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Cited by 664

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities

Open access
Manning, Melanie, Hudgins, Louanne·2010·Genetics in Medicine

Abstract

Laboratory evaluation of patients with developmental delay/intellectual disability, congenital anomalies, and dysmorphic features has changed significantly in the last several years with the introduction of microarray technologies. Using these techniques, a patient's genome can be examined for gains or losses of genetic material too small to be detected by standard G-banded chromosome studies. This increased resolution of microarray technology over conventional cytogenetic analysis allows for identification of chromosomal imbalances with greater precision, accuracy, and technical sensitivity. A variety of array-based platforms are now available for use in clinical practice, and utilization strategies are evolving. Thus, a review of the utility and limitations of these techniques and recommendations regarding present and future application in the clinical setting are presented in this study.

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Metadata

Authors
Manning, M., & Hudgins, L.
Venue
Genetics in Medicine
Publisher
Elsevier BV
Published
2010-11
Volume
12
Issue
11
Pages
742-745
ISSN
1098-3600 (ISSN-L)
OpenAlex
W1980096475
Cited by
664
References
3
FWCI
27.66
Type
journal article
Language
en
Update notices
addendum (2020-12-01)
Open access
bronze
Licence

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CoChat. (2026). Citation check: Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. https://app.cochat.ai/papers/10.1097/gim.0b013e3181f8baad
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Manning, M., & Hudgins, L. (2010). Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genetics in Medicine. https://doi.org/10.1097/gim.0b013e3181f8baad

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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.