Evidence map›Paper›PMID 31598610›Full record

ArticlePractice and Experience in Advanced Research Computing 2018 : Seamless Creativity : July 22-26 2017, Pittsburgh, Pennsylvania. Practice and Experience in Advanced Research Computing (Conference) (2018 : Pittsburgh, Pa.)2018

Building a Science Gateway For Processing and Modeling Sequencing Data Via Apache Airavata.

Zhong Wang, Marcus A Christie, Eroma Abeysinghe, Tinyi Chu, Suresh Marru, Marlon Pierce, Charles G Danko

Abstract read
In one paragraph

Article in Practice and Experience in Advanced Research Computing 2018 : Seamless Creativity : July 22-26 2017, Pittsburgh, Pennsylvania. Practice and Experience in Advanced Research Computing (Conference) (2018 : Pittsburgh, Pa.), 2018. 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. TopPIC Gateway: A Web Gateway for Top-Down Mass Spectrometry Data Interpretation.PEARC20 : Practice and Experience in Advanced Research Computing 2020 : Catch the wave : July 27-31, 2020, Portland, Or Virtual Conference. Practice and Experience in Advanced Research Computing (Conference) (2020 : Online) · 2020
    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

7 authors.

Zhong WangBaker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, zw355@cornell.edu.
Marcus A ChristieScience Gateways Research Center, Pervasive Technology Institute, Indiana University, Bloomington, IN, machrist@iu.edu.
Eroma AbeysingheScience Gateways Research Center, Pervasive Technology Institute, Indiana University, Bloomington, IN, eabeysin@iu.edu.
Tinyi ChuGraduate field of Computational Biology, Cornell University, Ithaca, NY, tc532@cornell.edu.
Suresh MarruScience Gateways Research Center, Pervasive Technology Institute, Indiana University, Bloomington, IN, smarru@iu.edu.
Marlon PierceScience Gateways Research Center, Pervasive Technology Institute, Indiana University, Bloomington, IN, marpierc@iu.edu.
Charles G DankoBaker Institute for Animal Health and Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, cgd24@cornell.edu.

Funding

Mapping RNA polymerase in tissue samples with ChRO-seq.R01HG009309 · NHGRI · CORNELL UNIVERSITY · PI DANKO, CHARLES GRAHE · 2017 to 2021
$1.9M
NHGRI NIH HHS R01 HG009309
6 · The paper itself

Abstract

The amount of DNA sequencing data has been exponentially growing during the past decade due to advances in sequencing technology. Processing and modeling large amounts of sequencing data can be computationally intractable for desktop computing platforms. High performance computing (HPC) resources offer advantages in terms of computing power, and can be a general solution to these problems. Using HPCs directly for computational needs requires skilled users who know their way around HPCs and acquiring such skills take time. Science gateways acts as the middle layer between users and HPCs, providing users with the resources to accomplish compute-intensive tasks without requiring specialized expertise. We developed a web-based computing platform for genome biologists by customizing the PHP Gateway for Airavata (PGA) framework that accesses publicly accessible HPC resources via Apache Airavata. This web computing platform takes advantage of the Extreme Science and Engineering Discovery Environment (XSEDE) which provides the resources for gateway development, including access to CPU, GPU, and storage resources. We used this platform to develop a gateway for the dREG algorithm, an online computing tool for finding functional regions in mammalian genomes using nascent RNA sequencing data. The dREG gateway provides its users a free, powerful and user-friendly GPU computing resource based on XSEDE, circumventing the need of specialized knowledge about installation, configuration, and execution on an HPC for biologists. The dREG gateway is available at: https://dREG.dnasequence.org/.

Indexed as

Apache Airavatacloud computingNext Generation SequencingScience gatewaysequencing datasoftware-as-a-service

Identifiers

PMID31598610
PMCPMC6785190

What OpenQuestion holds

Textmetadata
LicenceTDM
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.