The differentially expressed genes (DEGs) (P <0.001, and fold change ≥1.5 log2) were examined by IPA (IPA, Ingenuity Systems, http://www.ingenuity.com) to identify the canonical pathways by mapping these transcripts to the IPA program and to gain further insight into the molecular functions of these genes.
A report commissioned by the Pew Charitable Trust last year found "compelling" evidence in support of expanding ranger and IPA programs.
For pathway and biological function analysis of significantly differentially expressed genes, the Ingenuity Pathway Analysis (IPA) program was used.
Functional analyses were also made using the Ingenuity Pathway Analysis (IPA) program, looking at general regulation of signaling pathways not discriminating between up- and downregulation of specific genes.
The Ingenuity Pathways Analysis (IPA) program permitted the determination of significant networks, top functions and canonical pathways associated with the differentially expressed genes (IPA 5.0, Ingenuity Systems Inc., USA).
Protein networks for analyzing shortest pathways between the identified proteins were built by MetaCore™ (Gene GO) software and Ingenuity Pathways Analysis (IPA) program (Ingenuity Systems) for identifying molecular partners involved in particular disease.
The most important limitation concerns the Ingenuity Pathway Analysis (IPA) program itself.
Network and pathway analyses were generated using the Ingenuity Pathways Analysis (IPA) program (Ingenuity® Systems [ 13]).
The IPA program was used to gain insight into the potential functional implications of the spaceflight-induced changes in gene translation profiles in 48A9 cells.
The Ingenuity Pathway Analysis (IPA) program generated bioinformatics data sets including functional groups (gene ontology; GO) and gene networks for genes containing amino acid changes in SL chicken.
By using the IPA program (http://www.ingenuity.com/), bioinformatics aspects of differentially expressed genes during ILTV infection were analyzed for the relevance of gene functionalities and gene networks.
