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Hillary Voet

dblp:22/5423 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · unresolved

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › multiple sequence alignment
profile-profile alignment
0.112005
Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure · Bioinform. 2005
Bioinformatics and computational biology
protein function prediction
0.112005
Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure · Bioinform. 2005
Bioinformatics and computational biology
protein structure prediction
0.012005
Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure · Bioinform. 2005

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

statistical significance estimation · 0.1fisher's combining method · 0.1
YearPublicationVenuePosition
2005 Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure
abstract
MOTIVATION: Improved comparisons of multiple sequence alignments (profiles) with other profiles can identify subtle relationships between protein families and motifs significantly beyond the resolution of sequence-based comparisons. RESULTS: The local alignment of multiple alignments (LAMA) method was modified to estimate alignment score significance by applying a new measure based on Fisher's combining method. To verify the new procedure, we used known protein structures, sequence annotations and cyclical relations consistency analysis (CYRCA) sets of consistently aligned blocks. Using the new significance measure improved the sensitivity of LAMA without altering its selectivity. The program performed better than other profile-to-profile methods (COMPASS and Prof_sim) and a sequence-to-profile method (PSI-BLAST). The testing was large scale and used several parameters, including pseudo-counts profile calculations and local ungapped blocks or more extended gapped profiles. This comparison provides guidelines to the relative advantages of each method for different cases. We demonstrate and discuss the unique advantages of using block multiple alignments of protein motifs.
Milana Frenkel-Morgenstern, Hillary Voet, Shmuel Pietrokovski
Bioinform.2