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The free software package described here was designed to help neurophysiologists process and view recorded data in an efficient and user-friendly manner.
The software package described here built upon earlier implementations which were developed using the Matlab Image Acquisition Toolbox.
The intervention was only targeted to identify TB and patients with other chronic respiratory diseases were referred to services beyond the scope of the package described here.
The PINE-SPARKY software package described here provides a graphical interface for reviewing possible assignments in the context of their experimental basis (peaks in multidimensional NMR spectra) and for choosing among them.
As a means for visualizing the spectral data, picked peaks and spin system assemblies underlying these assignments, we have developed the standalone software package described here, ADAPT-NMR Enhancer.
The PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) software package described here bridges this gap and is meant to be used with an automated resonance assignment package such as PINE-NMR introduced earlier by our group (Bahrami et al., 2009).
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If the instructions on the package of diazinon vary from those described here, follow the package instructions instead of following these.
The different software packages for thermodynamics and diffusion are described here only briefly.
> -wrap-foot> We have prepared an R (23) package, coloc, which implements the tests described here and is available from CRAN (http://cran.r-project.org).org
The different actors described here read the packaging differently in some ways: for instance, national and regional distributors said that customers should look carefully at the packaging to check expiry dates and the like, whereas wary cattle owners pointed out that such packaging could easily be switched or falsified.
Finally, we are currently extending the bioinformatic analyses described herein with the development of a free, post-annotation software package for the execution of the full supragenome analysis pipeline described here.
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