Jonas Coelho Kasmanas
I am interested in the detection o novel bio-indicators for human dysbiosis based on metagenomic samples from the human microbial Big Data. As a way of identifying the patterns of interest from the microbial Big Data, my work starts with the collection of the human metagenomic samples, and the standardization of its metadata, from public repositories. Once with the relevant dataset, my research involves the development of novel bioinformatics pipelines for the recovery of metagenome-assembled genomes from the raw metagenomic samples. The identification of the bio-indicators is then made by meta-analysis and the creation of Machine Learning classification models optimized through the development of Automated Machine Learning pipelines.
- T. Brito-Sarracino, M. Rocha dos Santos, E. Freire Antunes, I. Batista de Andrade Santos, J. Coelho Kasmanas and A. C. Ponce de Leon Ferreira de Carvalho, "Explainable Machine Learning for Breast Cancer Diagnosis," 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), Salvador, Brazil, 2019, pp. 681-686, doi: 10.1109/BRACIS.2019.00124.