Evidence map›Paper›PMID 15851683›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2005

Solving the protein sequence metric problem.

William R Atchley, Jieping Zhao, Andrew D Fernandes, Tanja Drüke

Open access · greenAbstract readComparative Study
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 223 papers.

0numbers the graph read from it
0cells of the map it votes in
223citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

223 citing papers in PubMed, 469 citations in OpenAlex.

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

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

William R AtchleyDepartment of Genetics, Graduate Program in Biomathematics, and Center for Computational Biology, North Carolina State University, Raleigh, NC 27695-7614, USA. bill@atchleylab.org
Jieping Zhao
Andrew D Fernandes
Tanja Drüke
North Carolina State University · USBielefeld University · DE

Funding

THEORETICAL QUANTITATIVE GENETICSP01GM045344 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI MACKAY, TRUDY F · 1991 to 2005
$7.2M
NIGMS NIH HHS GM45344NIGMS NIH HHS P01 GM045344
6 · The paper itself

Abstract

Biological sequences are composed of long strings of alphabetic letters rather than arrays of numerical values. Lack of a natural underlying metric for comparing such alphabetic data significantly inhibits sophisticated statistical analyses of sequences, modeling structural and functional aspects of proteins, and related problems. Herein, we use multivariate statistical analyses on almost 500 amino acid attributes to produce a small set of highly interpretable numeric patterns of amino acid variability. These high-dimensional attribute data are summarized by five multidimensional patterns of attribute covariation that reflect polarity, secondary structure, molecular volume, codon diversity, and electrostatic charge. Numerical scores for each amino acid then transform amino acid sequences for statistical analyses. Relationships between transformed data and amino acid substitution matrices show significant associations for polarity and codon diversity scores. Transformed alphabetic data are used in analysis of variance and discriminant analysis to study DNA binding in the basic helix-loop-helix proteins. The transformed scores offer a general solution for analyzing a wide variety of sequence analysis problems.

Indexed as

Genetic VariationModels, GeneticPhylogenyAmino Acid SequenceAnalysis of VarianceCluster AnalysisCodonComputational BiologyDiscriminant AnalysisMultivariate AnalysisProtein ConformationStatic ElectricityStatistics as TopicCodon

Identifiers

PMID15851683
PMCPMC1088356
OpenAlexW1967195968

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.