Evidence map›Paper›PMID 8532532›Full record

ArticleNucleic acids research1995

MatInd and MatInspector: new fast and versatile tools for detection of consensus matches in nucleotide sequence data.

K Quandt, K Frech, H Karas, E Wingender, T Werner

Abstract read
In one paragraph

Article in Nucleic acids research, 1995. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 759 papers.

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759citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

759 citing papers in PubMed.

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699 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

K QuandtInstitut für Säugetiergenetik, GSF-Forschungszentrum für Umwelt und Gesundheit GmbH, Neuherberg, Germany.
K Frech
H Karas
E Wingender
T Werner

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of potential regulatory motifs in new sequence data is increasingly important for experimental design. Those motifs are commonly located by matches to IUPAC strings derived from consensus sequences. Although this method is simple and widely used, a major drawback of IUPAC strings is that they necessarily remove much of the information originally present in the set of sequences. Nucleotide distribution matrices retain most of the information and are thus better suited to evaluate new potential sites. However, sufficiently large libraries of pre-compiled matrices are a prerequisite for practical application of any matrix-based approach and are just beginning to emerge. Here we present a set of tools for molecular biologists that allows generation of new matrices and detection of potential sequence matches by automatic searches with a library of pre-compiled matrices. We also supply a large library (> 200) of transcription factor binding site matrices that has been compiled on the basis of published matrices as well as entries from the TRANSFAC database, with emphasis on sequences with experimentally verified binding capacity. Our search method includes position weighting of the matrices based on the information content of individual positions and calculates a relative matrix similarity. We show several examples suggesting that this matrix similarity is useful in estimating the functional potential of matrix matches and thus provides a valuable basis for designing appropriate experiments.

Indexed as

Consensus SequenceSoftwareBase SequenceConserved SequenceMolecular Sequence DataSequence Analysis

Identifiers

PMID8532532
PMCPMC307478

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.