The DOI matches its Crossref record.
A novel, sensitive detection system for high-density microarrays using dendrimer technology
Abstract
Stears, Robin L., Robert C. Getts, and Steven R. Gullans. A novel, sensitive detection system for high-density microarrays using dendrimer technology. Physiol Genomics 3: 93–99, 2000.—To improve signal detection on cDNA microarrays, we adapted a fluorescent oligonucleotide dendrimeric signal amplification system to microarray technology. This signal detection method requires 16-fold less RNA for probe synthesis, does not depend on the incorporation of fluorescent dNTPs into a reverse transcription reaction, generates a high signal-to-background ratio, and can be used to allow for multichannel detection on a single chip. Furthermore, since the dendrimers can be detected individually, it may be possible, by employing dendrimer-binding standards, to calculate the numbers of bound cDNAs can be estimated. These features make the dendrimer signal detection reagent ideal for high-throughput functional genomics research.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Nanostructures in Biodiagnostics
Rosi, N. L., & Mirkin, C. A. (2005) · Chemical Reviews · doi:10.1021/cr030067f · Cited by 4,603
Dendrimers in biomedical applications—reflections on the field
SVENSON, S., & TOMALIA, D. (2005) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2005.09.018 · Cited by 1,919
Dendrimers in biomedical applications—reflections on the field
Svenson, S., & Tomalia, D. A. (2012) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2012.09.030 · Cited by 593
John, G. R., Shankar, S. L., Shafit-Zagardo, B., Massimi, A., Lee, S. C., Raine, C. S., & Brosnan, C. F. (2002) · Nature Medicine · doi:10.1038/nm781 · Cited by 477
Metadata
- Authors
- STEARS, R. L., GETTS, R. C., & GULLANS, S. R.
- Venue
- Physiological Genomics
- Publisher
- American Physiological Society
- Published
- 2000-08-09
- Volume
- 3
- Issue
- 2
- Pages
- 93-99
- ISSN
- 1094-8341 (ISSN-L)
- 1531-2267
- OpenAlex
- W2186957524
- Cited by
- 216
- References
- 0
- FWCI
- 82.91
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A novel, sensitive detection system for high-density microarrays using dendrimer technology. https://app.cochat.ai/papers/10.1152/physiolgenomics.2000.3.2.93
- The paper
- STEARS, R. L., GETTS, R. C., & GULLANS, S. R. (2000). A novel, sensitive detection system for high-density microarrays using dendrimer technology. Physiological Genomics. https://doi.org/10.1152/physiolgenomics.2000.3.2.93
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.