Alternative approaches to measure age-specific contact patterns directly through diary-based methods are currently being explored using recently collected contact pattern data [ 53- 56].
Most implementations of two-step genomic selection methods are currently based on single-trait analyses but multivariate approaches are emerging.
The GMOMETHODS detection methods are currently based on the polymerase chain reaction (PCR) technology and are grouped according to the specificity of the target sequence: Event-specific methods have the highest levels of specificity, as they target regions that are unique to each DNA integration event.
Different classification methods are currently available based on machine learning, e.g. SVM, neural networks, HMM, and Naive Bayes (NB), and several tools based on machine learning have been developed and released to the research community, e.g. RNAmicro [ 200], MiRFinder [ 201], ProMir [ 202], MiRRim [ 203], SSCprofiler [ 204], HHMMiR [ 205] and BayesMiRNAFind [ 206].
The classification of protein families is based on homologous relationships and several methods are currently available for clustering proteins into families [2], [3].
Several imputation methods are currently available, based on different statistical models.
Two primary methods are currently implemented for genotype calling: (i) a filtering method based on a fixed number of observed variant nucleotides and (ii) a probabilistic method based on posterior genotype probabilities.
