P., Santos, A. P. A., Bonidia, R. P., Rocha, U. N. da, Sanches, D. S., & Carvalho, A. C. P. de L. F. de. (2021). Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches. Lecture Notes in Bioinformatics. Cham: Springer. doi:10.1007/978-3-030-91814-9_8
NLM
Almeida BLS de, Queiroz AP, Santos APA, Bonidia RP, Rocha UN da, Sanches DS, Carvalho ACP de LF de. Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches [Internet]. Lecture Notes in Bioinformatics. 2021 ; 13063 81-92.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1007/978-3-030-91814-9_8
Vancouver
Almeida BLS de, Queiroz AP, Santos APA, Bonidia RP, Rocha UN da, Sanches DS, Carvalho ACP de LF de. Feature importance analysis of non-coding DNA/RNA sequences based on machine learning approaches [Internet]. Lecture Notes in Bioinformatics. 2021 ; 13063 81-92.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1007/978-3-030-91814-9_8
Artigo de periodico
A community resource for paired genomic and metabolomic data mining (2021)
Schorn, Michelle A. ; Verhoeven, Stefan ; Ridder, Lars ; Huber, Florian ; Acharya, Deepa D. A ; Aksenov, Alexander A. ; Aleti, Gajender ; Moghaddam, Jamshid Amiri ; Aron, Allegra T. ; Aziz, Saefuddin ; Bauermeister, Anelize ; Bauman, Katherine D. ; Baunach, Martin ; Beemelmanns, Christine ; Beman, J. Michael ; Clavero, María Victoria Berlanga ; Blacutt, Alex A. ; Bode, Helge B. ; Boullie, Anne; Brejnrod, Asker ; Bugni, Tim S. ; Calteau, Alexandra ; Cao, Liu ; Carrión, Víctor J. ; Branco, Raquel Castelo ; Chanana, Shaurya ; Chase, Alexander B. ; Chevrette, Marc G. ; Costa-Lotufo, Letícia Veras ; Crawford, Jason M. ; Currie, Cameron R. ; Cuypers, Bart ; Dang, Tam ; Rond, Tristan de ; Demko, Alyssa M. ; Dittmann, Elke ; Du, Chao ; Drozd, Christopher ; Dujardin, Jean-Claude ; Dutton, Rachel J. ; Edlund, Ann; Fewer, David P. ; Garg, Neha; Gauglitz, Julia M. ; Gentry, Emily C.; Gerwick, Lena ; Glukhov, Evgenia ; Gross, Harald ; Gugger, Muriel ; Matus, Dulce G. Guillén ; Helfrich, Eric J. N. ; Hempel, Benjamin-Florian ; Hur, Jae-Seoun ; Iorio, Marianna ; Jensen, Paul R. ; Kang, Kyo Bin ; Kaysser, Leonard ; Kelleher, Neil L ; Kim, Chung Sub ; Kim, Ki Hyun ; Koester, Irina ; König, Gabriele M. ; Leao, Tiago ; Lee, Seoung Rak ; Lee, Yi-Yuan ; Li, Xuanji ; Little, Jessica C.; Maloney,Katherine N. ; Männle, Daniel ; H., Christian Martin ; McAvoy, Andrew C. ; Metcalf, Willam W ; Mohimani, Hosein ; Santiago, Carlos Molina ; Moore, Bradley S. ; Mullowney, Michael W. ; Muskat, Mitchell ; Nothias, Louis Félix ; O’Neill, Ellis C.; Parkinson, Elizabeth I. ; Petras, Daniel ; Piel, Jörn ; Pierce, Emily C. ; Pires, Karine ; Reher, Raphael ; Romero, Diego ; Roper, M. Caroline; Rust, Michael ; Saad, Hamada ; Saenz, Carmen ; Sanchez, Laura M. ; Sørensen, Søren Johann ; Sosio, Margherita ; Süssmuth, Roderich D. ; Sweeney, Douglas; Tahlan, Kapil ; Thomson, Regan J. ; Tobias, Nicholas J. ; Silva, Amaro Emiliano Trindade ; Wezel, Gilles P. van ; Wang, Mingxun ; Weldon, Kelly C. ; Zhang, Fan ; Ziemert, Nadine ; Duncan, Katherine R. ; Crüsemann, Max ; Rogers, Simon ; Dorrestein, Pieter C. ; Medema, Marnix H. ; Hooft, Justin J. J. van der
Fonte: Nature Chemical Biology. Unidade: ICB
Assuntos: FARMACOLOGIA, BASES DE DADOS, GENÔMICA, BIOINFORMÁTICA, DNA, METABOLÔMICA
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ABNT
SCHORN, Michelle A. et al. A community resource for paired genomic and metabolomic data mining. Nature Chemical Biology, p. 8 , 2021Tradução . . Disponível em: https://doi.org/10.1038/s41589-020-00724-z. Acesso em: 23 nov. 2025.
