{"id":944,"date":"2024-10-29T12:12:41","date_gmt":"2024-10-29T12:12:41","guid":{"rendered":"https:\/\/bsb.sbc.org.br\/2024\/?page_id=944"},"modified":"2025-02-06T21:42:08","modified_gmt":"2025-02-06T21:42:08","slug":"accepted-works","status":"publish","type":"page","link":"https:\/\/bsb.sbc.org.br\/2024\/accepted-works\/","title":{"rendered":"Accepted works"},"content":{"rendered":"\t\t
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Full papers<\/span><\/h3>\n

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  1. A Comparative Study of CNN for Prediction of Human Cancer Types Integrating Protein-Protein Interaction Networks and Omics Data<\/b><\/li>\n
  2. A computational pipeline for species- and strain-level classification of metagenomic sequences<\/b><\/li>\n
  3. AutoBioLearn: An Automated Data Science Framework for eXplainable Analyses (XAI) of Clinical Datasets<\/b><\/li>\n
  4. COCaDA – Large-Scale Protein Interatomic Contact Cutoff Optimization by Ca Distance Matrices<\/b><\/li>\n
  5. Comparison of computational fusion detection methods for short-read RNA-seq data<\/b><\/li>\n
  6. Evaluating the Generalization of Neural Network-Based Pan-Cancer Classification Models for Cohort-Specific Predictions<\/b><\/li>\n
  7. Genomic and phylogenetic analysis of plant growth-promoting bacteria<\/b><\/li>\n
  8. Graph Attention Neural Networks Improving Molecular Docking Rank with Protein-Ligand Contact Maps<\/b><\/li>\n
  9. Heuristics based on Adjacency Graph Packing for DCJ Distance Considering Intergenic Regions<\/b><\/li>\n
  10. Modeling cell signaling pathways through universal differential equations and joint inference of first-principle parameters and neural network weights<\/b><\/li>\n
  11. Optimized Neural Networks for Breast Cancer Classification Using Gene Expression Data<\/b><\/li>\n
  12. Predicting Mutation-Driven Changes in the SARS-CoV-2 Spike Protein Using Structural Signatures and Neural Networks<\/b><\/li>\n
  13. Scaling Up ESM2 Architectures for Long Protein Sequences Analysis: Long and Quantized Approaches<\/b><\/li>\n
  14. Squares in Cycles: Prediction of G-Quadruplexes in Circular RNA Secondary Stuctures<\/b><\/li>\n
  15. Teaching bioinformatics programming in high school: a case report<\/b><\/li>\n
  16. Towards a simpler computational semantics for molecular biology<\/b><\/li>\n
  17. Towards a Surrogate-assisted PALLAS algorithm for Gene Regulatory Network Inference<\/b><\/li>\n
  18. Tuning a predictive DNA replication programming computational model for Trypanosomatids<\/b><\/li>\n
  19. Unraveling Evolutionary Paths: Genomic Divergence and Geographic Secrets of Cylindrospermopsis and Sphaerospermopsis<\/b><\/li>\n
  20. Using graph-based structural signatures and machine learning algorithms for molecular docking assessment of histone deacetylases and small ligands<\/b><\/li>\n<\/ol>\n
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    Short papers<\/span><\/h3>\n

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    1. A strategy for refining the calculation of contacts in protein-RNA complexes<\/b><\/li>\n
    2. In silico study of the impact of the PRKAG2-H401Q mutation on AMPK affinity for AMP and ATP<\/b><\/li>\n<\/ol>\n

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      Posters<\/span><\/h3>\n

      P01 – A bioinformatics approach to define host-element boundaries using Microviridae phages and casposons as study models<\/b><\/p>\n

      P02 – A Curated Dataset for Machine Learning Training to Predict Novel Peptide Inhibitors of Voltage-Gated Sodium Channels in Drosophila suzukii (Matsumura, 1931) <\/b><\/p>\n

      P03 – A genomic approach to the selection of growth-promoting bacteria in maize using reverse ecology<\/b><\/p>\n

      P04 – A graphical bioinformatics tool for delineating viral taxonomic levels<\/b><\/p>\n

      P05 – A Tm-value prediction system and molecular dynamics analysis of AmNA-containing gapmer antisense oligonucleotides<\/b><\/p>\n

      P06 – Analysis of rbd-spike interactions of sars-cov-2 omicron variants with ace2 through molecular dynamics<\/b><\/p>\n

