Evidence map›Paper›PMID 25943544›Full record

ArticleNucleic acids research2015

FlyNet: a versatile network prioritization server for the Drosophila community.

Junha Shin, Sunmo Yang, Eiru Kim, Chan Yeong Kim, Hongseok Shim, Ara Cho, Hyojin Kim, Sohyun Hwang, Jung Eun Shim, Insuk Lee

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

10 authors.

Junha ShinDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Sunmo YangDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Eiru KimDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Chan Yeong KimDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Hongseok ShimDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Ara ChoDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Hyojin KimDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Sohyun HwangDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Jung Eun ShimDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Insuk LeeDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea insuklee@yonsei.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drosophila melanogaster (fruit fly) has been a popular model organism in animal genetics due to the high accessibility of reverse-genetics tools. In addition, the close relationship between the Drosophila and human genomes rationalizes the use of Drosophila as an invertebrate model for human neurobiology and disease research. A platform technology for predicting candidate genes or functions would further enhance the usefulness of this long-established model organism for gene-to-phenotype mapping. Recently, the power of network prioritization for gene-to-phenotype mapping has been demonstrated in many organisms. Here we present a network prioritization server dedicated to Drosophila that covers ∼95% of the coding genome. This server, dubbed FlyNet, has several distinctive features, including (i) prioritization for both genes and functions; (ii) two complementary network algorithms: direct neighborhood and network diffusion; (iii) spatiotemporal-specific networks as an additional prioritization strategy for traits associated with a specific developmental stage or tissue and (iv) prioritization for human disease genes. FlyNet is expected to serve as a versatile hypothesis-generation platform for genes and functions in the study of basic animal genetics, developmental biology and human disease. FlyNet is available for free at http://www.inetbio.org/flynet.

Indexed as

Gene Regulatory NetworksSoftwareAlgorithmsAnimalsDiseaseDisease Models, AnimalDrosophila melanogasterGenes, InsectHumansInternet

Identifiers

PMID25943544
PMCPMC4489278

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.