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- Gustafsson, Mats, et al.
(författare)
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Physical bounds and sum rules in scattering and antenna theory
- 2009
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Ingår i: Electromagnetics in Advanced Applications, 2009. ICEAA '09. International Conference on. ; , s. 600-603, s. 600-603
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Konferensbidrag (refereegranskat)abstract
- The objective of this paper is to review some recently developed sum rules and physical bounds in scattering and antenna theory. The sum rules are based on identities for Herglotz functions that relate the quantity of interest integrated over all wavelengths with its static polarizability dyadics. They are transformed to physical bounds by applying variational principles for the polarizability dyadics together with various estimates of the integrals. The theoretical findings are exemplified by numerical results for several configurations.
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- Soeria-Atmadja, Daniel, et al.
(författare)
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Computational detection of allergenic proteins attains a new level of accuracy with in silico variable-length peptide extraction and machine learning
- 2006
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 34:13, s. 3779-3793
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Tidskriftsartikel (refereegranskat)abstract
- The placing of novel or new-in-the-context proteins on the market, appearing in genetically modified foods, certain bio-pharmaceuticals and some household products leads to human exposure to proteins that may elicit allergic responses. Accurate methods to detect allergens are therefore necessary to ensure consumer/patient safety. We demonstrate that it is possible to reach a new level of accuracy in computational detection of allergenic proteins by presenting a novel detector, Detection based on Filtered Length-adjusted Allergen Peptides (DFLAP). The DFLAP algorithm extracts variable length allergen sequence fragments and employs modern machine learning techniques in the form of a support vector machine. In particular, this new detector shows hitherto unmatched specificity when challenged to the Swiss-Prot repository without appreciable loss of sensitivity. DFLAP is also the first reported detector that successfully discriminates between allergens and non-allergens occurring in protein families known to hold both categories. Allergenicity assessment for specific protein sequences of interest using DFLAP is possible via ulfh@slv.se.
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