
Network genomics is an emerging area of bioengineering which models the influence of genes (hence, genomics) in the context of a larger biomolecular system or network. A biomolecular network is a comprehensive collection of molecules and molecular interactions that regulate cellular function. Molecular interactions include physical binding events between proteins and proteins, proteins and DNA, or proteins and drugs, as well as genetic relationships dictating how genes combine to cause particular phenotypes. Thinking about biological systems as networks goes hand-in-hand with our ability to experimentally measure and define biomolecular interactions at large scale. Once we have catalogued all of the interactions present in a network, we may begin to ask questions such as: How many different molecules are bound by a typical protein? What is the topological structure of the network? How are signals transmitted through the network in response to internal and external events? Which parts of the network are evolutionarily conserved across species, and which parts differ? Perhaps most importantly, we can begin to use the interaction network as a storehouse of information from which to extract and construct computer-based models of cellular processes and disease.
Systems Biology, Amino Acid Motifs, Genes, Fungal, Computational Biology, Galactose, Nucleic Acid Hybridization, Genomics, Saccharomyces cerevisiae, Models, Biological, Evolution, Molecular, Fungal Proteins, Gene Expression Regulation, Genes, Bacterial, Animals, Humans
Systems Biology, Amino Acid Motifs, Genes, Fungal, Computational Biology, Galactose, Nucleic Acid Hybridization, Genomics, Saccharomyces cerevisiae, Models, Biological, Evolution, Molecular, Fungal Proteins, Gene Expression Regulation, Genes, Bacterial, Animals, Humans
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
