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Focused microarrays – comparison and selection
| Content Provider | Scilit |
|---|---|
| Author | Draghici, Sorin |
| Copyright Year | 2016 |
| Description | Microarrays have been introduced as powerful tools able to screen a large number of genes in an efficient manner.1 The typical result of a microarray to generate hypotheses, and locate effects on many, perhaps apparently unrelated pathways. This is a typical hypothesis generating experiment. For this purpose, it is best to use comprehensive microarrays that represent as many genes of an organism as possible. Currently, such arrays include tens of thousands of genes. For example, the HGU133 (A+B) set from Affymetrix, Inc., contains 44,928 probes that represent 42,676 unique sequences from GenBank database, corresponding to 30,264 UniGene clusters. Book Name: Statistics and Data Analysis for Microarrays Using R and Bioconductor |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2009-0-01898-2&isbn=9780429130588&doi=10.1201/b11566-31&format=pdf |
| Ending Page | 940 |
| Page Count | 12 |
| Starting Page | 929 |
| DOI | 10.1201/b11566-31 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2016-04-19 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Statistics and Data Analysis for Microarrays Using R and Bioconductor Mathematical and Computational Biology Corresponding |
| Content Type | Text |
| Resource Type | Chapter |