Single-cell genomic technologies provide an unprecedented opportunity to deﬁne molecular cell types in a data-driven fashion, but present unique data integration challenges. Here we present UINMF, a computational tool designed to improve dataset integrations by leveraging unshared features.
The objective of our research program is to better understand and improve nitrogen (N) use efficiency in maize. One of these strategies was to study the impacts of environmental conditions, and allelic variation of the cytosolic glutamine synthetase enzyme on maize hybrid kernel production.
We release a 306-channel MEG-BCI data recorded at 1KHz sampling frequency during four mental imagery tasks (i.e. hand imagery, feet imagery, subtraction imagery, and word generation imagery). The current dataset is the only publicly available MEG imagery BCI dataset as per our knowledge.
As our climate changes, plants using different ways to convert CO2, sunlight, & water into food, known as photosynthetic pathways, will have to ‘migrate’ to new habitats to survive. This problem inspired the creation of a new data set that lists the photosynthetic pathway > 2400 Australian species.
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