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Finding information in complex data sets becomes increasingly difficult as the data grow, therefore data search and discovery needs to be timely, intuitive and precise.
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Our experiments have demonstrated that the Pfam domain data is a useful resource for protein function prediction and its advantages become increasingly obvious as the data grows more complete.
As demand for the data grew, so did the need to make them fit standard fisheries models.
As the interaction data grows, the inferred diseases could be more precise.
Increasing the proportion of animals genotyped will further increase the accuracy of genomic selection as the training data grows over time, particularly through genotyping of cows.
Such promiscuity trends might be detected by monitoring promiscuity over time as activity data grow.
The cloud is a particularly smart play for this level of (big) data because companies can scale as much as they need as the amount of data grows.
17 As the data sets grow larger, there is a point to not distribute them inside the VMI and instead deliver them separately.
The high-dimensional data suffers from the Curse of Dimensionality [10] which has two main implications: (1) As the dimensionality of data grows, the relative contrast among similar and dissimilar points becomes less [11].
But as the complexity of sequence data grew and the scale of sequencing expanded with improvements in technology, it quickly became obvious that other, more systematic solutions were necessary.
For big amount of data items, large range of key space, it is necessary to distribute data to multiple ZDB instances and scale the system as data growing.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com