Evidence map›Paper›PMID 31972019›Full record

ArticleGigaScience2020

Telescope: an interactive tool for managing large-scale analysis from mobile devices.

Jaqueline J Brito, Thiago Mosqueiro, Jeremy Rotman, Victor Xue, Douglas J Chapski, Juan De la Hoz, Paulo Matias, Lana S Martin, Alex Zelikovsky, Matteo Pellegrini and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in GigaScience, 2020. 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. 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

11 authors.

Jaqueline J BritoDepartment of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90089-9121, USA.
Thiago MosqueiroInstitute for Quantitative and Computational Biosciences, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095, USA.
Jeremy RotmanDepartment of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA 90095, USA.
Victor XueDepartment of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA 90095, USA.
Douglas J ChapskiDepartment of Anesthesiology, David Geffen School of Medicine at UCLA, 650 Charles E. Young Drive, Los Angeles, CA 90095, USA.
Juan De la HozCenter for Neurobehavioral Genetics, University of California Los Angeles, 695 Charles E Young Dr S, Los Angeles, CA 90095, USA.
Paulo MatiasDepartment of Computer Science, Federal University of São Carlos, km 325 Rod. Washington Luis, São Carlos, SP 13565-905, Brazil.
Lana S MartinDepartment of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90089-9121, USA.
Alex ZelikovskyDepartment of Computer Science, Georgia State University, 1 Park Place, Atlanta, GA 30303, USA.
Matteo PellegriniInstitute for Quantitative and Computational Biosciences, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095, USA.
Serghei MangulDepartment of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90089-9121, USA.

Funding

QUBBD: VIRAL EVOLUTION AND SPREAD OF INFECTIOUS DISEASE IN COMPLEX NETWORK: BIG DATA ANALYSIS AND MODELINGR01EB025022 · NIBIB · GEORGIA STATE UNIVERSITY · PI SKUMS, PAVEL, VANNBERG, FREDRIK · 2017 to 2019
$891k
NIBIB NIH HHS R01 EB025022
6 · The paper itself

Abstract

backgroundIn today's world of big data, computational analysis has become a key driver of biomedical research. High-performance computational facilities are capable of processing considerable volumes of data, yet often lack an easy-to-use interface to guide the user in supervising and adjusting bioinformatics analysis via a tablet or smartphone.

resultsTo address this gap we proposed Telescope, a novel tool that interfaces with high-performance computational clusters to deliver an intuitive user interface for controlling and monitoring bioinformatics analyses in real-time. By leveraging last generation technology now ubiquitous to most researchers (such as smartphones), Telescope delivers a friendly user experience and manages conectivity and encryption under the hood.

conclusionsTelescope helps to mitigate the digital divide between wet and computational laboratories in contemporary biology. By delivering convenience and ease of use through a user experience not relying on expertise with computational clusters, Telescope can help researchers close the feedback loop between bioinformatics and experimental work with minimal impact on the performance of computational tools. Telescope is freely available at https://github.com/Mangul-Lab-USC/telescope.

Indexed as

SoftwareBig DataComputational BiologyData MiningUser-Computer Interfacebioinformaticsbioinformatics analysishigh-throughput computingjob scheduler

Identifiers

PMID31972019
PMCPMC6977584

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.