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miRNA expression data has recently been generated for some of the HapMap CEU and YRI cell lines [ 43].
While all fields of genetic analysis have benefited from these technological advances, population genetics has been especially affected as hundreds or even thousands of whole-genome sequences have been generated for some organisms (e.g., 1000 Genomes Project Consortium 2010; Pool et al. 2012; Long et al. 2013; Huang et al. 2014; Wallberg et al. 2014).
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However, we have found that incorrect solutions are generated for some data.
Using the structure-based approach, we obtained selective pharmacophores for both agonist and antagonist ligands of the NRs, but since the recalls were correlated with the availability and the diversity of PDB structures, no selective pharmacophore could be generated for some datasets.
Finally, InChIs cannot be generated for some classes of compounds, for instance polymers.
Furthermore, MOs that target 5'-UTR were generated for some selected DUB genes to test their specificity.
A number of molecular marker maps have been generated for Prunus species, some with reasonably complete coverage of all chromosomes.
Stem cell grafts have been generated for canine transplantation strategies with some myelinating cells types more thoroughly studied than in mice or humans [14], [15].
In some instances mouse models have been generated for in vivo analysis.
Scores have thus far been generated for just more than 100,000 foods.
Variant and gene lists have been generated for different sources.
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