Ana Marta Fernandes Tavares Sequeira (4717-388D-203F)

Curriculum Vitae

Ana Marta Fernandes Tavares Sequeira

Ana Marta Fernandes Tavares Sequeira. Publicou 1 artigos em revistas especializadas. No seu currículo Ciência Vitae os termos mais frequentes na contextualização da produção científica, tecnológica e artístico-cultural são: Machine learning; Peptide classification; Viral fusion peptides; .

Identification

Personal identification

Full name: Ana Marta Fernandes Tavares Sequeira

Citation names

Sequeira, Ana Marta

Author identifiers

Ciência ID: 4717-388D-203F

Education

	Degree	Classification
2017/09/01 - 2019/11/18 Concluded	Bioinformática (Mestrado) Universidade do Minho, Portugal "Building an automated platform for the classification of peptides/proteins using machine learning" (THESIS/DISSERTATION)	18
2013/09/01 - 2017/06/30 Concluded	Biologia (Licenciatura) Universidade de Aveiro, Portugal "Increase of bacterial biosurfactant production by cocultivation with biofilm-forming bacteria" (THESIS/DISSERTATION)	18

Affiliation

Science

	Category Host institution	Employer
2020/03/16 - Current	Researcher (Research)	Universidade do Minho Centro de Engenharia Biológica, Portugal
	Universidade do Minho Centro de Engenharia Biológica, Portugal
2019/09/01 - 2020/03/15	Researcher (Research)	Universidade do Minho Centro de Engenharia Biológica, Portugal
	Universidade do Minho Centro de Engenharia Biológica, Portugal
2016/10/01 - 2017/06/01	Research Trainee (Research)	University College Cork APC Microbiome Institute, Ireland
	University College Cork APC Microbiome Institute, Ireland
2015/10/01 - 2016/06/30	Research Trainee (Research)	Universidade de Aveiro Centro de Estudos do Ambiente e do Mar, Portugal
	Universidade de Aveiro Centro de Estudos do Ambiente e do Mar, Portugal

Projects

Grant

	Designation	Funders
2019/09/15 - Current	DeepBIO - Deep and machine learning for biotechnology NORTE-01-0247-FEDER-039831 Research Fellow	Ongoing

Other

	Designation	Funders
2018/10/01 - Current	Combinando métodos computacionais e experimentais para obter uma caracterização genérica dos péptidos de fusão de vírus PTDC/CCI-BIO/28200/2017 Other

Outputs

Publications

Book chapter	Sequeira, Ana Marta; Lousa, Diana; Rocha, Miguel. "ProPythia: A Python Automated Platform for the Classification of Proteins Using Machine Learning". In Practical Applications of Computational Biology & Bioinformatics, 14th International Conference (PACBB 2020), 32-41. Springer International Publishing, 2020. 10.1007/978-3-030-54568-0_4
Conference paper	Pereira, Sara; Lousa, Diana; Rocha, Miguel. "ProPythia, an automated platform for the classification of peptides/proteins using machine learning". Paper presented in Bioinformatic open days, Braga, 2020.
Journal article	Morais, Livia H.; Golubeva, Anna V.; Moloney, Gerard M.; Moya-Pérez, Angela; Ventura-Silva, Ana Paula; Arboleya, Silvia; Bastiaanssen, Thomaz F.S.; et al. "Enduring Behavioral Effects Induced by Birth by Caesarean Section in the Mouse". Current Biology (2020): http://dx.doi.org/10.1016/j.cub.2020.07.044. 10.1016/j.cub.2020.07.044 Alves, A.R.; Sequeira, A.M.; Cunha, Â.. "Increase in bacterial biosurfactant production by co-cultivation with biofilm-forming bacteria". Letters in Applied Microbiology 69(1) (2019): 79-86. http://dx.doi.org/10.1111/lam.13169. Open access • Published • 10.1111/lam.13169
Thesis / Dissertation	Sequeira, Ana Marta. "Building an automated platform for the classification of peptides/proteins using machine learning". Master, Universidade Nova de Lisboa Instituto de Tecnologia Química e Biológica, 2019.

Activities

Oral presentation

	Presentation title	Event name Host (Event location)
2020/10/08	ProPythia: a python automated platform for the classification of proteins using machine learning	PACBB - 14th International Conference on Practical Applications of Computational Biology & Bioinformatics (L' Aquila, Italy)
2019/12/20	Building an automated platform for the classification of peptides/proteins using machine learning	Encontro de Jovens Investigadores de Biologia Computacional Estrutural - EJIBCE 2019 Faculdade de ciências da Universidade de Lisboa (Lisboa, Portugal)