Evidence map›Paper›PMID 20594352›Full record

ArticleTheoretical biology & medical modelling2010

A statistical model for mapping morphological shape.

Guifang Fu, Arthur Berg, Kiranmoy Das, Jiahan Li, Runze Li, Rongling Wu

Abstract read
In one paragraph

Article in Theoretical biology & medical modelling, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Statistical shape models of cuboid, navicular and talus bones.Journal of foot and ankle research · 2017
    Article
  5. Article
  6. Article
  7. Article
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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

6 authors.

Guifang FuDepartment of Statistics, Pennsylvania State University, University Park, PA 16802, USA.
Arthur Berg
Kiranmoy Das
Jiahan Li
Runze Li
Rongling Wu

Funding

New Statistical Models for Intensive Longitudinal DataR21DA024260 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI DIERKER, LISA C, LI, RUNZE · 2007 to 2010
$1.2M
Dynamical System /Related Engineering Approach /Improving Behavioral InterventionR21DA024266 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI COLLINS, LINDA M, RIVERA, DANIEL E · 2007 to 2010
$1.1M
NIDA NIH HHS R21 DA024260NIDA NIH HHS R21 DA024266PHS HHS DMS/NIGMS-0540745
6 · The paper itself

Abstract

backgroundLiving things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine.

resultsWe derived a statistical model for mapping specific genes or quantitative trait loci (QTLs) that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model.

conclusionBy identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.

Indexed as

Models, StatisticalChromosome MappingComputer SimulationCrosses, GeneticCucurbitaGenotypePlant LeavesQuantitative Trait Loci

Identifiers

PMID20594352
PMCPMC2915964

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LicenceCC BY
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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.