Statistical Methods for the Analysis of Genomic Data
In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational bi...
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| Format: | Book Chapter |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2020
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| Online Access: | Get Fullteks DOAB: description of the publication |
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| LEADER | 03474naaaa2200721uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_68899 | ||
| 005 | 20210501 | ||
| 020 | |a books978-3-03936-141-0 | ||
| 020 | |a 9783039361403 | ||
| 020 | |a 9783039361410 | ||
| 024 | 7 | |a 10.3390/books978-3-03936-141-0 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 072 | 7 | |a GP |2 bicssc | |
| 072 | 7 | |a P |2 bicssc | |
| 100 | 1 | |a Jiang, Hui |4 edt | |
| 700 | 1 | |a He, Zhi |4 edt | |
| 700 | 1 | |a Jiang, Hui |4 oth | |
| 700 | 1 | |a He, Zhi |4 oth | |
| 245 | 1 | 0 | |a Statistical Methods for the Analysis of Genomic Data |
| 260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2020 | ||
| 300 | |a 1 electronic resource (136 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Research & information: general |2 bicssc | |
| 650 | 7 | |a Mathematics & science |2 bicssc | |
| 653 | |a multiple cancer types | ||
| 653 | |a integrative analysis | ||
| 653 | |a omics data | ||
| 653 | |a prognosis modeling | ||
| 653 | |a classification | ||
| 653 | |a gene set enrichment analysis | ||
| 653 | |a boosting | ||
| 653 | |a kernel method | ||
| 653 | |a Bayes factor | ||
| 653 | |a Bayesian mixed-effect model | ||
| 653 | |a CpG sites | ||
| 653 | |a DNA methylation | ||
| 653 | |a Ordinal responses | ||
| 653 | |a GEE | ||
| 653 | |a lipid-environment interaction | ||
| 653 | |a longitudinal lipidomics study | ||
| 653 | |a penalized variable selection | ||
| 653 | |a convolutional neural networks | ||
| 653 | |a deep learning | ||
| 653 | |a feed-forward neural networks | ||
| 653 | |a machine learning | ||
| 653 | |a gene regulatory network | ||
| 653 | |a nonparanormal graphical model | ||
| 653 | |a network substructure | ||
| 653 | |a false discovery rate control | ||
| 653 | |a gaussian finite mixture model | ||
| 653 | |a clustering analysis | ||
| 653 | |a uncertainty | ||
| 653 | |a expectation-maximization algorithm | ||
| 653 | |a classification boundary | ||
| 653 | |a gene expression | ||
| 653 | |a RNA-seq | ||
| 653 | |a n/a | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/2666 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/68899 |7 0 |z DOAB: description of the publication |