Evidence map›Paper›PMID 23890051›Full record

ArticleGenome medicine2013

Pathprinting: An integrative approach to understand the functional basis of disease.

Gabriel M Altschuler, Oliver Hofmann, Irina Kalatskaya, Rebecca Payne, Shannan J Ho Sui, Uma Saxena, Andrei V Krivtsov, Scott A Armstrong, Tianxi Cai, Lincoln Stein and 1 more

Abstract read
In one paragraph

Article in Genome medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Trial
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  10. Taking Bioinformatics to Systems Medicine.Methods in molecular biology (Clifton, N.J.) · 2016
    Review
  11. Article
  12. 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

11 authors.

Gabriel M AltschulerDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Oliver HofmannDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA ; Bioinformatics Core, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA ; Harvard Stem Cell Institute, 1350 Massachusetts Ave, Cambridge, MA 02138.
Irina KalatskayaOntario Institute for Cancer Research, Department of Informatics and Bio-computing, MaRS Centre, South Tower, 101 College Street, Toronto, ON, M5G 0A3, Canada.
Rebecca PayneDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Shannan J Ho SuiDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA ; Bioinformatics Core, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Uma SaxenaDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Andrei V KrivtsovDivision of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
Scott A ArmstrongDivision of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA ; Harvard Stem Cell Institute, 1350 Massachusetts Ave, Cambridge, MA 02138.
Tianxi CaiDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Lincoln SteinOntario Institute for Cancer Research, Department of Informatics and Bio-computing, MaRS Centre, South Tower, 101 College Street, Toronto, ON, M5G 0A3, Canada.
Winston A HideDepartment of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA ; Bioinformatics Core, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA ; Harvard Stem Cell Institute, 1350 Massachusetts Ave, Cambridge, MA 02138.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New strategies to combat complex human disease require systems approaches to biology that integrate experiments from cell lines, primary tissues and model organisms. We have developed Pathprint, a functional approach that compares gene expression profiles in a set of pathways, networks and transcriptionally regulated targets. It can be applied universally to gene expression profiles across species. Integration of large-scale profiling methods and curation of the public repository overcomes platform, species and batch effects to yield a standard measure of functional distance between experiments. We show that pathprints combine mouse and human blood developmental lineage, and can be used to identify new prognostic indicators in acute myeloid leukemia. The code and resources are available at http://compbio.sph.harvard.edu/hidelab/pathprint.

Identifiers

PMID23890051
PMCPMC3971351

What OpenQuestion holds

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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.