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Different data sources of (or methodologies to obtain) spatially distributed data have been explored for the first subset.
After the data have been explored visually, the next course of action is to quantify any observed behavior and to statistically test the hypotheses that were formulated earlier.
To address this problem, several possibilities to extend in time the empirical contact data have been explored [ 41].
Pregnancies complicated by low birth weight (LBW), spontaneous preterm delivery, and small for gestational age (SGA) infants have been shown to have reduced antioxidant and increased pro-oxidant levels, although no correlational data have been explored to establish this link [ 8].
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In this work, the usefulness of two complementary techniques, mean-field density functional theory (MF-DFT) and micro-computerized X-ray tomography (micro-CXT), for aiding interpretation of ambiguous mercury porosimetry data has been explored.
Identification of bias in short-read data has been explored in other work, such as that of Dohm et al. [10] and Harismendy et al. [11].
miRanda data has been explored for LHON; all genes are found to be under regulation of miRNA.
The concept of conducting a causality analysis based on genetic marker data has been explored by several authors [ 13- 22].
Analysis concentrating on the effect of probe sequence on gene expression data has been explored, but the majority of published data has focused on 25mer probes utilized on Affymetrix chips.
Liu et al. [ 5], whose data has been explored here, found that <2%% of all the putative LncRNAs they found in A. thaliana are conserved across the plant kingdom.
RNA-Seq technology, with its digital gene expression data, has been explored as a quantitative method to analyze differential gene expression between different physiological states of a given organism.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com