The advantages of using population-based datasets, such as the MDC, include the size of the dataset and the guaranteed accuracy of a validated dataset.
There are significant advantages of using population-based datasets such as MDC, including the size of the dataset, the guaranteed accuracy of a validated dataset and the anonymous nature of the results therein.
There are significant advantages of using population-based datasets such as the MDC, including the size of the dataset, the guaranteed accuracy of a validated dataset [ 49, 50] and the anonymous nature of the results therein.
Since the network reconstruction process is organism specific and is based on different datasets such as annotated genome sequence, high-throughput network-wide datasets and bibliomic data on the detailed properties of individual network components [ 15], it is not easy for biologists to efficiently construct the integrated cellular network by traditional genetic/molecular manipulation.
In addition, context-specific networks can be generated based on high-throughput datasets such as transcriptomics [ 10], proteomics [ 11] and metabolomics [ 12].
Developed by researchers at Caltech, Stanford, the University of California, Los Angeles, and Rice, the technology is based on the idea that datasets, such as those that represent images or signals, often contain a significant amount of structure.
In the experiments, the proposed framework has achieved great performance for face recognition and verification with high speed and high accuracy, based on the public available datasets such as the Labeled Face in the Wild dataset and the AT&T database of faces.
Component-types are used to group components sharing a common base set of input/output datasets such as those encapsulating code for different versions of the same tool or different tools performing similar functions.
As such, it is an improvement on current methods and lays the basis for further refinements using more extensive datasets, such as community based diagnoses.
To represent past regional hydrology and seasonal hydrological extreme events, we believe it is feasible to use some large precipitation datasets such as i) climate reanalysis, which is mainly based on a land surface component, and ii) datasets based on merged products.
