Sentence examples similar to in house visualization from inspiring English sources

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NAViGaTOR has evolved from an in-house visualization tool to a more versatile, comprehensive platform.

The OCT data was displayed using in-house visualization software developed in C++, which allowed extraction of an arbitrary oblique imaging plane from the 3D-OCT data set.

> -wrap-foot> standsands for Same Day Appointment: ROB or RGYN - 50 % - 50 % Patient tracker (PT) is an in-house built, visualization and touch-screen software installed on all computers at various locations of the clinic, such as the front desk, exam rooms, US room, and labs.

The best assembly, that is, the one containing a maximum number of full-length mitochondrial genes, was further improved manually, using an in-house software for visualization and analysis of a graph of alternative contig connections produced by Newbler.

It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways.

The Mutation Identification Pipeline (MIP) [ 6] together with dbCMMS and the in-house developed software Scout, for visualization of clinical variants, constitute a customized analytical platform designed to enable the adoption of MPS in a clinical setting, meeting health-care requirements and conforming to international guidelines [ 2– 4].

Positive cultures in the in-house bottles were detected by direct visualization of cloudy broth.

Comparative analysis was conducted using a multivariate correlation-based visualization application developed in-house.

In this manner, raw NuPop scores were converted to plots using in-house shell scripts for convenience of visualization.

Localization and visualization of individual activations by SPM were achieved by using BrainShow, in-house software (code by G. Galati) for visualization of fMRI data.

The web-based version of DeconSeq allows users to conduct decontamination using our in-house computing resources and provides additional visualizations such as coverage vs. identity plots to help users choose the best thresholds for their datasets.

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