| Autor: | Zhong Guan, Xing Wang Deng, Hongyu Zhao, Ligeng Ma, Deyun Pan, Ning Sun, Kei-Hoi Cheung, Matthew E. Holford |
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| Rok vydání: | 2003 |
| Předmět: |
0106 biological sciences
Genetics 0303 health sciences biology Microarray analysis techniques Applied Mathematics Computational biology biology.organism_classification 01 natural sciences Biochemistry Computer Science Applications 03 medical and health sciences Metabolic pathway Static image Structural Biology Arabidopsis Gene expression DNA microarray Molecular Biology Gene 030304 developmental biology 010606 plant biology & botany Statistical hypothesis testing |
| Zdroj: | BMC Bioinformatics. 4:56 |
| ISSN: | 1471-2105 |
| DOI: | 10.1186/1471-2105-4-56 |
| Popis: | Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. |
| Databáze: | OpenAIRE |
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