Overview

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.

Full Product Details

Author:   Mukul S. Bansal ,  Ion Măndoiu ,  Marmar Moussa ,  Murray Patterson
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13254
Weight:   0.296kg
ISBN:  

9783031175305

ISBN 10:   3031175301
Pages:   177
Publication Date:   19 October 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of 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.

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