Partnership
The SBCB is a member of the Brazilian National Institute of Ancestry and Genomics
Services - Bioinformatics Analysis, Consulting and Training
We offer bioinformatics and machine-learning data analysis, consulting and training services.
Paper - Biological Sciences: Multi-Omics
Multi-omics integration for neurodevelopmental, neurodegenerative and psychiatric disorders
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Paper - Biological Sciences: Genomic Data Analysis
Genetic insights into the peoples who shaped the American continent
Paper - Computer Science: Data Science
Exploring data visualization techniques in molecular dynamics
Paper - Data Science for Biotechnology Applications
Shaping soil fungal communities: How swine waste treatment systems and geography drive fungal community shifts
Project - MapStroke: a Computational Strategy to Improve Access to Acute Stroke Care
This project aims to use computational strategies to identify optimal locations for new Acute Stroke Centers (ASCs), improving access to treatment.
Paper - Computer Science: Heuristic Search Methods
The MAPSTROKE analysis of the access to stroke reperfusion treatment and stroke units in Italy
Paper - Computer Science: Heuristic Search Methods
Expanding acute stroke care coverage in resource-limited settings: A multi-objective approach based on facility location problems and NSGA-II
Project - Computational Fluid Dynamics and Machine Learning for Sustainable Engineering
In the realm of sustainable engineering, accurately simulating fluid dynamics presents numerous challenges due to their complex and nonlinear nature.
Paper - Biological Sciences: Transcriptomics Data Analysis
Deep learning methods and applications in single-cell multimodal data integration
Partnership
The SBCBLab is a member of the National Institute of Forensic Science and Technology
Project - Data Science for Biotechnology Applications
This project develops bioinformatics tools using Machine Learning, heuristic search, and high-performance computing for human and animal health.
Paper - Biological Sciences: Structural Bioinformatics
Assessment of Kaistella jeonii Esterase Conformational Dynamics in Response to Poly(ethylene terephthalate) Binding
Project - Machine Learning - Biomarkers of Cardiovascular Response
Applying ML in the Identification and Validation of Biomarkers of Treatment Response and Cardiovascular Metabolism in Major Depressive Disorder
Paper - Biological Sciences: Structural Bioinformatics
Alpha-amylase Evolution, Structure, and Potential Biotechnological Applications for the Bioremediation of n-alkanes
Paper - Biological Sciences: Metagenomic Data Analysis
Interdisciplinary Overview of Lipopeptide and Protein-Containing Biosurfactants
Paper - Computer Science: Machine Learning
Analysis and comparison of feature selection methods towards performance and stability
Paper - Computer Science: Machine Learning
Relevance aggregation for neural networks interpretability and knowledge discovery on tabular data
Paper - Biological Sciences: Transcriptomics Data Analysis
Transcriptomic Analysis of Long Non-Coding RNA during Candida albicans Infection
Paper - Biological Sciences: Transcriptomics Data Analysis
Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types
We turn biological questions into computational answers
The SBCB Lab (Structural Bioinformatics and Computational Biology Laboratory, Center for Biotechnology / Institute of Informatics, UFRGS) develops algorithms and software for biological data analysis and applies them to problems in health, agriculture and the environment.
On the computational side, we work on heuristic search and optimization, machine learning, high-performance and GPU computing, and data science. On the biological side, we build and customize pipelines for genomics, transcriptomics, metagenomics and microbiome studies, and structural bioinformatics, with applications in medical, environmental, animal, microbial and plant biotechnology.
SBCB - Research Computing Facility
The SBCB Lab maintains a research computing facility (CPU cluster, GPU servers and storage) used by lab members and collaborators, and is registered in the MCTI National Research Infrastructure Platform (PNIPE). Full hardware specifications are listed under Facilities.
Join our team!
The SBCB Lab welcomes prospective Master's and Ph.D. students in Computer Science or in Cell and Molecular Biology.
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A background in Computer Science, Bioinformatics, or Molecular Biology
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Good scientific writing and documentation skills
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Motivation, attention to detail, and interest in interdisciplinary research
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Interdisciplinary research at the interface of computing and the life sciences
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Supervision on developing new methods and software for bioinformatics problems
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Access to the lab's computing infrastructure; scholarships may be available
- Programs
- Postgraduate Program in Computing (PPGC) Master's or Ph.D. in Computer Science
- Postgraduate Program in Molecular and Cell Biology (PPGBCM) Master's or Ph.D. in Cell and Molecular Biology
To apply, email Prof. Márcio Dorn (mdorn@inf.ufrgs.br) with a short introduction covering your academic background, research interests and career goals.
Tools and Datasets
The SBCB Lab makes its software and curated datasets freely available, in line with open-science and FAIR principles (Findable, Accessible, Interoperable, Reusable). Each resource below links to its documentation, source code or download, and the publication to cite.
International Cooperation
The SBCB Lab collaborates with research groups in Germany, France, Chile and Canada through joint projects: PROBRAL and CFDSustain with the Karlsruhe Institute of Technology (Germany), AiCaBi (STIC-AmSud) with partners in Chile and France, and ML-BCR with McMaster University (Canada). These projects support researcher exchanges, joint workshops and co-authored publications.