APA
Schorn, M. A., Verhoeven, S., Ridder, L., Huber, F., Acharya, D. D. A., Aksenov, A. A., et al. (2021). A community resource for paired genomic and metabolomic data mining. Nature Chemical Biology, 8 . doi:10.1038/s41589-020-00724-z
NLM
Schorn MA, Verhoeven S, Ridder L, Huber F, Acharya DDA, Aksenov AA, Aleti G, Moghaddam JA, Aron AT, Aziz S, Bauermeister A, Bauman KD, Baunach M, Beemelmanns C, Beman JM, Clavero MVB, Blacutt AA, Bode HB, Boullie A, Brejnrod A, Bugni TS, Calteau A, Cao L, Carrión VJ, Branco RC, Chanana S, Chase AB, Chevrette MG, Costa-Lotufo LV, Crawford JM, Currie CR, Cuypers B, Dang T, Rond T de, Demko AM, Dittmann E, Du C, Drozd C, Dujardin J-C, Dutton RJ, Edlund A, Fewer DP, Garg N, Gauglitz JM, Gentry EC, Gerwick L, Glukhov E, Gross H, Gugger M, Matus DGG, Helfrich EJN, Hempel B-F, Hur J-S, Iorio M, Jensen PR, Kang KB, Kaysser L, Kelleher NL, Kim CS, Kim KH, Koester I, König GM, Leao T, Lee SR, Lee Y-Y, Li X, Little JC, Maloney KN, Männle D, H. CM, McAvoy AC, Metcalf WW, Mohimani H, Santiago CM, Moore BS, Mullowney MW, Muskat M, Nothias LF, O’Neill EC, Parkinson EI, Petras D, Piel J, Pierce EC, Pires K, Reher R, Romero D, Roper MC, Rust M, Saad H, Saenz C, Sanchez LM, Sørensen SJ, Sosio M, Süssmuth RD, Sweeney D, Tahlan K, Thomson RJ, Tobias NJ, Silva AET, Wezel GP van, Wang M, Weldon KC, Zhang F, Ziemert N, Duncan KR, Crüsemann M, Rogers S, Dorrestein PC, Medema MH, Hooft JJJ van der. A community resource for paired genomic and metabolomic data mining [Internet]. Nature Chemical Biology. 2021 ;8 .[citado 2025 nov. 23 ] Available from: https://doi.org/10.1038/s41589-020-00724-z
Vancouver
Schorn MA, Verhoeven S, Ridder L, Huber F, Acharya DDA, Aksenov AA, Aleti G, Moghaddam JA, Aron AT, Aziz S, Bauermeister A, Bauman KD, Baunach M, Beemelmanns C, Beman JM, Clavero MVB, Blacutt AA, Bode HB, Boullie A, Brejnrod A, Bugni TS, Calteau A, Cao L, Carrión VJ, Branco RC, Chanana S, Chase AB, Chevrette MG, Costa-Lotufo LV, Crawford JM, Currie CR, Cuypers B, Dang T, Rond T de, Demko AM, Dittmann E, Du C, Drozd C, Dujardin J-C, Dutton RJ, Edlund A, Fewer DP, Garg N, Gauglitz JM, Gentry EC, Gerwick L, Glukhov E, Gross H, Gugger M, Matus DGG, Helfrich EJN, Hempel B-F, Hur J-S, Iorio M, Jensen PR, Kang KB, Kaysser L, Kelleher NL, Kim CS, Kim KH, Koester I, König GM, Leao T, Lee SR, Lee Y-Y, Li X, Little JC, Maloney KN, Männle D, H. CM, McAvoy AC, Metcalf WW, Mohimani H, Santiago CM, Moore BS, Mullowney MW, Muskat M, Nothias LF, O’Neill EC, Parkinson EI, Petras D, Piel J, Pierce EC, Pires K, Reher R, Romero D, Roper MC, Rust M, Saad H, Saenz C, Sanchez LM, Sørensen SJ, Sosio M, Süssmuth RD, Sweeney D, Tahlan K, Thomson RJ, Tobias NJ, Silva AET, Wezel GP van, Wang M, Weldon KC, Zhang F, Ziemert N, Duncan KR, Crüsemann M, Rogers S, Dorrestein PC, Medema MH, Hooft JJJ van der. A community resource for paired genomic and metabolomic data mining [Internet]. Nature Chemical Biology. 2021 ;8 .[citado 2025 nov. 23 ] Available from: https://doi.org/10.1038/s41589-020-00724-z
