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Computational Advances in Bio and Medical Sciences [electronic resource] : 11th International Conference, ICCABS 2021, Virtual Event, December 16–18, 2021, Revised Selected Papers /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Bioinformatics ; 13254Publisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022Description: X, 177 p. 59 illus., 50 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031175312
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.3 23
LOC classification:
  • QA76.76.A65
Online resources:
Contents:
Computational Advances in Bio and Medical Sciences -- Single Model Quality Estimation of Protein Structures via Non-negative Tensor Factorization -- Graph Representation Learning for Protein Conformation Sampling -- Excerno: Filtering mutations caused by the clinical archival process in sequencing data -- Relabeling metabolic pathway data with groups to improve prediction outcomes -- MELEPS: Multiple Expert Linear Epitope Prediction System -- Encoder-Decoder Architectures for Clinically Relevant Coronary Artery Segmentation -- Unified SAT-Solving for Hard Problems of Phylogenetic Network Construction -- Feature Selection for Identification of Risk Factors Associated with Infant Mortality -- Addressing classification on highly imbalanced clinical datasets -- mcPBWT: Space-efficient Multi-column PBWT Scanning Algorithm for Composite Haplotype Matching -- Computational Advances in Molecular Epidemiology -- Clustering SARS-CoV-2 Variants from Raw High-Throughput Sequencing Reads Data.-Analysis of SARS-CoV-2 temporal molecular networks using global and local topological characteristics -- An SVM Based Approach to Study the Racial Disparity in Triple-Negative Breast Cancer.
In: Springer Nature eBookSummary: This book constitutes revised selected papers from the refereed proceedings of the 11th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2021, held as a virtual event during December 16–18, 2021. The 13 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: Computational advances in bio and medical sciences; and computational advances in molecular epidemiology.
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Computational Advances in Bio and Medical Sciences -- Single Model Quality Estimation of Protein Structures via Non-negative Tensor Factorization -- Graph Representation Learning for Protein Conformation Sampling -- Excerno: Filtering mutations caused by the clinical archival process in sequencing data -- Relabeling metabolic pathway data with groups to improve prediction outcomes -- MELEPS: Multiple Expert Linear Epitope Prediction System -- Encoder-Decoder Architectures for Clinically Relevant Coronary Artery Segmentation -- Unified SAT-Solving for Hard Problems of Phylogenetic Network Construction -- Feature Selection for Identification of Risk Factors Associated with Infant Mortality -- Addressing classification on highly imbalanced clinical datasets -- mcPBWT: Space-efficient Multi-column PBWT Scanning Algorithm for Composite Haplotype Matching -- Computational Advances in Molecular Epidemiology -- Clustering SARS-CoV-2 Variants from Raw High-Throughput Sequencing Reads Data.-Analysis of SARS-CoV-2 temporal molecular networks using global and local topological characteristics -- An SVM Based Approach to Study the Racial Disparity in Triple-Negative Breast Cancer.

This book constitutes revised selected papers from the refereed proceedings of the 11th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2021, held as a virtual event during December 16–18, 2021. The 13 full papers included in this book were carefully reviewed and selected from 17 submissions. They were organized in topical sections as follows: Computational advances in bio and medical sciences; and computational advances in molecular epidemiology.

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