We also used DAVID in order to perform a gene ontology enrichment analysis in the obtained clusters.
The individual genes that encode the relevant proteins were also subjected to DAVID functional analysis in order to group proteins sharing common molecular functions, cellular compartment or biological processes into annotation clusters (see supplementary material Tables S1 S3 for a list of all proteins significantly changed between mutant and wild type cartilage).
We identified genes located within the top 0.1% of the windows for each statistic and these genes were then annotated using the DAVID database in order to select genes that may potentially be involved in the pigmentation pathway.
DAVID was applied in order to conduct the gene ontology analysis, and the Kyoto Encyclopedia of Genes and Genomes was used to carry out the pathway enrichment analysis.
In order to extend the above results, we employed DAVID v6.7 (http://david.abcc.ncifcrf.gov/) to perform functional ontology enrichment analyses (i.e., biological processes, molecular functions, cellular components, and pathways) for 11 significantly identified proteins (Table 6).
In order to explore common themes of affected genes we employed DAVID (Database for Annotation, Visualization and Integrated Discovery, NIAID), an on-line resource that identifies enrichment of genes with specific gene ontology (GO) terms [27], [28].
In order to reduce the redundancy, a functional annotation clustering was performed with DAVID tool.
Whereas David asks a series of test questions in order to elicit this one word, Alex asks three successive test questions, each to elicit a different word.
Lists of significant genes were screened by the DAVID 6.7 annotation tools [ 40, 41] in order to find over-represented biological themes.
In order to evaluate our method further, we perform functional enrichment analysis using DAVID [ 26, 27] on the target sets of predicted drugs.
