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Application of omics, AI and blockchain in bioinformatics research edited by Jeffrey J-P Tsai, Asia University, Taiwan and Ka-Lok Ng, Asia University, Taiwan.

Contributor(s): Tsai, Jeffrey J.-P | Ng, Ka-Lok | [editor.] | [editor.].
Material type: materialTypeLabelBookSeries: Advanced series in electrical and computer engineering ; volume 21.Description: pages cm.ISBN: 9789811203572 (hc : alk. paper).Subject(s): Life sciences | Biotechnology | Biomedical engineering | Bioinformatics | Blockchains (Databases) | Artificial intelligence | -- Data processing | -- Data processing | -- Data processingDDC classification: 610.285
Partial contents:
Generalized iterative modeling for clinical omics data analysis / Kung-Hao Liang -- Explainable AI : mining of genotype data identifies complex disease pathways, autism case studies / Matt Spencer, Saad Khan, Zohreh Talebizadeh and Chi-Ren Shyu -- Blockchain for pre-clinical and clinical platform with big data analytics / Yin-Wu Chen and Zonyin Shae. Contents Chapter 1. Generalized Iterative Modeling for Clinical Omics Data Analysis Chapter 2. Explainable AI: Mining of Genotype Data Identifies Complex Disease Pathways — Autism Case Studies Chapter 3. Blockchain for Pre-clinical and Clinical Platform with Big Data Chapter 4. Analysis of Circulating Tumor DNA in Patients with Cancer: A Clinical Perspective Chapter 5. Big Data Computation of Drug Design: From the Natural Products to the Transcriptomic-Based Molecular Development Chapter 6. A Hybrid Approach Integrating Model-Based Method and Gene Functional Similarity for Cluster Analysis of RNA-Seq Data Chapter 7. High-Performance Computing for Measurement of Cancer Gene Signatures Chapter 8. High-Performance Computing in Tandem Mass Spectrometry (MS/MS) Data Processing Chapter 9. Analysis of Boolean Networks and Boolean Models of Metabolic Networks Chapter 10. Tensor Decomposition Based Unsupervised Feature Extraction Applied to Bioinformatics Index
Summary: "With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare. Two such areas are: (I) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (II) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases. A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, Omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network"--
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General Books General Books CUTN Central Library

This is a searchable open catalogue of all library of the Central University of Tamil Nadu.

Medicine, Technology & Management
Non-fiction 610.285 JEF (Browse shelf) Available 44006

Generalized iterative modeling for clinical omics data analysis / Kung-Hao Liang -- Explainable AI : mining of genotype data identifies complex disease pathways, autism case studies / Matt Spencer, Saad Khan, Zohreh Talebizadeh and Chi-Ren Shyu -- Blockchain for pre-clinical and clinical platform with big data analytics / Yin-Wu Chen and Zonyin Shae. Contents
Chapter 1. Generalized Iterative Modeling for Clinical Omics Data Analysis
Chapter 2. Explainable AI: Mining of Genotype Data Identifies Complex Disease Pathways — Autism Case Studies
Chapter 3. Blockchain for Pre-clinical and Clinical Platform with Big Data
Chapter 4. Analysis of Circulating Tumor DNA in Patients with Cancer: A Clinical Perspective
Chapter 5. Big Data Computation of Drug Design: From the Natural Products to the Transcriptomic-Based Molecular Development
Chapter 6. A Hybrid Approach Integrating Model-Based Method and Gene Functional Similarity for Cluster Analysis of RNA-Seq Data
Chapter 7. High-Performance Computing for Measurement of Cancer Gene Signatures
Chapter 8. High-Performance Computing in Tandem Mass Spectrometry (MS/MS) Data Processing
Chapter 9. Analysis of Boolean Networks and Boolean Models of Metabolic Networks
Chapter 10. Tensor Decomposition Based Unsupervised Feature Extraction Applied to Bioinformatics
Index

"With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare. Two such areas are: (I) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (II) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases. A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, Omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network"--

Includes bibliographical references and index.

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