• Protect yourself.

    Protect others.

    Wear a

  • New Paper

    Relevance aggregation for neural networks interpretability and knowledge discovery on tabular data

  • Research

    The use of artificial intelligence, particularly machine learning, creates new opportunities for analyzing large volumes of biological data

  • Research

    Identification of targets of interest derived from large-scale biological data, interaction networks between different types of molecules, molecular mechanisms and much more

  • Partnership

    The SBCBLab is a member of the 
    National Institute of Forensic Science and Technology

  • New Paper

    Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types

  • New Paper

    The Tale of a Versatile Enzyme: Alpha-amylase Evolution, Structure, and Potential Biotechnological Applications for the Bioremediation of n-alkanes

  • International Cooperation

    AICaBI: Artificial Intelligence for Cancer Biomarkes Identification


We convert biological questions into answers

The SBCBLab has a solid history of research in Bioinformatics, with several publications in the area. The group has vast knowledge in Artificial Intelligence, Machine Learning, Metaheuristics, and Massively Parallel Processing.

An essential aspect of the analysis made by our group is the potential integration of data of different natures. In this sense, for example, expression data can be applied in System Biology protocols and machine learning algorithms. We have experience dealing with the analysis and manipulation of data from the different sources listed above in a single integrative protocol that has been increasingly sought after and demanded in Brazil and worldwide.

We are also working in protein structure prediction, molecular docking, molecular dynamic simulation, analysis of transcriptomic data, systems biology, including analysis of co-expression networks, regulatory networks, and protein-protein interaction post-translational gene regulation (alternative splicing, miRNAs, and lncRNAs).

 We are Hiring!

SBCBLab is looking for Master and Ph.D. Candidates in Computer Science or Cell and Molecular Biology.

Candidates should be highly motivated and have strong academic backgrounds in Computer Science or Bioinformatics and excellent writing skills including documentation skills to maintain software and support documentation. A high degree of energy, accuracy, and attention to detail, and a passion for science. The students will participate in multidisciplinary studies focusing on the design of novel methods and computational strategies for Bioinformatics problems.

Interested students are encouraged to contact Prof. Dorn (mdorn@inf.ufrgs.br) with a short introduction of her/his academic backgrounds, research interests, and career goal. Students wishing to complete a Masters or Ph.D. degree in Computer Science are enrolled in the Postgraduate Program in Computing (PPGC) . Students who want to complete a Master or Ph.D. in Molecular and Cell Biology are registered in the Postgraduate Program in Molecular and Cell Biology (PPGBCM) . The candidate may hold a scholarship or may receive financial support from some other source.

  Tools and Datasets

Science is moving towards a greater openness, not just data but also publications, computer code, and workflows. The SBCBLab is committed to open science and free access to tools and datasets. Over the last few years, we have developed several tools, libraries, and datasets.

 International Cooperation