Title :
Database to Dynamically Aid Probe Design for Virus Identification
Author :
Lin, Feng-Mao ; Huang, Hsien-Da ; Chang, Yu-Chung ; Tsou, Ann-Ping ; Chan, Pak-Leong ; Wu, Li-Cheng ; Tsai, Meng-Feng ; Horng, Jorng-Tzong
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Jhongli
Abstract :
Viral infection poses a major problem for public health, horticulture, and animal husbandry, possibly causing severe health crises and economic losses. Viral infections can be identified by the specific detection of viral sequences in many ways. The microarray approach not only tolerates sequence variations of newly evolved virus strains, but can also simultaneously diagnose many viral sequences. Many chips have so far been designed for clinical use. Most are designed for special purposes, such as typing enterovirus infection, and compare fewer than 30 different viral sequences. None considers primer design, increasing the likelihood of cross hybridization to similar sequences from other viruses. To prevent this possibility, this work establishes a platform and database that provides users with specific probes of all known viral genome sequences to facilitate the design of diagnostic chips. This work develops a system for designing probes online. A user can select any number of different viruses and set the experimental conditions such as melting temperature and length of probe. The system then returns the optimal sequences from the database. We have also developed a heuristic algorithm to calculate the probe correctness and show the correctness of the algorithm. (The system that supports probe design for identifying viruses has been published on our web page http://bioinfo.csie.ncu.edu.tw/.)
Keywords :
cellular biophysics; database management systems; diseases; genetics; health care; medical computing; microorganisms; molecular biophysics; proteins; animal husbandry; cross hybridization; database system; diagnostic chip design; dynamically aid probe design; economic losses; heuristic algorithm; horticulture; microarray approach; probe correctness; probe length; public health; severe health crises; typing enterovirus infection; viral genome sequences; viral infection; virus identification; Animals; Bioinformatics; Capacitive sensors; Databases; Genomics; Heuristic algorithms; Probes; Public healthcare; Temperature; Viruses (medical); Database; probe design; virus identification;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2006.874202