Microarray Data Analysis
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Microarray Data Analysis
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Beschreibung
Tools in Pharmacogenomics Biomarker Identification for Cancer Patients.- High Performance Framework to Analyze Microarray Data.- Web and Cloud Computing to Analyze Microarray Data.- A Microarray Analysis Technique Using a Self-Organizing Multi-Agent Approach.- Improving Analysis and Annotation of Microarray Data with Protein Interactions.- Algorithms to Preprocess Microarray Image Data.- Microarray Data Preprocessing: From Experimental Design to Differential Analysis.- Supervised Methods for Biomarker Detection from Microarray Experiments.- Unsupervised Algorithms for Microarray Sample Stratification.- Pathway Enrichment Analysis of Microarray Data.- Network Analysis of Microarray Data.- geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO).- Scenarios for the Integration of Microarray Gene Expression Profiles in COVID-19-Related Studies.- Alignment of Microarray Data.- Integration of DNA Microarray with Clinical and Genomic Data.- ClusteringMethods for Microarray Data Sets.- Microarray Data Analysis Protocol.- Using Gene Ontology to Annotate and Prioritize Microarray Data.- Using MMRFBiolinks R-Package for Discovering Prognostic Markers in Multiple Myeloma.
Produktdetails
- Typ:
- Buch
- Edition:
- 1
- Sprachen:
-
Original:
Englisch
- Seitenzahl:
-
332
- Herausgeber:
-
Springer
- Veröffentlichungsdatum:
-
2021-12-14
- ISBN / EAN:
-
9781071618387
- Gewicht:
-
823 g
- Maße:
-
18/26/2 cm
- GPSR-Herstellerreferenz:
-
[email protected]
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