The following dye combinations for probe generation were used for detection and data normalization: FAM (for the mRNAs of interest), HEX (for GAPDH, as a normalizer mRNA) and BHQ1 (non-fluorescent quencher) and ROX (reference).
Measurement of circulating miRNAs as biomarkers is associated with some special challenges, including those related to pre-analytic variation and data normalization.
The choice of l depends heavily on the number of available training patterns, N. Before feature selection techniques can be used, a preprocessing stage is necessary for "housekeeping" purposes, such as removal of outlier points and data normalization.
We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability.
Specific enzyme activity measurements without purification, in situ soluble protein expression monitoring, and data normalization are the powerful outputs of this methodology, thus enabling the accurate identification of improved protein variants during high-throughput screening by substantially reducing the occurrence of false negatives and false positives.
2.4, over multiple concurrent time-series streams at high-speed rates under DTW and data normalization.
In this section, we first describe the data preprocessing procedure, and then present the feature extraction and data normalization process.
In order to solve these problems, generally, data preprocessing before the training sample is very important and data normalization can make BP neural networks stronger.
(3) To aggregate data from multiple data sources and transform them into the application-dependent features, e.g. through data fusion, noise elimination, dimension reduction and data normalization.
Important aspects of the data processing by selecting only the bioactivity type of interest, dealing with duplicates, removing missing data and salt groups, descriptors calculation, and data normalization are handled in a very flexible and consistent manner.
In future work, we plan to study how to identify common local patterns of coevolving time-series sequences under DTW and data normalization in light of the outcomes obtained from this work.
