Evidence map›Paper›PMID 27993775›Full record

ArticleBioinformatics (Oxford, England)2017

GENIUS: web server to predict local gene networks and key genes for biological functions.

Tomas Puelma, Viviana Araus, Javier Canales, Elena A Vidal, Juan M Cabello, Alvaro Soto, Rodrigo A Gutiérrez

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2017. 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
–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

2 citing papers in PubMed.

  1. Article
  2. African journal of biotechnology · 2019
    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

7 authors.

Tomas PuelmaMillennium Nucleus Center for Plant Systems and Synthetic Biology, FONDAP Center for Genome Regulation, Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile.
Viviana ArausMillennium Nucleus Center for Plant Systems and Synthetic Biology, FONDAP Center for Genome Regulation, Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile.
Javier CanalesMillennium Nucleus Center for Plant Systems and Synthetic Biology, FONDAP Center for Genome Regulation, Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile.
Elena A VidalMillennium Nucleus Center for Plant Systems and Synthetic Biology, FONDAP Center for Genome Regulation, Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile.
Juan M CabelloMillennium Nucleus Center for Plant Systems and Synthetic Biology, FONDAP Center for Genome Regulation, Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile.
Alvaro SotoMillennium Nucleus Center for Plant Systems and Synthetic Biology, Departamento de Ciencias de la Computación, Facultad de Ingeniería, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile.
Rodrigo A GutiérrezMillennium Nucleus Center for Plant Systems and Synthetic Biology, FONDAP Center for Genome Regulation, Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile.

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Summary: GENIUS is a user-friendly web server that uses a novel machine learning algorithm to infer functional gene networks focused on specific genes and experimental conditions that are relevant to biological functions of interest. These functions may have different levels of complexity, from specific biological processes to complex traits that involve several interacting processes. GENIUS also enriches the network with new genes related to the biological function of interest, with accuracies comparable to highly discriminative Support Vector Machine methods. Availability and Implementation: GENIUS currently supports eight model organisms and is freely available for public use at http://networks.bio.puc.cl/genius . Contact: genius.psbl@gmail.com. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

Gene Regulatory NetworksMachine LearningSoftwareArabidopsis

Identifiers

PMID27993775
PMCPMC5408817

What OpenQuestion holds

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LicenceCC BY-NC
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.