Current Challenges in Bioimage Database Design

Ambuj K. Singh, Arnab Bhattacharya, Vebjorn Ljosa
Department of Computer Science
University of California, Santa Barbara
Santa Barbara, CA 93106-5110
{ambuj, arnab, ljosa} [at] cs.ucsb.edu

Abstract

Information technology research has played a significant role in the high-throughput acquisition and analysis of biological information. The tremendous amount of information gathered from genomics in the past decade is being complemented by knowledge from comprehensive, systematic studies of the properties and behaviors of all proteins and other biomolecules. Understanding complex systems such as the nervous system requires the high-resolution imaging of molecules and cells and the analysis of these images in order to understand how distribution patterns (e.g., the localization of specific neuron types within a region of the central nervous system, or the localization of molecules at the subcellular level) change in response to stress, injury, aging, and disease. We discuss two kinds of bioimage data: retinal images and microtubule images. We argue that supporting effective access to them requires new database techniques for description of probabilistic and interpreted data, and analysis of spatial and temporal information. The developed techniques are being implemented in a publicly available bioimage database.
[PDF] [BibTex]
Ambuj K. Singh, Arnab Bhattacharya and Vebjorn Ljosa,
International Workshop on Bioimage Data Mining and Informatics, pp. 375-379, IEEE Computational Systems Bioinformatics Conference (CSB), Aug. 2005.
Node ID: 411 , DB ID: 213 , Lab: BIO , Target: Proceedings