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S. Goldberg

dblp:08/5281 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1997
—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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › statistical genetics
genetic linkage analysis
0.011997
Bi-dimensional scaling map (BDS-Map): an approach for building large genetic maps · Comput. Appl. Biosci. 1997
Bioinformatics and computational biology › statistical genetics
genetic mapping
0.011997
Bi-dimensional scaling map (BDS-Map): an approach for building large genetic maps · Comput. Appl. Biosci. 1997
Bioinformatics and computational biology › statistical genetics › genetic mapping
marker ordering
0.011997
Bi-dimensional scaling map (BDS-Map): an approach for building large genetic maps · Comput. Appl. Biosci. 1997

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

dynamical forces · 0.0bi-dimensional scaling · 0.0
YearPublicationVenuePosition
1997 Bi-dimensional scaling map (BDS-Map): an approach for building large genetic maps
abstract
Motivation: The approaches usually used for building large genetic maps consist of dividing the marker set into linkage groups and provide local orders that can be tested by multi-point linkage analysis. To deal with the limitations of these approaches, a strategy taking the marker set into account globally is defined. Results: The paper presents a new approach called 'Bi-Dimensional Scaling Map (BDS-Map) for inferring marker orders and distances in genetic maps based on the use of an additional dimension orthogonal to the map into which markers are projected. Dynamical forces based on a two-point analysis are applied to tend to optimize the marker locations in space. The efficiency of the approach is exemplified on real data (16 and 70 markers on chromosomes 6 and 2, respectively) and simulated data (50 maps of 70 markers). Availability: The package called ANGE (ANalyse du GE-nome), including both the program BDS-Map and the system allowing the database management, is available on request from the authors. Contact: E-mail:[email protected]
S. Goldberg, P. Ferrand, N. Q. Nguyen, Jean-François Boisvieux, Serge A. Hazout
Comput. Appl. Biosci.1