Artigo de periodico
CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems (2021)
Alkhnbashi, Omer S ; Mitrofanov, Alexander; Bonidia, Robson Parmezan ; Raden, Martin ; Tran, Van Dinh ; Eggenhofer, Florian ; Shah, Shiraz A ; Ozturk, Ekrem; Padilha, Victor Alexandre ; Sanches, Danilo Sipoli ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Backofen, Rolf
Fonte: Nucleic Acids Research. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, GENES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALKHNBASHI, Omer S et al. CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems. Nucleic Acids Research, v. 49, p. w125-w130, 2021Tradução . . Disponível em: https://doi.org/10.1093/nar/gkab456. Acesso em: 23 nov. 2025.
APA
Alkhnbashi, O. S., Mitrofanov, A., Bonidia, R. P., Raden, M., Tran, V. D., Eggenhofer, F., et al. (2021). CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems. Nucleic Acids Research, 49, w125-w130. doi:10.1093/nar/gkab456
NLM
Alkhnbashi OS, Mitrofanov A, Bonidia RP, Raden M, Tran VD, Eggenhofer F, Shah SA, Ozturk E, Padilha VA, Sanches DS, Carvalho ACP de LF de, Backofen R. CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems [Internet]. Nucleic Acids Research. 2021 ; 49 w125-w130.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/nar/gkab456
Vancouver
Alkhnbashi OS, Mitrofanov A, Bonidia RP, Raden M, Tran VD, Eggenhofer F, Shah SA, Ozturk E, Padilha VA, Sanches DS, Carvalho ACP de LF de, Backofen R. CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas systems [Internet]. Nucleic Acids Research. 2021 ; 49 w125-w130.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/nar/gkab456
Artigo de periodico
Casboundary: automated definition of integral Cas cassettes (2021)
Padilha, Victor Alexandre ; Alkhnbashi, Omer S ; Tran, Van Dinh ; Shah, Shiraz A ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Backofen, Rolf
Fonte: Bioinformatics. Unidade: ICMC
Assuntos: BIOINFORMÁTICA, APRENDIZADO COMPUTACIONAL, GENES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PADILHA, Victor Alexandre et al. Casboundary: automated definition of integral Cas cassettes. Bioinformatics, v. 37, n. 10, p. 1352-1359, 2021Tradução . . Disponível em: https://doi.org/10.1093/bioinformatics/btaa984. Acesso em: 23 nov. 2025.
