Eleanor Feingold, Ph.D.

Email: efein@helix.hgen.pitt.edu

Phone: (412) 383-8599

Room: A310B Crabtree Hall

Position: Assistant Professor, Human Genetics

Education: B.S., Massachusetts Institute of Technology, 1985
Ph.D., Stanford University, 1993

Research Interests:
Dr. Feingold has worked extensively on statistical methods for genetic linkage analysis. Most of her work has focused on methods for finding genes by scanning the genomes of affected pairs or other small pedigrees. A more recent area of concentration is methods for mapping genes for quantitative traits using selected (e.g. concordant or discordant) sibships.
Her other major area of concentration is trisomy and Down syndrome. Dr. Feingold has worked on methods for mapping genes associated with disorders that are disproportionately more common in individuals with Down syndrome, methods for creating genetic maps using trisomic individuals, and analyses of association between nondisjunction and altered recombination.
An additional area of interest is methods for analyzing large-scale gene expression data, such as that produced by microarrays or serial analysis of gene expression (SAGE).

Recent Publications:
Brown AS, Feingold E, Broman KW, Sherman SL. Genome-wide Variation in Recombination in Female Meiosis: a Risk Factor for Non-disjunction of Chromosome 21. Human Molecular Genetics 9(4):515-523, 2000.
Feingold E, Brown AS, Sherman SL. Multipoint Estimation of Genetic Maps for Human Trisomies with One Parent or Other Partial Data. American Journal of Human Genetics 66:958-968, 2000.
Forrest W, Feingold E. Composite Statistics for QTL Mapping with Moderately Discordant Sibling Pairs. American Journal of Human Genetics 66:1642-1660, 2000.
Feingold E, Song KK, Weeks DE. Comparison of Allele-sharing Statistics for General Pedigrees. Genetic Epidemiology 19:S92-S98, 2000.
Sengul H, Weeks DE, Feingold E. A Survey of Affected-Sibship Statistics for Nonparametric Linkage Analysis. American Journal of Human Genetics 69:179-190, 2001.
Yu K, Feingold E. Estimating the Frequency Distribution of Crossovers During Meiosis from Recombination Data. Biometrics 57:427-434, 2001.
Song, KK, Feingold E, Weeks DE. Statistics for Nonparametric Linkage Analysis of X-linked Traits in General Pedigrees. American Journal of Human Genetics 70:181-191, 2002.
Peters DG, Kassam AB, Feingold E, Heidrich-OÕHare E, Yonas H, Ferrell RE, Brufsky A. Molecular Anatomy of an Intracranial Aneurysm: Coordinated Expression of Genes Involved in Wound Healing and Tissue Remodeling. Stroke 32:1036-1042, 2001.
Yu K, Feingold E. Methods for Analyzing the Spatial Distribution of Chiasmata During Meiosis based on Recombination Data. Biometrics (in press).

Other Publications: Click here to perform an automatic search for a listing of all Eleanor Feingold's publications and their abstracts through the National Library of Science's PubMed service.

Click here to view Dr. Feingold's Faculty Interests Page on the GSPH web site

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Email:	efein@helix.hgen.pitt.edu
Phone:	(412) 383-8599
Room:	A310B Crabtree Hall
Position:	Assistant Professor, Human Genetics
Education:	B.S., Massachusetts Institute of Technology, 1985 Ph.D., Stanford University, 1993
Research Interests:	Dr. Feingold has worked extensively on statistical methods for genetic linkage analysis. Most of her work has focused on methods for finding genes by scanning the genomes of affected pairs or other small pedigrees. A more recent area of concentration is methods for mapping genes for quantitative traits using selected (e.g. concordant or discordant) sibships. Her other major area of concentration is trisomy and Down syndrome. Dr. Feingold has worked on methods for mapping genes associated with disorders that are disproportionately more common in individuals with Down syndrome, methods for creating genetic maps using trisomic individuals, and analyses of association between nondisjunction and altered recombination. An additional area of interest is methods for analyzing large-scale gene expression data, such as that produced by microarrays or serial analysis of gene expression (SAGE).