000			03659cam a22003978i 4500
999			_c35235 _d35235
003			CUTN
005			20210706144559.0
008			190222s2019 nju b 001 0 eng
020			_a9789811203572 (hc : alk. paper)
041			_aEnglish
042			_apcc
082	0	0	_a610.285 _223 _bJEF
245	0	0	_aApplication of omics, AI and blockchain in bioinformatics research _cedited by Jeffrey J-P Tsai, Asia University, Taiwan and Ka-Lok Ng, Asia University, Taiwan.
300			_apages cm.
505	2		_aGeneralized 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. _tContents 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
520			_a"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"--
650		0	_aLife sciences
650		0	_aBiotechnology
650		0	_aBiomedical engineering
650		0	_aBioinformatics.
650		0	_aBlockchains (Databases)
650		0	_aArtificial intelligence. _94
700	1		_aTsai, Jeffrey J.-P.,
700	1		_aNg, Ka-Lok,
942			_2ddc _cBOOKS
263			_a1908
490	0		_aAdvanced series in electrical and computer engineering ; _vvolume 21
504			_aIncludes bibliographical references and index.
650		0	_xData processing.
650		0	_xData processing.
650		0	_xData processing.
700	1		_eeditor.
700	1		_eeditor.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg