Advances in bioinformatics and computational biology : 13th Brazilian Symposium on Bioinformatics, BSB 2020, São Paulo, Brazil, November 23-27, 2020, Proceedings /
Advances in bioinformatics and computational biology : 13th Brazilian Symposium on Bioinformatics, BSB 2020, São Paulo, Brazil, November 23-27, 2020, Proceedings /
BSB 2020
João C. Setubal, Waldeyr Mendes Silva (eds.).
- Cham : Springer, 2020.
- 1 online resource (284 pages)
- Lecture Notes in Computer Science ; 12558 LNCS sublibrary, SL 8, Bioinformatics .
- Lecture notes in computer science ; 12558. LNCS sublibrary. SL 8, Bioinformatics. .
International conference proceedings. "This volume contains the accepted papers for BSB 2020, held virtually during November 23-27, 2020"--Preface Combining Mutation and Gene Network Data in a Machine Learning Approach for False-Positive Cancer Driver Gene Discovery. Includes author index.
Intro -- Preface -- Organization -- Contents -- A Classification of de Bruijn Graph Approaches for De Novo Fragment Assembly -- 1 Introduction -- 2 Genome Assembly -- 3 The de Bruijn Graph De Novo Assembly Approach -- 4 de Bruijn Graph Based Assemblers -- 4.1 Main Classification of Approaches -- 4.2 General Strategies to Reduce Memory Footprint for DBG Construction -- 4.3 Specific Strategies to Reduce the Large Memory Consumption -- 4.4 k-mers Counters -- 5 Conclusions -- References -- Redundancy Treatment of NGS Contigs in Microbial Genome Finishing with Hashing-Based Approach 1 Introduction -- 1.1 DNA Repetitions and Contigs Redundancy -- 1.2 Computational Methods for Redundancy Detection in Sequences -- 1.3 Contribution of This Work -- 2 Biological Dataset and Assembly -- 3 The Proposed Hybrid Model -- 4 Results and Discussion -- 5 Conclusion -- References -- Efficient Out-of-Core Contig Generation -- 1 Introduction -- 2 De Novo Assembly Using de Bruijn Graph -- 3 Overview of Our Proposed Approach -- 4 Contig Generation -- 5 Conclusions -- References -- In silico Pathogenomic Analysis of Corynebacterium Pseudotuberculosis Biovar Ovis -- 1 Introduction 1.1 Corynebacterium Pseudotuberculosis -- 1.2 Comparative Pathogenomics -- 1.3 Determinants of Pathogenicity -- 2 Methods -- 2.1 Pan-Genomic Analysis of C. Pseudotuberculosis Biovar Ovis -- 2.2 Prediction of Virulence Factors in Corynebacterium -- 2.3 Composition of Pathogenicity Islands (PAI) -- 2.4 Synteny in C. Pseudotuberculosis Genomes -- 2.5 In Silico Prediction of Pathogenicity Potentials -- 2.6 Protein-Protein Interactions -- 2.7 Identification of Prophages -- 3 Results and Discussion -- 3.1 Identification of Adherence Factors -- 3.2 Identification of Iron Uptake Factors 3.3 Identification of Regulation Factors -- 3.4 Identification of Toxin Factors -- 3.5 Prediction of Pathogenicity Islands -- 3.6 Prediction of Pathogenicity Potentials -- 3.7 Identification of Prophages -- 3.8 Prediction of Protein-Protein Interactions -- 4 Conclusion -- References -- Assessing the Sex-Related Genomic Composition Difference Using a k-mer-Based Approach: A Case of Study in Arapaima gigas (Pirarucu) -- 1 Introduction -- 2 Materials and Methods -- 2.1 Sequencing and Data Processing -- 2.2 k-mer Analysis -- 3 Results and Discussion -- 4 Conclusions -- References COVID-19 X-ray Image Diagnostic with Deep Neural Networks -- 1 Introduction -- 2 Dataset -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Classification Model -- 4 Experimental Evaluation -- 4.1 Model Evaluation -- 4.2 Multi-class and Binary Classification of the Unbalanced Dataset -- 4.3 Ensemble of CNNs -- 4.4 Test Set Evaluation -- 5 Conclusions and Future Work -- References -- Classification of Musculoskeletal Abnormalities with Convolutional Neural Networks -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Experiments -- 3 Results and Discussion -- 4 Conclusion -- References
This book constitutes the refereed proceedings of the Brazilian Symposium on Bioinformatics, BSB 2020, held in São Paulo, Brazil, in November 2020. Due to COVID-19 pandemic the conference was held virtually The 20 revised full papers and 5 short papers were carefully reviewed and selected from 45 submissions. The papers address a broad range of current topics in computational biology and bioinformatics.
