Umfang:
1 Online-Ressource(X, 177 p. 59 illus., 50 illus. in color.)
Ausgabe:
1st ed. 2022.
ISBN:
9783031175312
Serie:
Lecture Notes in Bioinformatics 13254
Inhalt:
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.
Inhalt:
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.
Weitere Ausg.:
ISBN 9783031175305
Weitere Ausg.:
ISBN 9783031175329
Weitere Ausg.:
Erscheint auch als Druck-Ausgabe ISBN 9783031175305
Weitere Ausg.:
Erscheint auch als Druck-Ausgabe ISBN 9783031175329
Sprache:
Englisch
DOI:
10.1007/978-3-031-17531-2