      P07 – Antimicrobial Resistance Genes in Oligotrophic Ecosystems: An Evolutionary Insight from Microbialites and Microbial Mats of Cuatro Ci\u00e9negas<\/b><\/p>\n

      P08 – Application of Machine Learning Algorithms for Identification of Viruses in Dark Matter from Next-Generation Sequencing<\/b><\/p>\n

      P09 – <\/span>Beyond mutations: Human Cytomegalovirus as a driver of heterogeneity in Glioblastoma<\/span>
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      P10 – Bioinformatics analysis revealed that NOTCH1 expression in Glioblastoma Multiforme patients and Glioma Stem Cells is associated with impaired cellular OXPHOS and low immune infiltration<\/b><\/p>\n

      P11 – Characterization of Psychiatric Disorders Cataloged in the DSM-5 Through a Network Approach<\/b><\/p>\n

      P12 – Classification of HIV genomes through graph comparison and analysis<\/b><\/p>\n

      P13 – ClusterONE Web: a web tool for detecting and visualizing overlapping protein complexes in protein-protein interaction networks<\/b><\/p>\n

      P14 – Comparative Analysis of Supervised Classifiers in Predicting COVID-19 Severity Using Data from 239 Exomes<\/b><\/p>\n

      P15 – Comparative Genomic Analyses Highlight the Crucial Role of Mobile Genetic Elements in Paenibacillus strains<\/b><\/p>\n

      P16 – Comparative Genomic Analyses reveal key characteristics for the Biocontrol and the Promotion of Plant Growth in Paenibacillus Strains<\/b><\/p>\n

      P17 – De novo transcriptome assembly and annotation for gene discovery in Euterpe edulis<\/b><\/p>\n

      P18 – Development of a web system responsible for automating the process of validating three-dimensional proteins<\/b><\/p>\n

      P19 – Discovery of Conditionally Independent Networks Among Gene Expressions in Breast Cancer Using Fast StepGraph<\/b><\/p>\n

      P20 – EEG-Based Schizophrenia Classification Using Vision Transformers and Microstate Analysis<\/b><\/p>\n

      P21 – Enhancing Enzyme Generation with Fine-Tuned Conditional Transformers<\/b><\/p>\n

      P22 – Evaluation Of Machine Learning Models In Identifying Neurological Complications Of Covid-19: An Integrated And Comparative Analysis<\/b><\/p>\n

      P23 – Exploring Genetic Determinants of Post-COVID-19 Dyspnea: An Exome Sequencing Approach<\/b><\/p>\n

      P24 – Exploring hybrid dynamic modeling of ordinary differential equations and data-driven models: From validation to expansion assisted by high-resolution mass spectrometry<\/b><\/p>\n

      P25 – Gene Expression Patterns and Their Impact on Muscle pH in Four Swine Genetic Groups<\/b><\/p>\n

      P26 – Genetic study of patients with persistent neurocognitive sequelae after COVID-19<\/b><\/p>\n

      P27 – Genome mining unveils the Algibacter genus as a treasure trove of biologically-active compounds<\/b><\/p>\n

      P28 – Genomic insights into the association between carbohydrate transporters and antimicrobial resistance in Staphylococcus aureus<\/b><\/p>\n

      P29 – Group I introns in the mitochondrial genomes of Trichoderma spp.<\/b><\/p>\n

      P30 – Harnessing Integrated Informatics and Molecular Simulation to Predict Antibody Epitopes on Viral Envelope Glycoproteins<\/b><\/p>\n

      P31 – Homology-based quantification of the fibrosis in the CT image: A proof of concept for CT image feature-assisted gene expression prediction<\/b><\/p>\n

      P32 – Identification of Genetic Alterations in Patients Who Developed Physical Fatigue as a Long COVID Condition<\/b><\/p>\n

      P33 – In silico validation of Linear B-Cell epitopes using Machine Learning: A proposed approach with organisms of genus Trypanosoma<\/b><\/p>\n

      P34 – Investigation of UDE-based approaches for cell cycle modeling<\/b><\/p>\n

      P35 – Metabarcoding reveal Fusarium decemcellulare as the potential causal agent of the emergent disease in Coffea canephora<\/b><\/p>\n

      P36 – Metagenomics and Bioinformatic tools in Agricultural Microbiome<\/b><\/p>\n

