Name
Title | ||
|---|---|---|
Extracting characteristic patterns from genome-wide expression data by non-negative matrix factorization |
Abstract | ||
|---|---|---|
In this paper, we propose a novel approach, which is called as nonnegative matrix factorization (NMF), to analyze genome wide expression data. One of NMF advantages is that it can directly process these data without normalization. Firstly, we design an optimal algorithm for NMF approach. Compared with the existing NMF algorithms, our algorithm is more stable and converges very fast. We have coded the final algorithm in highly optimized C. Secondly, we describe the use of NMF in the extraction of the characteristic patterns from genome wide expression data. Thirdly, some simulation experiments are made in order to verify the efficiency of NMF algorithm, our conclusions are that NMF can be used as a powerful tool to extract the biologically-meaningful expression patterns from genomic wide expression data. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/CSB.2004.1332499 | CSB |
Keywords | Field | DocType |
optimisation,genome wide expression data,biologically meaningful expression pattern,wide expression data,genetics,nmf advantage,nmf algorithm,data processing,characteristic pattern extraction,biology computing,final algorithm,nonnegative matrix factorization,matrix decomposition,existing nmf algorithm,genomic wide expression data,genome-wide expression data,non-negative matrix factorization,novel approach,optimal algorithm,nmf approach,extracting characteristic patterns,cell cycle regulation,non negative matrix factorization,simulation experiment | Genome,Normalization (statistics),Computer science,Matrix decomposition,Non-negative matrix factorization,Artificial intelligence,Bioinformatics,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2194-0 | 8 | 0.63 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nini Rao | 1 | 85 | 11.36 |
| Simon J. Shepherd | 2 | 60 | 10.53 |