Y. Elkind

dblp:70/151 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › phylogenetics › phylogenetic inference
maximum likelihood estimation
0.011994
Maximum likelihood estimation of quantitative trait loci parameters with the aid of genetic markers using a standard statistical package · Comput. Appl. Biosci. 1994
Bioinformatics and computational biology › statistical genetics
quantitative trait locus analysis
0.011994
Maximum likelihood estimation of quantitative trait loci parameters with the aid of genetic markers using a standard statistical package · Comput. Appl. Biosci. 1994

Methods — techniques the papers use, named apart from their topics

newton-raphson iteration · 0.0BMDP program LE · 0.0
YearPublicationVenuePosition
1994 Maximum likelihood estimation of quantitative trait loci parameters with the aid of genetic markers using a standard statistical package
abstract
Consistent parameter estimates of quantitative trait loci linked to genetic markers can be derived by maximum likelihood methodology. For many experimental designs of interest, parameter estimates and their standard errors can be obtained by program LE of BMDP, which uses the Newton-Raphson method of iteration. Program LE was tested on data simulated for a backcross between two inbred lines. A single quantitative trait locus linked to either one or two genetic markers was simulated. Convergence was rapid, and computing and programming time were insignificant. All parameter estimates were within the expected bounds. Many different designs can be readily analyzed.
Y. Elkind, B. Nir, Joel Ira Weller
Comput. Appl. Biosci.1