We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Data reduction for spectral clustering to analyze high throughput flow cytometry data.
- Authors
Zare, Habil; Shooshtari, Parisa; Gupta, Arvind; Brinkman, Ryan R
- Abstract
Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular has proven to be a powerful tool amenable for many applications. However, it cannot be directly applied to large datasets due to time and memory limitations. To address this issue, we have modified spectral clustering by adding an information preserving sampling procedure and applying a post-processing stage. We call this entire algorithm SamSPECTRAL.
- Publication
BMC bioinformatics, 2010, Vol 11, p403
- ISSN
1471-2105
- Publication type
Journal Article
- DOI
10.1186/1471-2105-11-403