Toward a complete in silico, multi-layered embryonic stem cell regulatory network.

摘要: Recent efforts in systematically profiling embryonic stem (ES) cells have yielded a wealth of highthroughput data. Complementarily, emerging databases and computational tools facilitate ES cell studies further pave the way toward silico reconstruction regulatory networks encompassing multiple molecular layers. Here, we briefly survey databases, algorithms, software used to organize analyze high-throughput experimental data collected study mammalian cellular systems with focus on cells. The vision using heterogeneous reconstruct complete multilayered network is discussed. This review also provides an accompanying manually extracted dataset different types interactions from lowthroughput available at http://amp.pharm.mssm.edu/iscmid/literature. Pluripotent are derived inner mass developing embryo can be cultured indefinitely vitro. In vivo, mouse contribute all adult populations, including germ line. Under defined vitro conditions both human differentiate into numerous providing great promise for regenerative medicine. shown that ‘reprogrammed’ induced pluripotent (iPS) state simple combinations transcription factors. order harness exciting biomedical potential ES/iPS cells, responsible controlling pluripotency/selfrenewal as well as, commitment differentiation lineages, need characterized. Stem research increasingly employing biology approaches define ‘parts lists’ between parts their more differentiated progeny. How these interconnected gene signaling ultimately self-renewal unclear. Approaches aimed bridge gap among molecules, architectures, dynamics ‘explain’ phenotypic behavior infancy. To enable efforts, pipeline process couples has emerged. An example such outlined Figure 1. First, layers [for example: epigenomic, messenger RNA (mRNA), proteomic data] technologies. Second, extract biological knowledge out rich, complex but often, noisy datasets, advanced being developed. Moreover, methods capable synthesizing