Automated identification of abnormal respiratory ciliary motion in nasal biopsies-Reference-Cited by-同舟云学术

Automated identification of abnormal respiratory ciliary motion in nasal biopsies

Published:2015-08-05 Issue:299 Volume:7 Page:
ISSN:1946-6234
Container-title:Science Translational Medicine
language:en
Short-container-title:Sci. Transl. Med.

Author:

Quinn Shannon P.¹²,Zahid Maliha J.³,Durkin John R.⁴,Francis Richard J.³,Lo Cecilia W.³,Chennubhotla S. Chakra²

Affiliation:

1. Joint Carnegie Mellon–University of Pittsburgh Ph.D. Program in Computational Biology, Department of Computation and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.

2. Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA.

3. Department of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15201, USA.

4. University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA.

Abstract

An objective, computational method to quantitatively identify ciliary motion in digital videos of cells from patients with ciliopathies can be used for diagnosis.

Funder

NIH

Pennsylvania Department of Health

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Medicine

Reference42 articles.

1. The effects of coronavirus on human nasal ciliated respiratory epithelium

2. Ciliary dysfunction and ultrastructural abnormalities are features of severe asthma

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4. Clinical and genetic aspects of primary ciliary dyskinesia/Kartagener syndrome

5. Increased postoperative and respiratory complications in patients with congenital heart disease associated with heterotaxy

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