9783030657758 3030657752
10.1007/978-3-030-65775-8 doi
Bioinformatics--Congresses.
Computational biology--Congresses.
Bio-informatique--Congrès.
Computational biology
Bioinformatics
Congress
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
QH324.2
570.285
International conference proceedings. "This volume contains the accepted papers for BSB 2020, held virtually during November 23-27, 2020"--Preface Combining Mutation and Gene Network Data in a Machine Learning Approach for False-Positive Cancer Driver Gene Discovery. Includes author index.
Intro -- Preface -- Organization -- Contents -- A Classification of de Bruijn Graph Approaches for De Novo Fragment Assembly -- 1 Introduction -- 2 Genome Assembly -- 3 The de Bruijn Graph De Novo Assembly Approach -- 4 de Bruijn Graph Based Assemblers -- 4.1 Main Classification of Approaches -- 4.2 General Strategies to Reduce Memory Footprint for DBG Construction -- 4.3 Specific Strategies to Reduce the Large Memory Consumption -- 4.4 k-mers Counters -- 5 Conclusions -- References -- Redundancy Treatment of NGS Contigs in Microbial Genome Finishing with Hashing-Based Approach 1 Introduction -- 1.1 DNA Repetitions and Contigs Redundancy -- 1.2 Computational Methods for Redundancy Detection in Sequences -- 1.3 Contribution of This Work -- 2 Biological Dataset and Assembly -- 3 The Proposed Hybrid Model -- 4 Results and Discussion -- 5 Conclusion -- References -- Efficient Out-of-Core Contig Generation -- 1 Introduction -- 2 De Novo Assembly Using de Bruijn Graph -- 3 Overview of Our Proposed Approach -- 4 Contig Generation -- 5 Conclusions -- References -- In silico Pathogenomic Analysis of Corynebacterium Pseudotuberculosis Biovar Ovis -- 1 Introduction 1.1 Corynebacterium Pseudotuberculosis -- 1.2 Comparative Pathogenomics -- 1.3 Determinants of Pathogenicity -- 2 Methods -- 2.1 Pan-Genomic Analysis of C. Pseudotuberculosis Biovar Ovis -- 2.2 Prediction of Virulence Factors in Corynebacterium -- 2.3 Composition of Pathogenicity Islands (PAI) -- 2.4 Synteny in C. Pseudotuberculosis Genomes -- 2.5 In Silico Prediction of Pathogenicity Potentials -- 2.6 Protein-Protein Interactions -- 2.7 Identification of Prophages -- 3 Results and Discussion -- 3.1 Identification of Adherence Factors -- 3.2 Identification of Iron Uptake Factors 3.3 Identification of Regulation Factors -- 3.4 Identification of Toxin Factors -- 3.5 Prediction of Pathogenicity Islands -- 3.6 Prediction of Pathogenicity Potentials -- 3.7 Identification of Prophages -- 3.8 Prediction of Protein-Protein Interactions -- 4 Conclusion -- References -- Assessing the Sex-Related Genomic Composition Difference Using a k-mer-Based Approach: A Case of Study in Arapaima gigas (Pirarucu) -- 1 Introduction -- 2 Materials and Methods -- 2.1 Sequencing and Data Processing -- 2.2 k-mer Analysis -- 3 Results and Discussion -- 4 Conclusions -- References COVID-19 X-ray Image Diagnostic with Deep Neural Networks -- 1 Introduction -- 2 Dataset -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Classification Model -- 4 Experimental Evaluation -- 4.1 Model Evaluation -- 4.2 Multi-class and Binary Classification of the Unbalanced Dataset -- 4.3 Ensemble of CNNs -- 4.4 Test Set Evaluation -- 5 Conclusions and Future Work -- References -- Classification of Musculoskeletal Abnormalities with Convolutional Neural Networks -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Experiments -- 3 Results and Discussion -- 4 Conclusion -- References
This book constitutes the refereed proceedings of the Brazilian Symposium on Bioinformatics, BSB 2020, held in São Paulo, Brazil, in November 2020. Due to COVID-19 pandemic the conference was held virtually The 20 revised full papers and 5 short papers were carefully reviewed and selected from 45 submissions. The papers address a broad range of current topics in computational biology and bioinformatics.
9783030657758 3030657752
10.1007/978-3-030-65775-8 doi
Bioinformatics--Congresses.
Computational biology--Congresses.
Bio-informatique--Congrès.
Computational biology
Bioinformatics
Congress
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
QH324.2
570.285