Evidence map›Paper›PMID 17389407›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2007

Branch migration displacement assay with automated heuristic analysis for discrete DNA length measurement using DNA microarrays.

Nader Pourmand, Stefano Caramuta, Andrea Villablanca, Silvia Mori, Miloslav Karhanek, Shan X Wang, Ronald W Davis

Abstract readComparative Study
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
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

7 authors at 2 institutions in 1 country.

Nader PourmandStanford Genome Technology Center, Palo Alto, CA 94304, USA. pourmand@stanford.edu
Stefano Caramuta
Andrea Villablanca
Silvia Mori
Miloslav Karhanek
Shan X Wang
Ronald W Davis
New York Genome Center · USStanford University · US

Funding

WHOLE YEAST GENOME TRANSCRIPTIONAL AND FUNCTIONAL GENE MAPS--A FEASIBILITY STUDYP01HG000205 · NHGRI · STANFORD UNIVERSITY · PI DAVIS, RONALD WAYNE, HOWE, ROGER THOMAS · 1990 to 2016
$120.9M
NHGRI NIH HHS P01 HG000205NHGRI NIH HHS P01-HG000205
6 · The paper itself

Abstract

The analysis of short tandem repeats (STRs) plays an important role in forensic science, human identification, genetic mapping, and disease diagnostics. Traditional STR analysis utilizes gel- or column-based approaches to analyze DNA repeats. Individual STR alleles are separated and distinguished according to fragment length; thus the assay is generally hampered by its low multiplex capacity. However, use of DNA microarray would employ a simple hybridization and detection for field forensics and biology. Here we demonstrate a rapid, highly sensitive method for STR analysis that utilizes DNA microarray technology. We describe two adaptations to accomplish this: the use of competitive hybridization to remove unpaired ssDNA from an array and the use of neural network classification to automate the analysis. The competitive displacement technique mimics the branch migration process that occurs during DNA recombination. Our technique will facilitate the rapid deduction of identity, length, and number of repeats for the multiple STRs in an unknown DNA sample.

Indexed as

DNAForensic GeneticsMicrosatellite RepeatsNeural Networks, ComputerNucleic Acid HybridizationOligonucleotide Array Sequence AnalysisOligonucleotidesDNAOligonucleotides

Identifiers

PMID17389407
PMCPMC1838402
OpenAlexW2071829361

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.