Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
BMC Bioinformatics. 2012 May 23;13:107. doi: 10.1186/1471-2105-13-107.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
果蝇胚胎发生是研究得最好的动物发育系统之一，这个过程中的时空基因表达动态可以通过数字图像捕捉。对这些高通量图像的分析将为动物基因的功能、相互作用和网络提供新的见解，这些基因控制着发育。为了便于比较分析，已经开发了基于身体部位关键词和图像的基于网络的界面来进行图像检索。目前，时空基因表达模式的关键词注释是手动进行的。然而，这种手动实践并不能适应不断扩展的图像集。此外，基于表达模式的现有图像检索系统可以使用关键词变得更加准确。
在本文中，我们采用先进的数据挖掘和计算机视觉技术来解决注释和检索果蝇基因表达模式图像的关键挑战。为了提高图像注释和检索的性能，我们提出了集成空间信息和稀疏特征的表示，克服了先前方案的局限性。
我们进行了系统的实验研究，以评估与现有方法相比，所提出的方案的性能。实验结果表明，空间信息和稀疏特征的集成导致图像注释的性能一致提高，而对于检索任务，稀疏特征本身可以产生更好的结果。
