Used AFFYMETRIX GeneChip 640 #164399 for sale

ID: 164399
Hybridization oven.
AFFYMETRIX GeneChip 640 is a state-of-the-art laboratory instrument and laboratory accessory that provides a powerful and cost-effective solution to genome-wide expression analysis. GeneChip 640 provides efficient sample processing, fast hybridization times, and high flow rates, allowing researchers to rapidly and reliably analyze microarray data. AFFYMETRIX GeneChip 640 is an automated instrument, requiring minimal user interaction and providing easy access to the sample information, analysis tools, and analysis results. The automated slide handler and onboard software enable user independence, allowing data analysis and visualization in a single step. The automation also allows researchers to perform multiple sample runs in a single instrument, helping to maximize productivity and efficiency. Furthermore, GeneChip 640 provides reproducible results with closely matched data sets, verifying the accuracy of the microarray experiments. AFFYMETRIX GeneChip 640 is equipped with a high-precision spotter for microarray slides, which accurately prints the spots and eliminates any manual spot placement. The sophisticated multichannel imaging system allows for rapid hybridization and high-quality, high-resolution images of the microarray slides. The on-board software also assists users by providing easy access to pre-made templates for running, quality checks for microarray slides, and an automated implementation of data analysis and visualization tools. GeneChip 640 is compatible with a variety of tissue types, and the data generated is suitable for a range of analysis techniques and applications. Additionally, AFFYMETRIX GeneChip 640 includes quality control features such as reagent tracking and annotation history, helping to ensure accurate, reliable results. Overall, GeneChip 640 provides intense throughput, robust design, and ease of use. It is a powerful, yet economical instrument and accessory, allowing researchers to quickly, effectively, and accurately analyze genome-wide expression data.
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