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.
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.
Partnership
The SBCB is a member of the Brazilian National Institute of Ancestry and Genomics
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 convert biological questions into answers
The SBCB Lab has a robust history of research in bioinformatics, evidenced by numerous publications in the field. These contributions include the development of novel algorithms and the application of gold-standard techniques for analyzing biological data. The laboratory specializes in creating new tools and customizing pipelines for genomics, transcriptomics, metagenomics, proteomics, structural bioinformatics, and multiomics analysis.
In the realm of Computer Science, the lab focuses on designing innovative techniques rooted in artificial intelligence, machine learning, heuristic search methods, and massively parallel processing to address diverse challenges in biological data processing.
Within Biological Sciences, the lab conducts research projects spanning several biotechnological domains: medical biotechnology, environmental biotechnology, animal biotechnology, microbial biotechnology, and plant biotechnology.
Tools and Datasets
Science is evolving into a new paradigm characterized by heightened transparency and accessibility. This shift extends beyond the sharing of raw data to include publications, software code, and research methodologies, fostering a more open and collaborative scientific ecosystem.
In recent years, the SBCB Lab has developed numerous tools, libraries, and datasets to advance collaboration and improve accessibility within the scientific community. Our commitment to providing free access to these resources underscores our belief in democratizing scientific participation, ensuring researchers from all backgrounds can contribute equitably to global progress. Below are some of the key tools and datasets we have developed:
SBCB - Research Computing Facility
The Structural Bioinformatics and Computational Biology Laboratory provides researchers and students involved with the lab access to state-of-the-art computational resources to accelerate scientific discovery. The SBCB Lab is a member of the National Research Infrastructure Platform MCTI. Further information about accessing these services can be found on the Laboratory Services page.
Detailed specifications of the available computing resources are available here.
Join our team!
SBCBLab is actively seeking talented Master's and Ph.D. Candidates in Computer Science or Cell and Molecular Biology.
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A strong academic background in Computer Science or Bioinformatics
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Excellent writing and documentation skills
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A high degree of motivation, attention to detail, and passion for science
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An opportunity to engage in cutting-edge, interdisciplinary research
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A focus on developing innovative methods and computational strategies for Bioinformatics problems
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Potential scholarships and state-of-the-art infrastructure to develop your research.
- Programs
- Postgraduate Program in Computing (PPGC) For those aiming for a Master's or Ph.D. in Computer Science
- Postgraduate Program in Molecular and Cell Biology (PPGBCM) For those aiming for a Master's or Ph.D. in Molecular and Cell Biology
Please email Prof. Dorn (mdorn@inf.ufrgs.br) with a brief introduction about your academic background, research interests, and career goals.
International Cooperation
Cooperation serves as a vital conduit for staying attuned to the latest scientific trends, breakthroughs, and applications, ensuring our continued relevance and effectiveness in addressing contemporary challenges. At SBCBLab, we recognize collaboration’s indispensable role in driving innovation and fostering the cross-pollination of ideas.
Our participation in multiple international cooperative projects underscores our commitment to leveraging collective intelligence on a global scale. Through these initiatives, we strive to cultivate a cohort of highly skilled, adaptable professionals equipped to navigate the complexities of modern research and innovation. These researchers—armed with diverse expertise and a global perspective—are poised not only to advance academic knowledge but also to translate discoveries into tangible solutions with real-world impact, bridging academia and industry.
Key international partners of the lab include institutions in Germany, Chile, and France.
