SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Luiz Eduardo D. Paiva(ledp@iq.ufrj.br)
2 Guy M. B. Junior(guyjunior@iq.ufrj.br)
3 Giseli Lopes(giseli@ic.ufrj.br)
4 Jorge Zavaleta(zavaleta.jorge@gmail.com,)
5 SERGIO MANUEL SERRA CRUZ(sergioserra@gmail.com)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Allain, F. pymsfilereader: Thermo MSFileReader Python bindings. [S. l.]: GitHub, 2019. Disponível em: https://github.com/frallain/pymsfilereader. Acesso em: 4 abr. 2026.
2 Bi, R. et al. Database of Chemicals for Organophosphorus (DCOP): An Information Application Platform for Organophosphorus Compounds. Analytical Chemistry, 2026. DOI: 10.1021/acs.analchem.5c06885.
3 Chambers, M. C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nature Biotechnology, v. 30, n. 10, p. 918-920, 2012. DOI: 10.1038/nbt.2377.
4 Heinsvig, P. J. et al. Forensic drug screening by liquid chromatography hyphenated with high-resolution mass spectrometry (LC-HRMS). TrAC Trends in Analytical Chemistry, v. 162, p. 117023, 2023. DOI: 10.1016/j.trac.2023.117023.
5 Magalhães Britto Junior, G. et al. Aplicando Lógica Fuzzy na Interpretação de Grandes Volumes de Dados Cromatográficos no Controle de Dopagem. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 18., 2024, Florianópolis/SC. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2024. p. 24-31. DOI: 10.5753/bresci.2024.244261.
6 Mardal, M. et al. Scalable Analysis of Untargeted LC-HRMS Data by Means of SQL Database Archiving. Analytical Chemistry, v. 95, n. 10, p. 4592-4596, 2023. DOI: 10.1021/acs.analchem.2c03769.
7 Mattoso, M. et al. Towards supporting the life cycle of large scale scientific experiments. International Journal of Business Process Integration and Management, v. 5, n. 1, p. 79-92, 2010. DOI: 10.1504/IJBPIM.2010.033176.
8 Milman, B. L.; Zhurkovich, I. K. The chemical space for non-target analysis. TrAC Trends in Analytical Chemistry, v. 97, p. 179-187, 2017. DOI: 10.1016/j.trac.2017.09.013.
9 Miloslavskaya, N.; Tolstoy, A. Big Data, Fast Data and Data Lake Concepts. Procedia Computer Science, v. 88, p. 300-305, 2016. DOI: 10.1016/j.procs.2016.07.439.
10 Mogollón, N. G. S. et al. O estado da arte da cromatografia líquida bidimensional: conceitos fundamentais, instrumentação e aplicações. Química Nova, v. 37, n. 10, p. 1680-1691, 2014. DOI: 10.5935/0100-4042.20140261.
11 Pasternak, Z. et al. Automatic detection and classification of ignitable liquids from GC-MS data of casework samples in forensic fire-debris analysis. Forensic Chemistry, v. 29, p. 100419, 2022. DOI: 10.1016/j.forc.2022.100419.
12 Schymanski, E. L. et al. Strategies to characterize polar organic contamination in wastewater: exploring the capability of high resolution mass spectrometry. Environmental Science & Technology, v. 48, n. 3, p. 1811-1818, 2014. DOI: 10.1021/es4044374.
13 Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, v. 3, p. 160018, 2016. DOI: 10.1038/sdata.2016.18.
14 Yao, Y. et al. Analysis of Metabolomics Datasets with High-Performance Computing and Metabolite Atlases. Metabolites, v. 5, n. 3, p. 431-442, 2015. DOI: 10.3390/metabo5030431.