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Alice Meier

dblp:81/10932 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › statistical genetics
variant effect prediction
0.112012
SNPdbe: constructing an nsSNP functional impacts database · Bioinform. 2012
Bioinformatics and computational biology › statistical genetics › genotype-phenotype association
disease association
0.012012
SNPdbe: constructing an nsSNP functional impacts database · Bioinform. 2012
Bioinformatics and computational biology › genome annotation
genomic variant annotation
0.012012
SNPdbe: constructing an nsSNP functional impacts database · Bioinform. 2012

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

SNAP · 0.1SIFT · 0.1
YearPublicationVenuePosition
2012 SNPdbe: constructing an nsSNP functional impacts database
abstract
UNLABELLED: Many existing databases annotate experimentally characterized single nucleotide polymorphisms (SNPs). Each non-synonymous SNP (nsSNP) changes one amino acid in the gene product (single amino acid substitution;SAAS). This change can either affect protein function or be neutral in that respect. Most polymorphisms lack experimental annotation of their functional impact. Here, we introduce SNPdbe-SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from >2600 organisms; 'human' being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt. SNPdbe is consistently updated and easily augmented with new sources of information. The database is available as an MySQL dump and via a web front end that allows searches with any combination of organism names, sequences and mutation IDs. AVAILABILITY: http://www.rostlab.org/services/snpdbe.
Christian Schaefer, Alice Meier, Burkhard Rost, Yana Bromberg
Bioinform.2