Microarray data analysis : methods and applications / edited by Pietro Hiram Guzzi.
Material type:
TextSeries: Methods in molecular biology ; 1375.Publisher: New York : Springer, 2015Edition: 2nd editionDescription: 200 pages ; 26 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9781493931729 (hbk.) :Subject(s): Non-coding RNA | Science | ScienceDDC classification: 572.8'8 Summary: This volume covers a large area, from the description of methodologies for data analysis to the real application. Chapters focus on methodologies for preprocessing of microarray data, a survey of miRNA Data analysis, Cloud-based approaches, application of data mining techniques for data analysis, biclustering to query different datasets, web-based tool to analyze the evolution of miRNA clusters, application of biclustering to mine patterns of co-regulated genes ontologies, microarray and proteomic Data, Gene Regulatory Network Inference, Gene Regulatory Network methods, analysis of Mouse data for metabolomics studies, analysis of microRNA data in Multiple Myeloma, microarray data analysis in Gliobastomas, and microRNA data in Cardiogenesis.
| Item type | Current library | Home library | Shelving location | Class number | Status | Date due | Barcode | Item reservations | |
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Reference book
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Paul Hamlyn Library | Paul Hamlyn Library | Floor 2 | 572.8636 MIC (Browse shelf(Opens below)) | Not for loan | 06527809 | |||
Book
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Paul Hamlyn Library | Paul Hamlyn Library | Floor 2 | 572.8636 MIC (Browse shelf(Opens below)) | Available | 06527795 |
Includes bibliographical references.
This volume covers a large area, from the description of methodologies for data analysis to the real application. Chapters focus on methodologies for preprocessing of microarray data, a survey of miRNA Data analysis, Cloud-based approaches, application of data mining techniques for data analysis, biclustering to query different datasets, web-based tool to analyze the evolution of miRNA clusters, application of biclustering to mine patterns of co-regulated genes ontologies, microarray and proteomic Data, Gene Regulatory Network Inference, Gene Regulatory Network methods, analysis of Mouse data for metabolomics studies, analysis of microRNA data in Multiple Myeloma, microarray data analysis in Gliobastomas, and microRNA data in Cardiogenesis.
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