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Ingrid Mihai

dblp:17/7063 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
comparative genomics
0.112008
Effective cluster-based seed design for cross-species sequence comparisons · Bioinform. 2008
Bioinformatics and computational biology › comparative genomics
cross-species sequence comparison
0.112008
Effective cluster-based seed design for cross-species sequence comparisons · Bioinform. 2008
Bioinformatics and computational biology
sequence alignment
0.112008
Effective cluster-based seed design for cross-species sequence comparisons · Bioinform. 2008
Bioinformatics and computational biology › sequence alignment
spaced seed design
0.112008
Effective cluster-based seed design for cross-species sequence comparisons · Bioinform. 2008

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

clustering · 0.1
YearPublicationVenuePosition
2008 Effective cluster-based seed design for cross-species sequence comparisons
abstract
Abstract Summary: To annotate newly sequenced organisms, cross-species sequence comparison algorithms can be applied to align gene sequences to the genome of a related species. To improve the accuracy of alignment, spaced seeds must be optimized for each comparison. As the number and diversity of genomes increase, an efficient alternative is to cluster pairwise comparisons into groups and identify seeds for groups instead of individual comparisons. Here we investigate a measure of comparison closeness and identify classes of comparisons that show similar seed behavior and therefore can employ the same seed. Availability: Source code is freely available at http://dna.cs.gwu.edu and from Bioinformatics online. Contact: [email protected], [email protected] Supplementary information: Supplementary data are available at http://dna.cs.gwu.edu and Bioinformatics online.
Leming Zhou, Ingrid Mihai, Liliana Florea
Bioinform.2