Dr. João Pedro Saraiva
My primary research interest is in the field of complex microbial systems. The advancements in high throughput sequencing technologies has greatly increased our ability to generate genomic data. This exponential increase in microbial big data now demands the development of novel concepts and strategies to better characterize and study microbial community composition and microbial interactions.
Developing and implementing novel concepts focused on microbial communities is the overall goal of my research. How to generate models that use (meta)genomic data to answer questions related to complex microbial communities and interspecies interactions is the main driver of my research activities. Because natural microbial communities are highly complex, answering these questions require careful design and planning to reflect its true scenario. I also use machine learning approaches that allows for the discovery of patterns in microbial communities composition and interactions.
- Lian, S. et al. Biotransformation of hexachlorocyclohexanes contaminated biomass for energetic utilization demonstrated in continuous anaerobic digestion system. J. Hazard. Mater. 384, 121448 (2020).
- Edit list item Corrêa, F. B., Saraiva, J. P., Stadler, P. F. & da Rocha, U. N. (2020). TerrestrialMetagenomeDB: a public repository of curated and standardized metadata for terrestrial metagenomes. Nucleic Acids Research, 48(D1), D626-D632.
- Saraiva, J. et al. iDS372, a Phenotypically Reconciled Model for the Metabolism of Streptococcus pneumoniae Strain R6. Front. Microbiol. 10, 1283 (2019).
- Rosado, P. M. et al. Marine probiotics: increasing coral resistance to bleaching through microbiome manipulation. ISME J. 13, 921–936 (2019).
- Saraiva, J. & Koenig, R. Infection-specific human immune responses: fungi vs. bacteria. in INFECTION 43, S10–S10 (SPRINGER HEIDELBERG TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY, 2015).
- Leonor Fernandes Saraiva J. P., Zubiria-Barrera C., Klassert T. E., Lautenbach M. J. Blaess, M., Claus R. A., König R. (2017). Combination of Classifiers Identifies Fungal-Specific Activation of Lysosome Genes in Human Monocytes. Frontiers in Microbiology, 8, 2366
- Saraiva JP, Oswald M, Biering A, Röll D, Assmann C, Klassert T, Blaess M, Czakai K, Claus R, Löffler J, Slevogt H, König R. (2017) Fungal biomarker discovery by integration of classifiers. BMC Genomics 18, 601.
- Saraiva J, Oswald M, Biering A, Assmann C, Klassert T, Blaess M, Czakai K, Claus R, Löffler J, Slevogt H, König R (2016) Integrating classifiers across datasets improves consistency of biomarker predictions in sepsis. In: Proceedings of the 6th IFAC Conference on Foundations of Systems Biology in Engineering, Magdeburg, 10/09/2016-10/12/2016, pp. 95-102.Elsevier ScienceDirect.