Name
Title | ||
|---|---|---|
Curve Profiling Feature: Novel Compact Representation for Drosophila Embryonic Gene Expression Pattern Mining |
Abstract | ||
|---|---|---|
Curve Profiling Feature (CPF) is an innovative compact and discriminative feature for representing and mining the temporal-spatial patterns underlying Drosophila embryonic gene expressions from the Berkeley Drosophila Genome Project (BDGP) in situ hybridization (ISH) database. CPF is calibration-free, unaffected by differences in individual embryonic size or shape, biologically inspired, and can significantly reduce data dimensionality. Moreover, CPF can identify spatial periodic patterns - a nontrivial concern by previous methods. Quantitative evaluations by controlled vocabulary annotation prediction and gene function enrichment with Gene Ontology knowledge base showed that our CPF achieves comparable performance as state-of-the-art Bag-Of-Words model while requires much less space and time. Application systems are also proposed to help biologists in different aspects including predicting annotations and gene functional enrichment, visualization based on manifold learning, content-based gene expression pattern retrieval with synthesized query. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICDMW.2010.67 | ICDM Workshops |
Keywords | Field | DocType |
drosophila embryonic gene expression,feature representation,pattern mining,novel compact representation,gene ontology functional enrichment,berkeley drosophila genome project,embryonic gene expression pattern mining,gene function enrichment,annotation prediction,drosophila,content-based gene expression pattern,curve profiling feature,in situ hybridization database,biology computing,comparable performance,individual embryonic size,ontologies (artificial intelligence),data mining,gene ontology knowledge base,application system,gene functional enrichment,ontologies,gene expression,spatial pattern,databases,bag of words,fault tolerance,controlled vocabulary,embryo,manifold learning,knowledge base,manifolds | Data mining,Gene,Annotation,Genome project,Expression (mathematics),Profiling (computer programming),Computer science,Curse of dimensionality,Nonlinear dimensionality reduction,Discriminative model | Conference |
ISBN | Citations | PageRank |
978-0-7695-4257-7 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunsheng Fang | 1 | 7 | 1.49 |
| Minlu Zhang | 2 | 25 | 1.96 |
| Anca L. Ralescu | 3 | 274 | 83.69 |
| Jason Lu | 4 | 73 | 6.00 |