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A number of studies have examined the problems of tumor classification: class discovery, the problem of defining a number of classes of tumors using the data from a DNA chip, and class prediction, the problem of accurately classifying an unknown tumor, given expression data from the unknown tumor and from a learning set.
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This makes Bayesian inference applicable to a wide range of diagnostic challenges in the field of chance discovery, including the problem of disputed authorship that arises in electronic commerce, counter-terrorism and other forensic applications.
In other words, Shor's remarkable result rests on the discovery that the problem of factoring reduces to the problem of finding the period of a certain periodic function \ f: Z_{n} \rightarrow Z_{N}\), where \(Z_{n}\) is the additive group of integers mod \(n\) (Note that \(f(x) = y^{x}\ \textrm{mod}\ N\) so that \(f(x+r) = f(x)\) if \(x+r \le n\).
Motif discovery is the problem of finding approximately repeated patterns in unaligned sequence data.
Underlying our approach, we consider motif discovery as the problem of finding the best gapless local multiple sequence alignment using the sum-of-pairs (SP) scoring scheme.
In this commentary we provide an overview of the challenges that arise from applying molecular modeling tools developed and commonly used for pharmaceutical discovery to the problem of predicting the potential toxicities of environmental chemicals.
A significant advantage of this approach is that it bypasses the conventional SNP discovery phase, ameliorating the problem of ascertainment bias and allowing for the scoring of SNPs without regard to a priori selection based on minor allele frequency.
For instance, we observed no marked increase in the use of these designs until some years after the discovery of GAM-related problems; a peak in use occurred 2 years after the discovery of the problems of concurvity (analog to collinearity for nonlinear relationships).
Neighbor discovery is defined as the problem of identifying all nodes within the communication range of a sensor device.
Transcriptome assembly, also known as novel transcript discovery or reconstruction, is the problem of assembling the full length transcript sequences from the RNA sequencing data.
Related to this work with partial differential equations was his discovery of a solution to the problem of distribution of heat in a solid with a variable boundary temperature, now known as Duhamel's principle.
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