Keynote Speakers

For details on our keynote speakers, including profiles, research contributions, and topics they will be presenting, please refer to our keynote section:

Keynote Speakers – BSB 2024

Technical Sessions

Technical Session 1 (Monday 15:30 – 17:00)

1) A computational pipeline for species- and strain-level classification of metagenomic sequences. Arthur Solano and Joao Setubal

2) Towards a simpler computational semantics for molecular biology. Luis Henrique Costa Neto and Sergio Lifschitz and Marcos Catanho and Antônio B. de Miranda and Edward Hermann Haeusler

3) Modeling cell signaling pathways through universal differential equations and joint inference of first-principle parameters and neural network weights. Cristiano Campos and Ronaldo Nogueira de Sousa and Hugo Aguirre Armelin and Marcelo Reis

4) Genomic and phylogenetic analysis of plant growth-promoting bacteria. Marcus Rodrigues and João Oliveira and Sandriele Noriler and Angelo Garcia and Ulisses Pereira and Ulisses Rocha and Admilton Oliveira Junior

5) Tuning a predictive DNA replication programming computational model for Trypanosomatids. Bruno Scholl and Ligia Palma and Victor Seiji Hariki and Maria Carolina Elias and Marcelo Reis

6) A strategy for refining the calculation of contacts in protein-RNA complexes. Luana Bastos and Rafael Lemos and Diego Mariano and Raquel Cardoso de Melo-Minardi

Technical Session 2 (Tuesday 09:00 – 10:30)

1) AutoBioLearn: An Automated Data Science Framework for eXplainable Analyses (XAI) of Clinical Datasets. Lucas Pinheiro Badaró Moreira and Maria Laura Gabriel Kuniyoshi and Zofia Wicik and David Martins-Jr and Helena Brentani and Sérgio Nery Simões

2) Graph Attention Neural Networks Improving Molecular Docking Rank with Protein-Ligand Contact Maps. Glauco Lima and Simone Pantaleão and Isabelle Pereira and Ana Scott

3) A Comparative Study of CNN for Prediction of Human Cancer Types Integrating Protein-Protein Interaction Networks and Omics Data. Marilio Almeida and Sérgio Nery Simões and Karin Komati

4) Using graph-based structural signatures and machine learning algorithms for molecular docking assessment of histone deacetylases and small ligands. Alessandra Cioletti and Rafael Lemos and Lucas Moraes dos Santos and Diego Mariano and Raquel de Melo-Minardi

5) Optimized Neural Networks for Breast Cancer Classification Using Gene Expression Data. Ana Beatriz Valentin and Glaucia Bressan and Leonardo Canuto Junior and Elisangela Lizzi

Technical Session 3 (Best Paper Contenders; Tuesday 15:30 – 17:00)

1) Teaching bioinformatics programming in high school: a case report. Helena Costa and Giovana Fiorini Maia and Lucas Moraes dos Santos and Diego Mariano and Raquel de Melo-Minardi

2) Squares in Cycles: Prediction of G-Quadruplexes in Circular RNA Secondary Stuctures. Ronny Lorenz and Peter Stadler

3) Unraveling Evolutionary Paths: Genomic Divergence and Geographic Secrets of Cylindrospermopsis and Sphaerospermopsis. Reno Nooblath and Daniel Gomes and Vinicius Abreu and Sintia Almeida

4) Comparison of computational fusion detection methods for short-read RNA-seq data. Lucas Oliveira and Victor Rigatto and João Meidanis

5) Towards a Surrogate-assisted PALLAS algorithm for Gene Regulatory Network Inference. Hugo Amorim and Luis Loo and Marcelo Lacerda and Ulisses Braga Neto and Fernando Buarque de Lima Neto

Tecnhical Session 4 (Wednesday 09:00 – 10:30)

1) Heuristics based on Adjacency Graph Packing for DCJ Distance Considering Intergenic Regions. Gabriel Siqueira and Alexsandro Alexandrino and Andre Oliveira and Zanoni Dias

2) Predicting Mutation-Driven Changes in the SARS-CoV-2 Spike Protein Using Structural Signatures and Neural Networks. Eduardo Moreira and Leandro Morais and Sheila Cruz and Rafael Lemos and Ana Bastos and Diego Mariano and Alessandra Silva

3) Evaluating the Generalization of Neural Network-Based Pan-Cancer Classification Models for Cohort-Specific Predictions. Thomas Fontanari and Mariana Recamonde-Mendoza

4) Scaling Up ESM2 Architectures for Long Protein Sequences Analysis: Long and Quantized Approaches. Gabriel Oliveira and Helio Pedrini and Zanoni Dias

5) COCaDA – Large-Scale Protein Interatomic Contact Cutoff Optimization by Ca Distance Matrices. Rafael Lemos and Diego Mariano and Sabrina Silveira and Raquel Cardoso de Melo-Minardi

6) In silico study of the impact of the PRKAG2-H401Q mutation on AMPK affinity for AMP and ATP. Jorge Fernandez

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Minicurso

Título: Introdução ao Aprendizado de Máquina para Bioinformática

Palestrante: Ronaldo Nogueira, bacharel em Ciência da Computação (UFG, 2019) e doutorando em Bioinformática na USP. Sua pesquisa foca em técnicas avançadas de Aprendizado de Máquina e Inteligência Artificial para elucidar mecanismos moleculares em vias de sinalização, especialmente no contexto da biologia do câncer.

Resumo:
O crescente volume e variedade de dados experimentais exige ferramentas para extração de padrões que possibilitem a exploração dos dados e a elucidação de hipóteses biológicas. Este minicurso introduz o Aprendizado de Máquina, abordando seu histórico, principais paradigmas e modelos. Demonstrações práticas serão realizadas em Python usando bibliotecas como Sklearn, PyTorch e/ou Tensorflow, com aplicações em Bioinformática.

Idioma: O minicurso será realizado em português (The minicourse will be held in Portuguese).

Público-alvo: Estudantes de graduação e pós-graduação com formação em ciências biológicas ou áreas de exatas.

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SBMF (Brazilian Symposium on Formal Methods)

The SBMF (Brazilian Symposium on Formal Methods) will be a co-located event with BSB 2024. SBMF activities will begin on Wednesday, December 4th, at 2:00 pm, following the conclusion of BSB, which ends at 12:30 pm.

We invite all participants to join us for SBMF (https://sbmf24.ifes.edu.br/) and take advantage of this opportunity for knowledge exchange in formal methods and related fields.