In this review, we first briefly explain the principles of the major methods, identify the assumptions behind them and pinpoint the limitations and possible pitfalls in applying them to real biological questions.
These data show that the results generated by the two methods identify the same functional gene categories to be differentially expressed.
Therefore, PPC adds further information regarding how the connectivity methods identify the connections.
Usually, global methods generate an autocorrelation parameter that defines the nature of the spatial pattern whereas local methods identify the specific locations of clusters, also known as hotspots.
The energy-based methods identify the binding site using model of energetics [ 3– 6], such as PocketFinder [ 5] and Q-SiteFinder [ 6].
In contrast, the P and C methods identify the largest numbers of putative Wnt pathway candidates that are not predicted by any other method.
If a conservative approach is taken, using only locomotor cost estimates for slow walking, for which our two methods identify the same set of taxa as endothermic, then the hypothesis that endothermy arose independently at least three times (in Sauropodomorpha, Tetanurae and Neornithes) and was lost once (in Coelurosauria) is favored.
Both methods identify the same single SNP pair having a prominent interaction plotted in the upper right corner.
More relevant to this present work, a number of prior methods identify the principal components of clinical data that are heritable, and characterize the components by linear combinations of clinical variables [ 19- 23].
Some methods identify the subset of computationally predicted miRNA targets with a positive correlation of expression as the more reliable targets [ 17– 17].
Range-based methods identify the maximal morphospace occupation of each group, and therefore are more sensitive to outliers and sample size bias.
