
The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.
Epigenomics, Models, Molecular, 570, General Science & Technology, 1.1 Normal biological development and functioning, Biophysics, Bioinformatics and Computational Biology, Models, Biological, Chromosomes, Cell Line, Mice, Spatio-Temporal Analysis, Structural Biology, Models, Genetics, Animals, Humans, Epigenomics Gene regulation, Cell Nucleus, Genome, Information Dissemination, Systems Biology, Human Genome, 4D Nucleome Network, Computational Biology, 500, Molecular, Reproducibility of Results, Genomics, Biological Sciences, Stem Cell Research, Biological, Chromatin, Gene regulation, Molecular Imaging, Biochemistry and Cell Biology, Generic health relevance, Single-Cell Analysis, Goals, Biotechnology
Epigenomics, Models, Molecular, 570, General Science & Technology, 1.1 Normal biological development and functioning, Biophysics, Bioinformatics and Computational Biology, Models, Biological, Chromosomes, Cell Line, Mice, Spatio-Temporal Analysis, Structural Biology, Models, Genetics, Animals, Humans, Epigenomics Gene regulation, Cell Nucleus, Genome, Information Dissemination, Systems Biology, Human Genome, 4D Nucleome Network, Computational Biology, 500, Molecular, Reproducibility of Results, Genomics, Biological Sciences, Stem Cell Research, Biological, Chromatin, Gene regulation, Molecular Imaging, Biochemistry and Cell Biology, Generic health relevance, Single-Cell Analysis, Goals, Biotechnology
| 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). | 681 | |
| 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. | Top 0.1% | |
| 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 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
