Evidence map›Paper›PMID 26199946›Full record

ArticleBioMed research international2015

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

Ning Ye, Hengfu Yin, Jingjing Liu, Xiaogang Dai, Tongming Yin

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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

5 authors at 2 institutions in 1 country.

Ning YeThe Southern Modern Forestry Collaborative Innovation Center, Nanjing Forestry University, Nanjing 210037, China ; College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China.
Hengfu YinResearch Institute of Subtropical Forestry, Chinese Academy of Forestry, Fuyang, Zhejiang 311400, China ; Key Laboratory of Forest genetics and breeding, Chinese Academy of Forestry, Fuyang, Zhejiang 311400, China.
Jingjing LiuThe Southern Modern Forestry Collaborative Innovation Center, Nanjing Forestry University, Nanjing 210037, China ; College of Forest Resources and Environment, Nanjing Forestry University, Nanjing 210037, China.
Xiaogang DaiThe Southern Modern Forestry Collaborative Innovation Center, Nanjing Forestry University, Nanjing 210037, China ; College of Forest Resources and Environment, Nanjing Forestry University, Nanjing 210037, China.
Tongming YinThe Southern Modern Forestry Collaborative Innovation Center, Nanjing Forestry University, Nanjing 210037, China ; College of Forest Resources and Environment, Nanjing Forestry University, Nanjing 210037, China.
Nanjing Forestry University · CNChinese Academy of Forestry · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

Indexed as

Data MiningSoftwareTranscriptomeAlgorithmsComputational BiologyDatabases, GeneticGene Expression RegulationHigh-Throughput Nucleotide SequencingHumansOligonucleotide Array Sequence Analysis

Identifiers

PMID26199946
PMCPMC4496643
OpenAlexW1496538562

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.