12,881 research outputs found
Next-generation sequencing: applications beyond genomes.
The development of DNA sequencing more than 30 years ago has profoundly impacted biological research. In the last couple of years, remarkable technological innovations have emerged that allow the direct and cost-effective sequencing of complex samples at unprecedented scale and speed. These next-generation technologies make it feasible to sequence not only static genomes, but also entire transcriptomes expressed under different conditions. These and other powerful applications of next-generation sequencing are rapidly revolutionizing the way genomic studies are carried out. Below, we provide a snapshot of these exciting new approaches to understanding the properties and functions of genomes. Given that sequencing-based assays may increasingly supersede microarray-based assays, we also compare and contrast data obtained from these distinct approaches
Z-stability and finite dimensional tracial boundaries
We show that a simple separable unital nuclear nonelementary Cā-algebra whose tracial state space has a compact extreme boundary with finite covering dimension admits uniformly tracially large order zero maps from matrix algebras into its central sequence algebra. As a consequence, strict comparison implies Z-stability for these algebras
Counteracting systems of diabaticities using DRAG controls: The status after 10 years
The task of controlling a quantum system under time and bandwidth limitations
is made difficult by unwanted excitations of spectrally neighboring energy
levels. In this article we review the Derivative Removal by Adiabatic Gate
(DRAG) framework. DRAG is a multi-transition variant of counterdiabatic
driving, where multiple low-lying gapped states in an adiabatic evolution can
be avoided simultaneously, greatly reducing operation times compared to the
adiabatic limit. In its essence, the method corresponds to a convergent version
of the superadiabatic expansion where multiple counterdiabaticity conditions
can be met simultaneously. When transitions are strongly crowded, the system of
equations can instead be favorably solved by an average Hamiltonian (Magnus)
expansion, suggesting the use of additional sideband control. We give some
examples of common systems where DRAG and variants thereof can be applied to
improve performance.Comment: 7 pages, 2 figure
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