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The articles in this series consider the range of levels at which transcription is controlled, the molecules involved and how the modes of regulation are adapted to particular types of gene or developmental contexts.
Recent technological advances are providing unprecedented opportunities to analyse the complexities of biological systems at the single-cell level. Various crucial biological phenomena are either invisible or only partially characterized when interrogated using standard analyses that average data across a bulk population of cells. However, high-throughput analyses of the genomes, transcriptomes and proteomes of single cells are providing novel and important insights into diverse processes such as development, gene-expression dynamics, tissue heterogeneity and disease pathogenesis.
The scale and complexity of genetic and genomic data are ever-expanding, requiring biologists to apply increasingly more sophisticated computational tools in the analysis, interpretation and storage of these data. This series contains articles that focus on the application of these software tools in genetics and genomics.
The articles in this series discuss recent views on regulatory elements, including their role in evolution and the function of chromatin modifications, as well as methods to study these important regions of the genome.
Genetics continues to play a crucial part in furthering our understanding of the basis of disease, from revealing biological pathways involved in pathogenesis to improving knowledge of the relative contributions of various genetic and environmental factors. The articles in this series focus on genetic studies of specific diseases or specific processes in pathogenesis.
An abundance of data and unprecedented computational power are allowing sophisticated biological models to be devised and tested. This series of articles examines how the coupling of genetics with disciplines such as engineering, statistics, physics and computational biology has enriched our understanding in areas that range from developmental patterning to genetic association analyses.