APA
Padilha, V. A., Alkhnbashi, O. S., Tran, V. D., Shah, S. A., Carvalho, A. C. P. de L. F. de, & Backofen, R. (2021). Casboundary: automated definition of integral Cas cassettes. Bioinformatics, 37( 10), 1352-1359. doi:10.1093/bioinformatics/btaa984
NLM
Padilha VA, Alkhnbashi OS, Tran VD, Shah SA, Carvalho ACP de LF de, Backofen R. Casboundary: automated definition of integral Cas cassettes [Internet]. Bioinformatics. 2021 ; 37( 10): 1352-1359.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/bioinformatics/btaa984
Vancouver
Padilha VA, Alkhnbashi OS, Tran VD, Shah SA, Carvalho ACP de LF de, Backofen R. Casboundary: automated definition of integral Cas cassettes [Internet]. Bioinformatics. 2021 ; 37( 10): 1352-1359.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/bioinformatics/btaa984
Parte de monografia/livro
Rational design of profile hidden Markov models for viral classification and discovery (2021)
Oliveira, Liliane Santana; Gruber, Arthur
Fonte: Bioinformatics [Internet]. Unidade: ICB
Assuntos: PARASITOLOGIA, VIROLOGIA MOLECULAR, MODELOS ANIMAIS DE DOENÇAS, VÍRUS, BIOINFORMÁTICA, DIVERSIDADE GENÉTICA, SEQUENCIAMENTO GENÉTICO, MUTAÇÃO GENÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Liliane Santana e GRUBER, Arthur. Rational design of profile hidden Markov models for viral classification and discovery. Bioinformatics [Internet]. Tradução . Brisbane: Exon Publication, 2021. p. ca 9. Disponível em: https://doi.org/10.36255/exonpublications.bioinformatics.2021.ch9. Acesso em: 23 nov. 2025.
APA
Oliveira, L. S., & Gruber, A. (2021). Rational design of profile hidden Markov models for viral classification and discovery. In Bioinformatics [Internet] (p. ca 9). Brisbane: Exon Publication. doi:10.36255/exonpublications.bioinformatics.2021.ch9
NLM
Oliveira LS, Gruber A. Rational design of profile hidden Markov models for viral classification and discovery [Internet]. In: Bioinformatics [Internet]. Brisbane: Exon Publication; 2021. p. ca 9.[citado 2025 nov. 23 ] Available from: https://doi.org/10.36255/exonpublications.bioinformatics.2021.ch9
Vancouver
Oliveira LS, Gruber A. Rational design of profile hidden Markov models for viral classification and discovery [Internet]. In: Bioinformatics [Internet]. Brisbane: Exon Publication; 2021. p. ca 9.[citado 2025 nov. 23 ] Available from: https://doi.org/10.36255/exonpublications.bioinformatics.2021.ch9
Artigo de periodico-carta/editorial
4th ISCB Latin American Student Council Symposium. [Editorial]: a virtual and inclusive experience during COVID-19 times (2020)
Castillo-Vilcahuaman, Camila; Valdivia, Catalina; Osorio-Mogollón, Cleidy; Silva-Andrade, Claudia; Puche-Quiñonez, Rafael; Ayala-Ruano, Sebastián; Cuesta-Astroz, Yesid; Parra, R. Gonzalo
Fonte: F1000Research. Unidade: FMRP
Assuntos: COVID-19, BIOINFORMÁTICA, PANDEMIAS, EVENTOS, ESTUDANTES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASTILLO-VILCAHUAMAN, Camila et al. 4th ISCB Latin American Student Council Symposium. [Editorial]: a virtual and inclusive experience during COVID-19 times. F1000Research. London: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.12688/f1000research.28330.1. Acesso em: 23 nov. 2025. , 2020
APA
Castillo-Vilcahuaman, C., Valdivia, C., Osorio-Mogollón, C., Silva-Andrade, C., Puche-Quiñonez, R., Ayala-Ruano, S., et al. (2020). 4th ISCB Latin American Student Council Symposium. [Editorial]: a virtual and inclusive experience during COVID-19 times. F1000Research. London: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.12688/f1000research.28330.1
NLM
