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Run by NIH's National Center for Biotechnology Information (NCBI), the database can be searched by condition, test, gene, and lab and includes information such as whether the test sequences the entire gene for mutations or looks for specific errors.
All of these sub-processes are vulnerable for specific errors and consequently may result in false memories.
The algorithm has a hierarchical structure and allows for specific errors in names and dates of birth.
This overview has shown that memory formation comprises at least three different sub-processes, all of which are vulnerable for specific errors and, consequently, may result in false memories: encoding [ 28, 30, 35, 78, 85, 99, 110, 111], consolidation [ 20, 21, 58- 62, 64, 75, 78] and retrieval of the learned material [ 2, 97, 102, 112- 115].
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Such an approach would enable a researcher to determine if coded error feedback may be particularly useful for specific error types.
Both would be essential to qualify and validate the method and to control for specific error sources such as the magic angle effect [7].
The results provide a springboard for the deeper consideration of specific errors types, their origins within medical training and potential educational strategies aimed at reduction of error and improvement of patient outcomes.
When probabilistic error functions for specific fault origins are known at the bit or signal level, knowledge about the unit of design and its environment allow the transformation of the bit-related error functions into characteristic higher layer representations, such as error functions for data words, Finite State Machine (FSM) state, macro-interfaces or software variables.
A further advantage of this model is that it corrects for various specific errors, e.g. translational frameshift and other output errors, by basing the ribosome reactivity upon production of functional enzymes and measuring those functions directly.
This study describes novel strategies to combine two widely used high-throughput sequencing technologies, Illumina and 454 RNAseq, in order to compensate for their specific errors and to produce accurate transcriptomes.
Finally, a relevant study on motifs that induce sequencing errors was undertaken by Allhoff et al. [ 12], who described a statistical framework for identifying sequence specific errors caused as a result of preceding bases, which they term context-specific errors (CSEs).
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