The two detector sets are used in a proportion-based classification method to detect unknown instances.
Our aim was to examine whether determination of the capillary haemoglobin A1c (HbA1c) is a reliable method for detecting unknown diabetes and poor glycaemic control in the ED.
Thus, our method can detect unknown disease causing genes by identifying the most disrupted expression modules in the global distance network.
Moreover, it illustrates that NGS data can be used very easily, without specific bioinformatics expertise, in order to obtain crucial information to develop specific TaqMan® qPCR methods, to detect unknown and unauthorized GMO in food and feed.
Moreover, this work can be seen as a case study to substantiate how the use of NGS data can offer an added value to easily gain access to sequence information needed to develop qPCR methods to detect unknown andunauthorized GMO in food and feed.
Our method detects the previously described strata without generating a plethora of segments of unknown significance, as is the case with a previous segmentation-only method (Kelkar et al. 2009) (supplementary fig. S1, Supplementary Material online).
New techniques such as gene chips/biosensors or VIDISCA (Virus Discovery-cDNA-AFLP) method are valuable for detecting unknown viruses (Lia van der Hoek, University of Amsterdam, Amsterdam, the Netherlands).
As such, the method is also suitable for detecting unknown substances, provided they contain the targeted portion of the molecular structure.
RNA-Seq method can further be used to detect unknown genes, discover new transcripts, and accurately identify the variable shear loci and cSNP and UTR region [ 26].
Thus, generalization of the detection methods is crucial in order to be able to detect unknown malware before its execution.
