Analysis of other genetic risk factors, epigenetic markers, and other modulatory influences will require validated clinical and molecular phenotyping based on disease-linked attributes and mechanistic interpretation based on detailed understanding of the underlying pathobiology.
These findings, taken together, suggest that our proposed reclassification is not merely a mathematical model function; rather it is tracking real underlying molecular sarcoma "phenotypes" based on tissue differentiation lines.
Then, it is also possible to predict the molecular, cellular and organismal phenotypes based on the functional states of the CRMs and their variations among individuals and species, given the recent indication of the importance of CRMs in determining the phenotypes of organism [ 96– 104].
Researchers and breeders have increasingly been adopting molecular markers to identify genomic regions influencing traits and to select for desirable phenotypes based on identified marker-trait associations [ 4- 6].
We classified the phenotypes based on Additional file 6 and further confirmed by in situ staining using different molecular markers at different stages (Additional file 8).
A molecular classification has replaced the former phenotype based one and unified the diverse phenotypes under a single precisely defined disorder [ 16, 22, 26].
Recent studies have revealed that there are several molecular phenotypes of breast cancer, based on receptor expression [2].
This technique is well suited to high-throughput whole genome detection of chromosomal gains and losses at high resolution, enabling rapid detection of homozygous loss, which allow molecular phenotyping of tumours based on the underlying abnormalities and the detection of amplicons, which may be associated with overexpression of oncogenes.
This was done by combining most informative canonical pathways identified using IPA, genes having the strongest association with the disease phenotype based on ANOVA analysis, and similarities to molecular patterns altered in other systemic inflammatory processes associated with endothelial dysfunction.
Many model systems lack species specific organized phenotype based gene sets to enable high throughput analysis of large molecular datasets.
