Performance of in silico analysis in predicting the effect of non-synonymous variants in inherited steroid metabolic diseases.

doi:10.1016/j.steroids.2013.04.002

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Back to search

Article

Performance of in silico analysis in predicting the effect of non-synonymous variants in inherited steroid metabolic diseases.

Steroids - 1 Jul 2013

Chan Angel O K

Abstract excerpt

BACKGROUND: Unclassified genetic variants are commonly encountered in molecular diagnostic service. In silico analyses using web-based predictive programs may provide information on the nature of the genetic variants, and help to prioritize novel variants for in vitro functional characterization. The objective of this study was to compare the performance of three such programs in genes related to steroid...

Topics

Amino Acid Substitution
Computational Biology
Metabolic Diseases
Polymorphism, Single Nucleotide

Source

Open in PubMed

Identifiers

PMID: 23603282
DOI: 10.1016/j.steroids.2013.04.002

Genes

DHCR7
POR

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

Community interpretation

Discuss the evidence

Ask a question, add context or challenge an interpretation. Community activity is separate from scientific evidence strength.

discussions

replies

Citations encouraged

Claims remain attributable.

No discussion yet

Be the first to add a careful, cited interpretation.

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics