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A general approach for increasing the marker density in genetic linkage maps involves the identification of more markers and the integration of several linkage maps.
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Empty matrices help dealing with maps involving the zero vector space.
As described, the GEM Initiative evidence maps involved the generation of 129 clinical questions and independent review of tens of thousands of abstracts and thousands of full-text articles by the 3.5 EFT project staff.
These maps involve the player trying to survive within the parameters of the map.
Digital soil mapping involves the use of auxiliary data to assist in the mapping of soil classes.
Digital soil mapping involves the use of ancillary data (e.g. proximal and remotely sensed) as surrogates for soil information to produce maps of soil type or classes.
As association mapping involves the screening of large numbers of plant lines, specific and accurate high-throughput phenotyping (HTP) methods are needed.
LHZ mapping involves the discrimination of identical areas of varying hazard levels based on degrees of actual or potential damage [77].
SFP mapping involves the detection of probes revealing putative SFP whose behavior as Mendelian markers is then evaluated in segregating populations.
Mapping involves the development and use of an algorithm (or algorithms) to predict the primary outputs of generic preference-based outcome measures, i.e. health utility values, using data on other indicators or measures of health.
QTL mapping involves the analysis of a population(s) where individual plants, lines or families within the population have been characterized for a set of well-distributed molecular marker polymorphisms as well as for one or more quantitative traits.
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