Abstract
Induced pluripotent stem cells have displayed great potential in disease investigation and drug development applications. However, selection of reprogramming factors in each cell type or disease state is both expensive and time consuming. To deal with this kind of situation, a fast computational framework was developed by optimize the reprogramming factors via the protein interaction network and gene functional profiles. It can be used to select reprogramming factors from millions of possibilities. It is anticipated that the novel approach will become a very useful tool for both basic research and drug development.
Keywords: Stem cells, Reprogramming factors, Protein interaction network, Gene functional profiles, Disease investigation, pluripotent stem cells, cDNA sequences, Yamanaka factors, Candidate pluripotency genes, STRING network, Dijkstra, ’, s algorithm, HGF-induced hepatomegaly, ESCs, c-Myc, Gene Ontology