However, many of the proteins in our database are homologous to many others, and so the database is not made of independent sequences.
All known animal miRNAs appear to target regions in the 3' UTRs of mRNAs [ 2, 23- 28], and so the database was limited to 3' UTR sequences.
Since April 2002, the NHSLA handled every clinical negligence claim in the NHS, and so the database from that date is all-inclusive.
In this case, we did not search for more protein sequences because we did not find any previous sequence-identity region between the proteins from the ID and human ones, so the database remained consisting of a total of 25 protein sequences.
SM, RI, TM, MK, and SO built the database.
In a smart grid, the data volume is high and so the performance and flexibility of the database are important properties for real-time monitoring and demand-side management in a smart grid [31, 32].
Furthermore, the low number of ADEs in this study means that it is difficult to generalize these results: ADEs are rare and so the construction of inter-hospital databases may provide more robust results.
However RCTs make up only a very small proportion of all the articles included in bibliographic databases, and so the problem for systematic reviewers has been to devise a search strategy which is sensitive enough to find all the RCTs, but specific enough not to bury them in a large number of other unwanted retrievals needing to be manually excluded.
These last four pathogens have not got any sequence-identity region between the proteins from the IDs and human ones, so the databases were not enlarged.
Participating general practitioners systematically and prospectively retrieve and enter clinical information on patients, including personal data, diagnoses, and prescriptions so that the database provides a longitudinal medical record for each patient.
We included both picking up box actions and putting down box actions, so that the database contained actions with similar (albeit opposite) kinematics with different goals; such stimuli have been useful in the development of computational models of action recognition (Barraclough, Keith, Xiao, Oram, & Perrett, 2009; Fleischer, Caggiano, Thier, & Giese, 2013).