      P37 – Molecules of the Amazon: Integration and Centralization of Data on the Amazon Flora and its Biomolecules<\/b><\/p>\n

      P38 – Multi-omics systems biology approach identifies novel signature genes for neuropsychiatric disorders<\/b><\/p>\n

      P39 – Network Pharmacology and UHPLC-ESI-Q-TOF-MS\/MS Approaches to Explore Active Compounds and Mechanisms of Acerola Seed Hydroethanolic Extract in Obesity Treatment<\/b><\/p>\n

      P40 – Non coding variants near the NOTCH1 gene are associated with frailty criteria in Brazilians older adults<\/b><\/p>\n

      P41 – Nuclear Segmentation of Oncology Microscopy Images through Convolutional Neural Networks: A Comparative Analysis<\/b><\/p>\n

      P42 – Predicting aggregation region in proteins with machine learning based on tertiary structure: web platform<\/b><\/p>\n

      P43 – Predicting side effects of drug combinations in realistic experimental settings<\/b><\/p>\n

      P44 – Predictive Modeling Of Post-covid-19 Hair Loss: Insights From Machine Learning And Logistic Regression<\/b><\/p>\n

      P45 – Sialic Acid Enzymes Database<\/b><\/p>\n

      P46 – SP crime: A Python package for merging S\u00e3o Paulo criminal and medical data<\/b><\/p>\n

      P47 – The potential role of the JAK\/STAT pathways in the progression of depressive and anxiety disorders in Long COVID<\/b><\/p>\n

      P48 – The Role of Indel Variants in COVID-19: Unveiling Frequency Patterns and Potential Clinical Significance<\/b><\/p>\n

      P49 – The role of polyploid giant cells in cancer progression and their potential as therapeutic targets: a bioinformatic overview<\/b><\/p>\n

      P50 – Topology-based pan-cancer analysis of DLK1-DIO3-derived microRNA roles<\/b><\/p>\n

      P51 – Transcriptomic analysis of Crassostrea gigas oysters exposed to tamoxifen demonstrates alterations in cancer-associated metabolic pathways<\/b><\/p>\n

      P52 <\/b>–<\/span> <\/b>Transcriptomic analysis of the aged female omentum. Insights on metastatic invasion in a mouse model of ovarian cancer <\/b><\/p>\n

      P53 – Transcriptomic Analysis Reveals a Novel MicroRNA in Porcine Fetuses from Gilds Supplemented with L-Arginine<\/b><\/p>\n

      P54 – Tumor-Regeneration Interplay: Systems Biology and New Models in Comparative Study with Therapeutic Insights<\/b><\/p>\n

      P55 – Unlocking The Anti-aging Potential: In silico Analysis of Astaxanthin, Curcumin, Quercetin, and Resveratrol in Modulating Skin Aging Pathways<\/b><\/p>\n

      P56 – Verdict: An Interactive Web Tool for Exploring Disease Modules and Drug Targets within the Human Interactome<\/b><\/p>\n

      P57 – Large scale analysis of sialic acid incorporation mechanisms of <\/b>microorganisms from intestinal microbiota<\/b><\/p>\n

      P58 – Improvement of the assembly and Annotation of the Trypanosoma cruzi Genome Using Hi-C Data<\/strong><\/p>\n

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      Proceedings\u00a0<\/span><\/h2>\n

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      BSB 2024 Proceedings are available at SBC OpenLib (SOL)<\/b><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

      Accepted works Full papers A Comparative Study of CNN for Prediction of Human Cancer Types Integrating Protein-Protein Interaction Networks and Omics Data A computational pipeline for species- and strain-level classification of metagenomic sequences AutoBioLearn: An Automated Data Science Framework for eXplainable Analyses (XAI) of Clinical Datasets COCaDA – Large-Scale Protein Interatomic Contact Cutoff Optimization by […]<\/p>\n","protected":false},"author":11,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-944","page","type-page","status-publish","hentry","entry"],"_links":{"self":[{"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/pages\/944","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/comments?post=944"}],"version-history":[{"count":72,"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/pages\/944\/revisions"}],"predecessor-version":[{"id":2711,"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/pages\/944\/revisions\/2711"}],"wp:attachment":[{"href":"https:\/\/bsb.sbc.org.br\/2024\/wp-json\/wp\/v2\/media?parent=944"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}