Biomedical subjects

R M Winter

Publications and source records attributed to R M Winter.

219 records · Page 13Linked to original sources

PubMed1980

Estimation of male to female ratio of mutation rates from carrier-detection tests in X-linked disorders.

A method is presented for the estimation of the ratio of male to female mutation rates from female carrier-detection test data from pedigrees containing an isolated male manifesting an X-linked necessive disorder. Pedigrees of any size and complexity (barring consanguinity) and containing any number of tested females can be utilized. The relative fitness of affected males and carrier females, and the segregation probability of the abnormal gamete in females, can be estimated simultaneously with the ratio of mutation rates in order to test specific hypotheses against given bodies of data. Here this method is applied to families containing isolated individuals affected with Lesch-Nyhan syndrome.

Female↗

PubMedDate not supplied

The Online London Dysmorphology Database.

A prototype of the Online London Dysmorphology Database is now available for testing purposes. In this paper we describe the new online version of the London Dysmorphology Database (LDDB), which is accessible via the World-Wide Web. The system has been developed primarily to address the information lag associated with the stand-alone version of LDDB (currently 3-15 months) and therefore provides access to the latest data from the master database that resides on a web server. An additional benefit is that, because the Online LDDB is a web-based resource, it will be available to users of both Macintosh and Unix computers as well as PC users.

Animals↗

PubMedDate not supplied

A case-based learning approach to grouping cases with multiple malformations.

A case-based classification system can provide assistance to specialists in dysmorphology. This article describes a case-based model designed to assist in identification and retrospective analysis of rare types of syndromes that have proved difficult to diagnose. The primary task of diagnosis is complemented by a learning, or grouping, task. Using data sets of diagnosed cases in related categories of syndromes, we demonstrate how a case-based learning algorithm can extend the retrieval and indexing mechanisms of standard databases to provide a focus for analysis of syndrome classifications.

Abnormalities, Multiple↗