News Column

Research Data from Virginia Tech Update Understanding of Allergies

May 27, 2014

By a News Reporter-Staff News Editor at Information Technology Newsweekly -- A new study on Allergies is now available. According to news reporting from Blacksburg, Virginia, by VerticalNews journalists, research stated, "Accurately identifying and eliminating allergens from biotechnology- derived products are important for human health. From a biomedical research perspective, it is also important to identify allergens in sequenced genomes."

The news correspondents obtained a quote from the research from Virginia Tech, "Many allergen prediction tools have been developed during the past years. Although these tools have achieved certain levels of specificity, when applied to large-scale allergen discovery (e. g. at a whole-genome scale), they still yield many false positives and thus low precision (even at low recall) due to the extreme skewness of the data (allergens are rare). Moreover, the most accurate tools are relatively slow because they use protein sequence alignment to build feature vectors for allergen classifiers. Additionally, only web server implementations of the current allergen prediction tools are publicly available and are without the capability of large batch submission. These weaknesses make large-scale allergen discovery ineffective and inefficient in the public domain. We developed Allerdictor, a fast and accurate sequence-based allergen prediction tool that models protein sequences as text documents and uses support vector machine in text classification for allergen prediction. Test results on multiple highly skewed datasets demonstrated that Allerdictor predicted allergens with high precision over high recall at fast speed."

According to the news reporters, the research concluded: "For example, Allerdictor only took similar to 6 min on a single core PC to scan a whole Swiss-Prot database of similar to 540 000 sequences and identified < 1% of them as allergens."

For more information on this research see: Allerdictor: fast allergen prediction using text classification techniques. Bioinformatics, 2014;30(8):1120-1128. Bioinformatics can be contacted at: Oxford Univ Press, Great Clarendon St, Oxford OX2 6DP, England. (Oxford University Press -; Bioinformatics -

Our news journalists report that additional information may be obtained by contacting H.X. Dang, Virginia Technical, Dept. of Biol Sci, Blacksburg, VA 24061, United States.

Keywords for this news article include: Antigens, Virginia, Genetics, Allergens, Allergies, Blacksburg, Immunology, United States, Allergy Medicine, North and Central America

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Source: Information Technology Newsweekly