Nexus expression software

Manufactured by BioDiscovery

Sourced in United States

Nexus Expression software is a bioinformatics tool designed for the analysis and visualization of gene expression data. The software provides a range of analytical functionalities to process and interpret large-scale gene expression datasets.

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Lab products found in correlation

Imagene 8, by BioDiscovery (1 mentions) Nimblescan software, by Roche (1 mentions)

3 protocols using nexus expression software

Transcriptomic Analysis of YAP1-Overexpressing Huh7 Cells

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High-quality RNA from 4 independent Huh7 cell cultures transfected with 400 ng of YAP1 cDNA and 4 control cell lines transfected with vector alone, were used to obtain fluorescently labeled complementary double-stranded DNA (cDNA). cDNA was labeled with Cy3 or Cy5, hybridized using Agilent In situ Hybridization Kit-plus (Agilent Technologies, Wilmington, DE). Microarray experiments were made with Agilent Human G4131F 4 × 44 K. Fluorescence intensities were measured using ImaGene 8.0 software and analyzed by Nexus Expression software (Biodiscovery, El Segundo, CA). To select the spot subsets, we followed the criterion of minimum variance in quadruplicate fluorescence ratio measurements, when the fluorescence signal was higher than 0.3% of the measurable total signal dynamics range above background in both channels of the hybridization. For normalization, the intensity of each spot was divided by average intensity of housekeeping genes. Genes showing more than 1.5- fold difference compared to median expression value in more than 4 arrays, were selected for cluster analysis. The algorithm based on Pearson correlation coefficients was used for hierarchical cluster analysis. K-mean clustering analysis, and visualization of analyzed data were performed as described [64 (link)].

Simile M.M., Latte G., Demartis M.I., Brozzetti S., Calvisi D.F., Porcu A., Feo C.F., Seddaiu M.A., Daino L., Berasain C., Tomasi M.L., Avila M.A., Feo F, & Pascale R.M. (2016). Post-translational deregulation of YAP1 is genetically controlled in rat liver cancer and determines the fate and stem-like behavior of the human disease. Oncotarget, 7(31), 49194-49216.

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Comparative Genomic Hybridization for Genetic Profiling

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Patient genomic DNA and matched control DNA from a normal healthy male were isolated from peripheral blood nucleated cells collected in an EDTA tube. Then, 1 μg of each sample were verified by agarose gel electrophoresis. The aCGH analysis was performed using a Chromosome Y Tiling 385K Array (Roche NimbleGen Systems Inc., Madison, WI), with average probe spacing of ∼20 Kb and probe length of 50–75 mer. Genomic DNA was sonicated to fragments of 600–2000 bp, and then re-purified with DNA labeling and hybridization. The fragmented genomic DNA from patients and matched controls were differentially labeled with the fluorescent cyanine-5 (Cy5) and cyanine-3 (Cy3). Specimen labeling, array hybridization, washing, and scanning were performed at NimbleGen Service Laboratory (Iceland) and array image analysis and data normalization were performed using NimbleScan software (Roche Diagnostics). The normalized data were then processed using Nexus Expression software (BioDiscovery, Inc., El Segundo, CA, USA).

Lan K.C., Wang H.J., Wang T.J., Lin H.J., Chang Y.C, & Kang H.Y. (2022). Y-chromosome genes associated with sertoli cell-only syndrome identified by array comparative genome hybridization. Biomedical Journal, 46(2), 100524.

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Differential Gene Expression in HCV Infection

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After a robust multi-array average (RMA) procedure and quantile normalization, the probes were filtered using BioDiscovery’s Nexus Expression software. Probes with a variance less than 0.2 and intensity less than 4.0 were removed. Differential expression of HCV-infected versus naive cells in vitro was evaluated via two-sample Student’s t-test, using a threshold of P < 0.05 after Bonferoni correction for multiple hypotheses. Under these conditions, 893 genes were differentially regulated in vitro. Patient-to-patient differences required a more stringent test for the in vivo samples in order to reduce variability. We therefore carried out a two-sample Student’s t-test using a threshold of P < 0.01 after Bonferoni correction for multiple hypotheses and 1.5-fold change. Under these conditions, a similar-sized group of 1,259 genes were found to be differentially regulated in vivo.

Levy G., Habib N., Guzzardi M.A., Kitsberg D., Bomze D., Ezra E., Uygun B.E., Uygun K., Trippler M., Schlaak J.F., Shibolet O., Sklan E.H., Cohen M., Timm J., Friedman N, & Nahmias Y. (2016). Nuclear receptors control pro-viral and antiviral metabolic responses to hepatitis C virus infection. Nature chemical biology, 12(12), 1037-1045.

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