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Parallel Synthesis Technologies
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silicon microarray spotting pins - by Bioz Stars,
2026-03
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Parallel Synthesis Technologies
customized printheads silicon microarray spotting pins ![]() Customized Printheads Silicon Microarray Spotting Pins, supplied by Parallel Synthesis Technologies, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/result/customized printheads silicon microarray spotting pins/product/Parallel Synthesis Technologies Average 90 stars, based on 1 article reviews
customized printheads silicon microarray spotting pins - by Bioz Stars,
2026-03
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Journal: Nature protocols
Article Title: Quantifying protein-protein interactions in high throughput using protein domain microarrays
doi: 10.1038/nprot.2010.36
Figure Lengend Snippet: Quantifying domain–peptide interactions in high throughput using protein domain microarrays. (a) A set of n protein interaction domains are cloned, expressed, purified and arrayed. The microarrays of protein domains are then probed with m fluorescently labeled peptides to reveal the full n × m matrix of domain–peptide interactions. (b) For high-affinity interactions (KD < 2 μM), dissociation constants can be determined directly using protein microarrays. Microarrays of protein domains are probed with eight concentrations of each peptide and the resulting saturation binding curves are used to determine the binding affinity of each domain–peptide interaction. (c) For low-affinity interactions (KD < 50 μM), microarrays of protein domains are probed with fluorescently labeled peptides and a fluorescence threshold is used to divide domain–peptide pairs into putative interactions (array positives) and putative noninteractions (array negatives). A secondary assay (FP) is then used to retest and quantify all array positives. The result is a quantitative interaction data set (data set 1) in which all the false positives in the microarray data set have been eliminated. To remove false negatives, it is necessary to build a model that can predict domain–peptide interactions. The model is then used to highlight suspected false negatives in the microarray data set, which are retested by FP. By performing multiple cycles of prediction, retesting and retraining of the model, many of the microarray false negatives can be corrected. This results in a substantially refined data set (data set 2).
Article Snippet: Custom-made aldehyde-coated 74.5 mm × 112.5 mm × 1 mm glass substrates (Thermo Fisher Scientific Inc., cat. no. HAR-1101-C60) ProPlate Gaskets (Grace Bio-labs, cat. no. 204971) 96-Well No-Bottom microtiter plates (Greiner Bio-One, cat. no. 655000) 96-well microtiter plates (Greiner Bio-One, cat. no. 650201) 384-well assay plates, black nonbinding, for FP assays (Corning, cat. no. 3575) 384-well microarray plates, for printing protein microarrays (Genetix, cat. no. X7022) Storage Mat III (Costar, cat. no. 3080) Disposable reagent reservoirs, sterile (VWR, cat. no. 82026-350) Deep-well 96-well microtiter plate (Costar, cat. no. 3960) 14 ml Polypropylene Round-Bottom Tube (Becton Dickinson, cat. no. 352059) NanoPrint LM60 Microarrayer (Arrayit Corporation) including cooling block for source plate and destination block designed for 16 microtiter-sized
Techniques: High Throughput Screening Assay, Clone Assay, Purification, Labeling, Binding Assay, Fluorescence, Microarray