Castillo-Vilcahuaman C, Valdivia C, Osorio-Mogollón C, Silva-Andrade C, Puche-Quiñonez R, Ayala-Ruano S, Cuesta-Astroz Y, Parra RG. 4th ISCB Latin American Student Council Symposium. [Editorial]: a virtual and inclusive experience during COVID-19 times [Internet]. F1000Research. 2020 ;[citado 2025 nov. 23 ] Available from: https://doi.org/10.12688/f1000research.28330.1
Vancouver
Castillo-Vilcahuaman C, Valdivia C, Osorio-Mogollón C, Silva-Andrade C, Puche-Quiñonez R, Ayala-Ruano S, Cuesta-Astroz Y, Parra RG. 4th ISCB Latin American Student Council Symposium. [Editorial]: a virtual and inclusive experience during COVID-19 times [Internet]. F1000Research. 2020 ;[citado 2025 nov. 23 ] Available from: https://doi.org/10.12688/f1000research.28330.1
Artigo de periodico
CRISPRcasIdentifier: machine learning for accurate identification and classification of CRISPR-Cas systems (2020)
Padilha, Victor Alexandre ; Alkhnbashi, Omer S ; Shah, Shiraz A ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Backofen, Rolf
Fonte: GigaScience. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, GENES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PADILHA, Victor Alexandre et al. CRISPRcasIdentifier: machine learning for accurate identification and classification of CRISPR-Cas systems. GigaScience, v. 9, n. 6, p. 1-12, 2020Tradução . . Disponível em: https://doi.org/10.1093/gigascience/giaa062. Acesso em: 23 nov. 2025.
APA
Padilha, V. A., Alkhnbashi, O. S., Shah, S. A., Carvalho, A. C. P. de L. F. de, & Backofen, R. (2020). CRISPRcasIdentifier: machine learning for accurate identification and classification of CRISPR-Cas systems. GigaScience, 9( 6), 1-12. doi:10.1093/gigascience/giaa062
NLM
Padilha VA, Alkhnbashi OS, Shah SA, Carvalho ACP de LF de, Backofen R. CRISPRcasIdentifier: machine learning for accurate identification and classification of CRISPR-Cas systems [Internet]. GigaScience. 2020 ; 9( 6): 1-12.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/gigascience/giaa062
Vancouver
Padilha VA, Alkhnbashi OS, Shah SA, Carvalho ACP de LF de, Backofen R. CRISPRcasIdentifier: machine learning for accurate identification and classification of CRISPR-Cas systems [Internet]. GigaScience. 2020 ; 9( 6): 1-12.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1093/gigascience/giaa062
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
Fonte: Molecular Oncology. Unidade: IME
Assunto: BIOINFORMÁTICA
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ABNT
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: https://doi.org/10.1002/1878-0261.12501. Acesso em: 23 nov. 2025.
APA
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 2025 nov. 23 ] Available from: https://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 2025 nov. 23 ] Available from: https://doi.org/10.1002/1878-0261.12501
Artigo de periodico
In silico selection approach to develop DNA aptamers for a stem-like cell subpopulation of non-small lung cancer adenocarcinoma cell line A549 (2018)
Vidic, Mateja; Smuc, Tina; Blank, Michael; Michael Blank; Accetto, Tomaz; Mavri, Jan; Nascimento, Isis C; Nery, Arthur A; Ulrich, Henning ; Lah, Tamara T
Fonte: Radiology and Oncology. Unidade: IQ
Assuntos: ADENOCARCINOMA, CÉLULAS-TRONCO, NEOPLASIAS DO TRATO RESPIRATÓRIO, BIOINFORMÁTICA
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ABNT
VIDIC, Mateja et al. In silico selection approach to develop DNA aptamers for a stem-like cell subpopulation of non-small lung cancer adenocarcinoma cell line A549. Radiology and Oncology, v. 52, n. 2, p. 152-159, 2018Tradução . . Disponível em: https://doi.org/10.2478/raon-2018-0014. Acesso em: 23 nov. 2025.
