Evidence map›Paper›PMID 18842630›Full record

ArticleNucleic acids research2008

Gene expression module-based chemical function similarity search.

Yun Li, Pei Hao, Siyuan Zheng, Kang Tu, Haiwei Fan, Ruixin Zhu, Guohui Ding, Changzheng Dong, Chuan Wang, Xuan Li and 5 more

Abstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
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  13. Small Molecule Subgraph Detector (SMSD) toolkit.Journal of cheminformatics · 2009
    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

15 authors.

Yun LiKey Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, Shanghai, PR China.
Pei Hao
Siyuan Zheng
Kang Tu
Haiwei Fan
Ruixin Zhu
Guohui Ding
Changzheng Dong
Chuan Wang
Xuan Li
H-J Thiesen
Y Eugene Chen
Hualiang Jiang
Lei Liu
Yixue Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigation of biological processes using selective chemical interventions is generally applied in biomedical research and drug discovery. Many studies of this kind make use of gene expression experiments to explore cellular responses to chemical interventions. Recently, some research groups constructed libraries of chemical related expression profiles, and introduced similarity comparison into chemical induced transcriptome analysis. Resembling sequence similarity alignment, expression pattern comparison among chemical intervention related expression profiles provides a new way for chemical function prediction and chemical-gene relation investigation. However, existing methods place more emphasis on comparing profile patterns globally, which ignore noises and marginal effects. At the same time, though the whole information of expression profiles has been used, it is difficult to uncover the underlying mechanisms that lead to the functional similarity between two molecules. Here a new approach is presented to perform biological effects similarity comparison within small biologically meaningful gene categories. Regarding gene categories as units, a reduced similarity matrix is generated for measuring the biological distances between query and profiles in library and pointing out in which modules do chemical pairs resemble. Through the modularization of expression patterns, this method reduces experimental noises and marginal effects and directly correlates chemical molecules with gene function modules.

Indexed as

Antineoplastic AgentsBreast NeoplasmsCell HypoxiaCell Line, TumorDNA ProbesFemaleGene ExpressionGene Expression ProfilingGene Regulatory NetworksHumansOligonucleotide Array Sequence AnalysisAntineoplastic AgentsDNA Probes

Identifiers

PMID18842630
PMCPMC2582597

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Registered trials

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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.