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Cluster analysis
| Content Provider | Scilit |
|---|---|
| Author | Draghici, Sorin |
| Copyright Year | 2016 |
| Description | Cluster analysis is currently the most frequently used multivariate technique to analyze gene sequence expression data. Clustering is appropriate when there is no a priori knowledge about the data. In such circumstances, the only possible approach is to study the similarity between different samples or experiments. In a machine learning framework, such an analysis process is known as unsupervised learning since there is no known desired answer for any particular gene or experiment. 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/b11566-23&format=pdf |
| Ending Page | 680 |
| Page Count | 68 |
| Starting Page | 613 |
| DOI | 10.1201/b11566-23 |
| 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 Cluster Analysis Learning Experiment Circumstances Machine Unsupervised Answer Priori |
| Content Type | Text |
| Resource Type | Chapter |