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This article is part of the supplement: Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology

Open Access Proceedings

UPS 2.0: unique probe selector for probe design and oligonucleotide microarrays at the pangenomic/ genomic level

Shu-Hwa Chen1, Chen-Zen Lo1, Sheng-Yao Su1, Bao-Han Kuo1, Chao A Hsiung2 and Chung-Yen Lin1234*

Author affiliations

1 Institute of Information Science, Academia Sinica, No. 128 Academia Rd., Sec. 2, Taipei 115, Taiwan

2 Division of Biostatistics and Bioinformatics, National Health Research Institutes. No. 35 Keyan Rd. Zhunan, Miaoli County 350, Taiwan

3 Institute of Fisheries Science, College of Life Science, National Taiwan University, No. 1, Roosevelt Rd. Sec 4, Taipei, Taiwan

4 Research Center of Information Technology Innovation, Academia Sinica, No. 128 Yan-Chiu-Yuan Rd., Sec. 2, Taipei 115, Taiwan

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Citation and License

BMC Genomics 2010, 11(Suppl 4):S6  doi:10.1186/1471-2164-11-S4-S6

Published: 2 December 2010

Abstract

Background

Nucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets.

Results

Algorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,Unique probe within a group,Unique probe in a specific Unigene set,Unique probe based onthe pangenomic level, and Unique Probe in the user-defined genome/transcriptome, are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments.

Conclusions

The UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at http://array.iis.sinica.edu.tw/ups/. webcite

Screen cast: http://array.iis.sinica.edu.tw/ups/demo/demo.htm webcite