Interpretation of omics data analyses

Guidelines for the design, analysis and interpretation of 'omics' data: focus on human endometrium.

BACKGROUND 'Omics' high-throughput analyses, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, are widely applied in human endometrial studies. Analysis of endometrial transcriptome patterns in physiological and pathophysiological conditions has been to date the most commonly applied 'omics' technique in human endometrium. As the technologies improve, proteomics hol...

Functional Interpretation of Omics Data by Profiling Genes and Diseases Using MeSH–Controlled Vocabulary

An Algorithm for Modeling and Interpretation of Seismoelectric Data

Generally speaking, seismoelectric modeling is a prospecting method based on seismic and electromagnetic waves, in which waves generated by a seismic source at the boundary of the two environments generate a relative fluid-solid motion formed as a result of antagonism between the elastic properties of the environment with the saturated fluid. This research has as its objective, a study of the e...

Epigenome-wide Association Studies and the Interpretation of Disease -Omics

Epigenome-wide association studies represent one means of applying genome-wide assays to identify molecular events that could be associated with human phenotypes. The epigenome is especially intriguing as a target for study, as epigenetic regulatory processes are, by definition, heritable from parent to daughter cells and are found to have transcriptional regulatory properties. As such, the epi...

Quantifying periodicity in omics data

Oscillations play a significant role in biological systems, with many examples in the fast, ultradian, circadian, circalunar, and yearly time domains. However, determining periodicity in such data can be problematic. There are a number of computational methods to identify the periodic components in large datasets, such as signal-to-noise based Fourier decomposition, Fisher's g-test and autocorr...