The phrase "analyzing data generated from" is correct and usable in written English.
You can use it when discussing the examination or interpretation of data that has been produced by a specific source or process.
Example: "The researchers are focused on analyzing data generated from the latest survey to identify trends in consumer behavior."
Alternatives: "examining data produced by" or "evaluating data derived from".
The predictions were similar to a computer fit of the release data using an empirical model often employed for analyzing data generated from this type of experimental design.
Empirically derived decay functions for keff were developed as a function of important meteorological parameters such as solar flux, temperature, humidity, and cloud cover for various land uses and locations by statistically analyzing data generated from a detailed chemistry mechanism run over a wide range of (typical) atmospheric conditions.
Although strictly speaking we can only make conclusion about these platforms, we believe that the key lessons learned in this study are instructive for analyzing data generated from other platforms.
She helped design numerous studies and analyzed data generated from such studies.
Dr. Zhou's research interest is to develop and apply novel statistical methods to better design biological and clinical studies related to cancer prevention, diagnosis and treatment and properly analyze data generated from such studies.
In contrast to databases dedicated to individual organisms, the PIGD provides comparative analyses of genomic data from five species, and in conjunction with the BLAST program, it will allow users to explore and analyze data generated from the PIGD efficiently.
Analyzed uniquely mapped reads used for analysis (Bold) To identify LRH-1 binding peaks, we used Model-based Analysis of ChIP-seq (MACS), which was designed to analyze data generated by short read sequencers such as from the SOLiD platform [ 15] to first estimate peak size and location, using BED files as an input.
At extremely large scale, research projects such as CloudBurst [23], CloudBlast [24], and Galaxy [25] provide standard environments and algorithms for analyzing large data generated from scientific experiments.
Despite the wealth of microarray time-series analysis procedures devised to date (such as [ 12, 13]), only simple linear regression methods are used in analyzing microarray data generated from most of the published ageing studies (for example, [ 3, 5, 7- 9]).
This study comparatively analyzed expression data generated from lung adenocarcinoma and adjacent normal tissue acquired from the same samples using LCM cell-sampling and bulk tissue-sampling.
Although GWAS Analyzer has thus far only been utilized to organize and analyze the data generated from one particular study, we are currently adapting the tool for use in similar studies.
