Approximately 1800000 individual experimental observations were integrated into YeastNet2 from ten different types of functional genomics, proteomics and comparative genomics datasets by optimizing a total of ~155 free parameters to construct the whole network.
However, it should be noted that different types of functional genomics data yield different results, and that such evidence is often inadequate to the challenge of making comparisons over larger evolutionary distances, e.g. H. sapiens to C. elegans [22].
This interactome network constitutes a scaffold in which different types of functional genomics data can be integrated to ascertain the coordinated function of proteins under particular conditions.
Gitools types of analysis and visualization has shown to be very useful in a number of different types of projects ranging from cancer genomics [2], plant genomics [26], molecular biology [27][28][29], and evolutionary genomics [30].
In health care, the complexity of big data analysis also arises from combining different types of information, such as data from genomics, proteomics, cellular signaling, clinical research, and even environmental studies.
We characterise the different types of biological information of SH-SY5Y – genomics, transcriptomics and proteomics - and compare the relationships between them in terms of expression levels and variants.
Consistent results were obtained when interacting proteins were selected from the STRING database using a score that combines different types of evidence including physical interactions, comparative genomics approaches, and gene expression (data not shown).
Finally, we introduce current systems genetics approaches, known as genetic genomics, which combine different types of data such as expression and genetic data.