APA
Vidic, M., Smuc, T., Blank, M., Michael Blank,, Accetto, T., Mavri, J., et al. (2018). In silico selection approach to develop DNA aptamers for a stem-like cell subpopulation of non-small lung cancer adenocarcinoma cell line A549. Radiology and Oncology, 52( 2), 152-159. doi:10.2478/raon-2018-0014
NLM
Vidic M, Smuc T, Blank M, Michael Blank, Accetto T, Mavri J, Nascimento IC, Nery AA, Ulrich H, Lah TT. In silico selection approach to develop DNA aptamers for a stem-like cell subpopulation of non-small lung cancer adenocarcinoma cell line A549 [Internet]. Radiology and Oncology. 2018 ; 52( 2): 152-159.[citado 2025 nov. 23 ] Available from: https://doi.org/10.2478/raon-2018-0014
Vancouver
Vidic M, Smuc T, Blank M, Michael Blank, Accetto T, Mavri J, Nascimento IC, Nery AA, Ulrich H, Lah TT. In silico selection approach to develop DNA aptamers for a stem-like cell subpopulation of non-small lung cancer adenocarcinoma cell line A549 [Internet]. Radiology and Oncology. 2018 ; 52( 2): 152-159.[citado 2025 nov. 23 ] Available from: https://doi.org/10.2478/raon-2018-0014
Artigo de periodico
Bioinformatics meets virology: the european virus Bioinformatics Center’s Second Annual Meeting (2018)
Ibrahim, Bashar; Arkhipova, Ksenia; Andeweg, Arno C.; Posada-Céspedes, Susana; Enault, François; Gruber, Arthur ; Koonin, Eugene V.; Kupczok, Anne; Lemey, Philippe; McHardy, Alice C.; McMahon, Dino P.; Pickett, Brett E.; Robertson, David L.; Scheuermann, Richard H.; Zhernakova, Alexandra; Zwart, Mark P.; Schönhuth, Alexander; Dutilh, Bas E.; Marz, Manja
Fonte: Viruses. Unidade: ICB
Assuntos: PARASITOLOGIA, BIOINFORMÁTICA, VÍRUS
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ABNT
IBRAHIM, Bashar et al. Bioinformatics meets virology: the european virus Bioinformatics Center’s Second Annual Meeting. Viruses, v. 10, n. 5, p. 1-19, 2018Tradução . . Disponível em: https://doi.org/10.3390/v10050256. Acesso em: 23 nov. 2025.
APA
Ibrahim, B., Arkhipova, K., Andeweg, A. C., Posada-Céspedes, S., Enault, F., Gruber, A., et al. (2018). Bioinformatics meets virology: the european virus Bioinformatics Center’s Second Annual Meeting. Viruses, 10( 5), 1-19. doi:10.3390/v10050256
NLM
Ibrahim B, Arkhipova K, Andeweg AC, Posada-Céspedes S, Enault F, Gruber A, Koonin EV, Kupczok A, Lemey P, McHardy AC, McMahon DP, Pickett BE, Robertson DL, Scheuermann RH, Zhernakova A, Zwart MP, Schönhuth A, Dutilh BE, Marz M. Bioinformatics meets virology: the european virus Bioinformatics Center’s Second Annual Meeting [Internet]. Viruses. 2018 ; 10( 5): 1-19.[citado 2025 nov. 23 ] Available from: https://doi.org/10.3390/v10050256
Vancouver
Ibrahim B, Arkhipova K, Andeweg AC, Posada-Céspedes S, Enault F, Gruber A, Koonin EV, Kupczok A, Lemey P, McHardy AC, McMahon DP, Pickett BE, Robertson DL, Scheuermann RH, Zhernakova A, Zwart MP, Schönhuth A, Dutilh BE, Marz M. Bioinformatics meets virology: the european virus Bioinformatics Center’s Second Annual Meeting [Internet]. Viruses. 2018 ; 10( 5): 1-19.[citado 2025 nov. 23 ] Available from: https://doi.org/10.3390/v10050256

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