1 option
Computational Advances in Bio and Medical Sciences : 11th International Conference, ICCABS 2021, Virtual Event, December 16-18, 2021, Revised Selected Papers / edited by Mukul S. Bansal, Ion Măndoiu, Marmar Moussa, Murray Patterson, Sanguthevar Rajasekaran, Pavel Skums, Alexander Zelikovsky.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in bioinformatics 2366-6331 ; 13254
- Lecture Notes in Bioinformatics, 2366-6331 ; 13254
- Language:
- English
- Subjects (All):
- Application software.
- Computers, Special purpose.
- Image processing-Digital techniques.
- Computer vision.
- Machine learning.
- Computer and Information Systems Applications.
- Special Purpose and Application-Based Systems.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Machine Learning.
- Local Subjects:
- Computer and Information Systems Applications.
- Special Purpose and Application-Based Systems.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Machine Learning.
- Physical Description:
- 1 online resource (X, 177 pages) : 59 illustrations, 50 illustrations in color.
- Edition:
- 1st ed. 2022.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- System Details:
- text file PDF
- Summary:
- 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.
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-031-17531-2
- 9783031175312
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.