Automatic annotation of drosophila developmental stages using association classification and information integration

Tao Meng, Mei-Ling Shyu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

In current developmental research, one of the challenging tasks is to understand the spatio-temporal gene expression patterns and the relationships among different genes. In situ hybridization (ISH) assay which shows mRNA spatio-temporal expression patterns in cells and tissues directly is currently widely utilized in the bench work. With the increasing of available ISH images, automatic annotation systems are highly demanded. In this paper, an automatic classification system is proposed for annotating the in situ hybridization images with respect to the developmental stages. The embryo is first segmented from the original image, registered and normalized. The segmented embryo image is then divided into 100 blocks from which the pixel intensity and texture features are extracted and discretized. The multiple correspondence analysis (MCA) based association classification approach is proposed to generate classification rules for different stages based on the training data set. The testing instance is classified by applying the rules generated in the training process and a classification coordination module is incorporated to resolve the conflicts utilizing the weights derived from angle values in the MCA procedure. Experimental results show that our proposed method achieves promising results and outperforms other state-of-the-art algorithms.

Original languageEnglish
Title of host publicationProceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011
Pages142-147
Number of pages6
DOIs
StatePublished - Sep 29 2011
Event12th IEEE International Conference on Information Reuse and Integration, IRI 2011 - Las Vegas, NV, United States
Duration: Aug 3 2011Aug 5 2011

Other

Other12th IEEE International Conference on Information Reuse and Integration, IRI 2011
CountryUnited States
CityLas Vegas, NV
Period8/3/118/5/11

Fingerprint

Association reactions
Gene expression
Assays
Textures
Genes
Pixels
Tissue
Annotation
Information integration
Testing
In situ hybridization
Correspondence analysis
Embryo
Messenger RNA
Module
Classification system
Texture
Gene

Keywords

  • Association Classification
  • Drosophila Developmental Stage
  • MCA-based Classification Model

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

Cite this

Meng, T., & Shyu, M-L. (2011). Automatic annotation of drosophila developmental stages using association classification and information integration. In Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011 (pp. 142-147). [6009536] https://doi.org/10.1109/IRI.2011.6009536

Automatic annotation of drosophila developmental stages using association classification and information integration. / Meng, Tao; Shyu, Mei-Ling.

Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. 2011. p. 142-147 6009536.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Meng, T & Shyu, M-L 2011, Automatic annotation of drosophila developmental stages using association classification and information integration. in Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011., 6009536, pp. 142-147, 12th IEEE International Conference on Information Reuse and Integration, IRI 2011, Las Vegas, NV, United States, 8/3/11. https://doi.org/10.1109/IRI.2011.6009536
Meng T, Shyu M-L. Automatic annotation of drosophila developmental stages using association classification and information integration. In Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. 2011. p. 142-147. 6009536 https://doi.org/10.1109/IRI.2011.6009536
Meng, Tao ; Shyu, Mei-Ling. / Automatic annotation of drosophila developmental stages using association classification and information integration. Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. 2011. pp. 142-147
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