Advances in bioinformatics and computational biology : 13th Brazilian Symposium on Bioinformatics, BSB 2020, São Paulo, Brazil, November 23-27, 2020, Proceedings /
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| Meeting name: | Brazilian Symposium on Bioinformatics (13th : 2020 : Online) |
|---|---|
| Imprint: | Cham : Springer, 2020. |
| Description: | 1 online resource (284 pages) |
| Language: | English |
| Series: | Lecture Notes in Computer Science ; 12558 LNCS sublibrary, SL 8, Bioinformatics Lecture notes in computer science ; 12558. LNCS sublibrary. SL 8, Bioinformatics. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/12609632 |
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| 111 | 2 | |a Brazilian Symposium on Bioinformatics |n (13th : |d 2020 : |c Online) | |
| 245 | 1 | 0 | |a Advances in bioinformatics and computational biology : |b 13th Brazilian Symposium on Bioinformatics, BSB 2020, São Paulo, Brazil, November 23-27, 2020, Proceedings / |c João C. Setubal, Waldeyr Mendes Silva (eds.). |
| 246 | 3 | |a BSB 2020 | |
| 260 | |a Cham : |b Springer, |c 2020. | ||
| 300 | |a 1 online resource (284 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 347 | |b PDF | ||
| 490 | 1 | |a Lecture Notes in Computer Science ; |v 12558 | |
| 490 | 1 | |a LNCS sublibrary, SL 8, Bioinformatics | |
| 500 | |a International conference proceedings. | ||
| 500 | |a "This volume contains the accepted papers for BSB 2020, held virtually during November 23-27, 2020"--Preface | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 500 | |a Combining Mutation and Gene Network Data in a Machine Learning Approach for False-Positive Cancer Driver Gene Discovery. | ||
| 500 | |a Includes author index. | ||
| 520 | |a 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. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed February 17, 2021). | |
| 650 | 0 | |a Bioinformatics |v Congresses. | |
| 650 | 0 | |a Computational biology |v Congresses. | |
| 650 | 7 | |a Computational biology. |2 fast |0 (OCoLC)fst00871990 | |
| 650 | 7 | |a Bioinformatics. |2 fast |0 (OCoLC)fst00832181 | |
| 655 | 7 | |a Conference papers and proceedings. |2 fast |0 (OCoLC)fst01423772 | |
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Setubal, João Carlos. |0 http://id.loc.gov/authorities/names/n96090924 | |
| 700 | 1 | |a Silva, Waldeyr Mendes. | |
| 776 | 0 | 8 | |i Print version: |a Setubal, João C. |t Advances in Bioinformatics and Computational Biology. |d Cham : Springer International Publishing AG, ©2021 |z 9783030657741 |
| 830 | 0 | |a Lecture notes in computer science ; |v 12558. |0 http://id.loc.gov/authorities/names/n42015162 | |
| 830 | 0 | |a LNCS sublibrary. |n SL 8, |p Bioinformatics. |0 http://id.loc.gov/authorities/names/n2008077790 | |
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