J. Comput. Biol. - Nonadaptive algorithms for threshold group testing with inhibitors and error-tolerance.

Tópicos

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Resumo

A group test gives a positive (negative) outcome if it contains at least u (at most l) positive items, and an arbitrary outcome if the number of positive items is between thresholds l and u. This problem introduced by Damaschke is called threshold group testing. It is a generalization of classical group testing. Chen and Fu extended this problem to the error-tolerant version and first proposed efficient nonadaptive algorithms. In this article, we extend threshold group testing to the k-inhibitors model in which a test has a positive outcome if it contains at least u positives and at most k-1 inhibitors. By using (d + k - l, u; 2e + 1]-disjunct matrix we provide nonadaptive algorithms for the threshold group testing model with k-inhibitors and at most e-erroneous outcomes. The decoding complexity is O(n(u+k) log n) for fixed parameters (d, u, l, k, e).

Resumo Limpo

group test give posit negat outcom contain least u l posit item arbitrari outcom number posit item threshold l u problem introduc damaschk call threshold group test general classic group test chen fu extend problem errortoler version first propos effici nonadapt algorithm articl extend threshold group test kinhibitor model test posit outcom contain least u posit k inhibitor use d k l u e disjunct matrix provid nonadapt algorithm threshold group test model kinhibitor eerron outcom decod complex onuk log n fix paramet d u l k e

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