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A combination of techniques reveals that aggregate forces from all enzymes active in the cytoplasm result in randomly fluctuating forces throughout the cell.
The ability to convert somatic cells to induced pluripotent stem cells has immense potential to further our understanding of development and disease mechanisms, and for cellular therapy. Before researchers can achieve these goals, they must expand current methodology to incorporate animal models and quantitative descriptions of the essential phenomena driving reprogramming.
A decade of advances in genome engineering technologies has enabled the editing of genome sequences much like one edits computer code; many more applications for precisely manipulating genome structure and function are on the horizon.
The decade since the launch of Nature Methods has been one of intense and dynamic development in biological research methods. We predict this will continue.
Our choice, among many candidates, of the ten areas of methods development with the most impact on biological research over the last decade. Visit Methagora to browse Nature Methods papers in some of these areas.
The CellNet platform, based on cell- and tissue-specific gene regulatory networks, is used to evaluate cells converted to a particular fate by various methods.
Much of our knowledge about biological systems has been obtained by examining ensembles of molecules. However, this has begun to change because of the unprecedented precision and clarity afforded by single-molecule measurements. The last decade has seen amazing advances in the resolution and complexity of these methods, making it possible to ask and answer entirely new types of biological questions.
The optogenetic revolution is transforming neuroscience. The dramatic recent progress in using light to both control and read out neural activity has highlighted the need for better probes, improved light delivery and more careful interpretation of results, which will all be required for optogenetics to fully realize its remarkable potential.
Efficiently cutting a target sequence to effect a desired change in the genome is one gene-editing task. Knowing where else in the genome a tool might have made its mark is quite another.
