Paper Info
Title
Automatic recognition and annotation of gene expression patterns of fly embryos.
Abstract
Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts.We develop a system to automatically annotate a fruitfly's embryonic tissue in which a gene has expression. We formulate the task as an image pattern recognition problem. For a new fly embryo image, our system answers two questions: (1) Which stage range does an image belong to? (2) Which annotations should be assigned to an image? We propose to identify the wavelet embryo features by multi-resolution 2D wavelet discrete transform, followed by min-redundancy max-relevance feature selection, which yields optimal distinguishing features for an annotation. We then construct a series of parallel bi-class predictors to solve the multi-objective annotation problem since each image may correspond to multiple annotations.The complete annotation prediction results are available at: http://www.cs.niu.edu/~jzhou/papers/fruitfly and http://research.janelia.org/peng/proj/fly_embryo_annotation/. The datasets used in experiments will be available upon request to the correspondence author.
Year
DOI
Venue
2007
10.1093/bioinformatics/btl680
Bioinformatics
Keywords
DocType
Volume
important information,automatic recognition,image pattern recognition problem,fly embryo,multiple annotation,multi-objective annotation problem,new fly embryo image,different gene,gene expression pattern,complete annotation prediction result,wavelet embryo feature,supplementary information,pattern recognition,embryos,feature selection
Journal
23
Issue
ISSN
Citations 
5
1367-4811
32
PageRank 
References 
Authors
1.65
12
2
Name
Order
Citations
PageRank
Jie Zhou113910.45
Hanchuan Peng23930182.27