Evidence map›Paper›PMID 18725293›Full record

ReviewCurrent opinion in biotechnology2008

Gene module level analysis: identification to networks and dynamics.

Xuewei Wang, Ertugrul Dalkic, Ming Wu, Christina Chan

Abstract readReview
In one paragraph

Review in Current opinion in biotechnology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Trial
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  11. The functional study of human proteins using humanized yeast.Journal of microbiology (Seoul, Korea) · 2020
    Review
  12. Article
  13. Review
  14. Article
  15. Article
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  17. SMARCE1 is required for the invasive progression of in situ cancers.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  18. Article
  19. Article
  20. 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

4 authors.

Xuewei WangMichigan State University, Chemical Engineering and Materials Science Department, 2527 Engineering building, East Lansing, MI 48823, USA.
Ertugrul Dalkic
Ming Wu
Christina Chan

Funding

Develop a Dynamic Model that Incoporates Text-mining to Reconstruct NetworksR01GM079688 · NIGMS · MICHIGAN STATE UNIVERSITY · PI CHAN, CHRISTINA · 2007 to 2012
$1.2M
Development of a parallel, array-based transcription factor expression assayR21RR024439 · NCRR · MICHIGAN STATE UNIVERSITY · PI WALTON, STEPHEN PATRICK · 2008 to 2010
$540k
Aptamer-based Proteomic Analysis for Cancer SignaturesR21CA126136 · NCI · MICHIGAN STATE UNIVERSITY · PI WALTON, STEPHEN PATRICK · 2006 to 2007
$354k
NCI NIH HHS R21 CA126136NCI NIH HHS R21CA126136NCRR NIH HHS R21 RR024439NCRR NIH HHS R21RR024439NIGMS NIH HHS 1R01GM079688NIGMS NIH HHS R01 GM079688
6 · The paper itself

Abstract

Nature exhibits modular design in biological systems. Gene module level analysis is based on this module concept, aiming to understand biological network design and systems behavior in disease and development by emphasizing on modules of genes rather than individual genes. Module level analysis has been extensively applied in genome wide level analysis, exploring the organization of biological systems from identifying modules to reconstructing module networks and analyzing module dynamics. Such module level perspective provides a high level representation of the regulatory scenario and design of biological systems, promising to revolutionize our view of systems biology, genetic engineering as well as disease mechanisms and molecular medicine.

Indexed as

AlgorithmsModels, BiologicalComputer SimulationMetabolomeMultigene FamilySignal Transduction

Identifiers

PMID18725293
PMCPMC2615490

What OpenQuestion holds

Textmetadata
LicenceTDM
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.