DNA Subway: Making genome analysis egalitarian

Uwe K.K Hilgert, Sheldon McKay, Cornel Ghiban, Mohammed Khalfan, David Micklos, Jason Williams

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

DNA Subway bundles research-grade bioinformatics tools, highperformance computing, and databases into easy-to-use workflows. Students have been "riding" different lines since 2010, to predict and annotate genes in up to 150kb of raw DNA sequence (Red Line), identify homologs in sequenced genomes (Yellow Line), identify species using DNA barcodes and construct phylogenetic trees (Blue Line), and examine RNA sequence (RNA-Seq) datasets for transcript abundance and differential expression (Green Line). With support for plant and animal genomes, DNA Subway engages students in their own learning, bringing to life key concepts in molecular biology, genetics, and evolution. Integrated DNA barcoding and RNA extraction wet-lab experiments support a variety of inquiry-based projects using student-generated data. Products of student research can be exported, published, and used in follow-up experiments. To date, DNA Subway has over 8,000 registered users who have produced 51,000 projects. Based on the popular Tuxedo Protocol, the Green Line was introduced in January 2014 as an easy-to-use workflow to analyze RNA-Seq datasets. The workflow uses iPlant's APIs (http://agaveapi.co/) to access high-performance compute resources of NSF's Extreme Scientific and Engineering Discovery Environment (XSEDE), providing the first easy "on ramp" to biological supercomputing.

Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
ISBN (Print)9781450328937
DOIs
StatePublished - 2014
Event2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014 - Atlanta, GA, United States
Duration: Jul 13 2014Jul 18 2014

Other

Other2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014
CountryUnited States
CityAtlanta, GA
Period7/13/147/18/14

Fingerprint

Subways
DNA
Genes
RNA
Students
Molecular biology
DNA sequences
Bioinformatics
Application programming interfaces (API)
Animals
Experiments
Network protocols

Keywords

  • Cold spring harbor
  • DNA subway
  • Education
  • Fastx toolkit
  • Green line
  • Iplant api
  • Iplant collaborative
  • Red line
  • Rna seq
  • Rna seq data
  • Undergraduate

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Hilgert, U. K. K., McKay, S., Ghiban, C., Khalfan, M., Micklos, D., & Williams, J. (2014). DNA Subway: Making genome analysis egalitarian. In ACM International Conference Proceeding Series [70] Association for Computing Machinery. https://doi.org/10.1145/2616498.2616575

DNA Subway : Making genome analysis egalitarian. / Hilgert, Uwe K.K; McKay, Sheldon; Ghiban, Cornel; Khalfan, Mohammed; Micklos, David; Williams, Jason.

ACM International Conference Proceeding Series. Association for Computing Machinery, 2014. 70.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hilgert, UKK, McKay, S, Ghiban, C, Khalfan, M, Micklos, D & Williams, J 2014, DNA Subway: Making genome analysis egalitarian. in ACM International Conference Proceeding Series., 70, Association for Computing Machinery, 2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014, Atlanta, GA, United States, 7/13/14. https://doi.org/10.1145/2616498.2616575
Hilgert UKK, McKay S, Ghiban C, Khalfan M, Micklos D, Williams J. DNA Subway: Making genome analysis egalitarian. In ACM International Conference Proceeding Series. Association for Computing Machinery. 2014. 70 https://doi.org/10.1145/2616498.2616575
Hilgert, Uwe K.K ; McKay, Sheldon ; Ghiban, Cornel ; Khalfan, Mohammed ; Micklos, David ; Williams, Jason. / DNA Subway : Making genome analysis egalitarian. ACM International Conference Proceeding Series. Association for Computing Machinery, 2014.
@inproceedings{b28b371328594fb3bbedd80cea3a94dd,
title = "DNA Subway: Making genome analysis egalitarian",
abstract = "DNA Subway bundles research-grade bioinformatics tools, highperformance computing, and databases into easy-to-use workflows. Students have been {"}riding{"} different lines since 2010, to predict and annotate genes in up to 150kb of raw DNA sequence (Red Line), identify homologs in sequenced genomes (Yellow Line), identify species using DNA barcodes and construct phylogenetic trees (Blue Line), and examine RNA sequence (RNA-Seq) datasets for transcript abundance and differential expression (Green Line). With support for plant and animal genomes, DNA Subway engages students in their own learning, bringing to life key concepts in molecular biology, genetics, and evolution. Integrated DNA barcoding and RNA extraction wet-lab experiments support a variety of inquiry-based projects using student-generated data. Products of student research can be exported, published, and used in follow-up experiments. To date, DNA Subway has over 8,000 registered users who have produced 51,000 projects. Based on the popular Tuxedo Protocol, the Green Line was introduced in January 2014 as an easy-to-use workflow to analyze RNA-Seq datasets. The workflow uses iPlant's APIs (http://agaveapi.co/) to access high-performance compute resources of NSF's Extreme Scientific and Engineering Discovery Environment (XSEDE), providing the first easy {"}on ramp{"} to biological supercomputing.",
keywords = "Cold spring harbor, DNA subway, Education, Fastx toolkit, Green line, Iplant api, Iplant collaborative, Red line, Rna seq, Rna seq data, Undergraduate",
author = "Hilgert, {Uwe K.K} and Sheldon McKay and Cornel Ghiban and Mohammed Khalfan and David Micklos and Jason Williams",
year = "2014",
doi = "10.1145/2616498.2616575",
language = "English (US)",
isbn = "9781450328937",
booktitle = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - DNA Subway

T2 - Making genome analysis egalitarian

AU - Hilgert, Uwe K.K

AU - McKay, Sheldon

AU - Ghiban, Cornel

AU - Khalfan, Mohammed

AU - Micklos, David

AU - Williams, Jason

PY - 2014

Y1 - 2014

N2 - DNA Subway bundles research-grade bioinformatics tools, highperformance computing, and databases into easy-to-use workflows. Students have been "riding" different lines since 2010, to predict and annotate genes in up to 150kb of raw DNA sequence (Red Line), identify homologs in sequenced genomes (Yellow Line), identify species using DNA barcodes and construct phylogenetic trees (Blue Line), and examine RNA sequence (RNA-Seq) datasets for transcript abundance and differential expression (Green Line). With support for plant and animal genomes, DNA Subway engages students in their own learning, bringing to life key concepts in molecular biology, genetics, and evolution. Integrated DNA barcoding and RNA extraction wet-lab experiments support a variety of inquiry-based projects using student-generated data. Products of student research can be exported, published, and used in follow-up experiments. To date, DNA Subway has over 8,000 registered users who have produced 51,000 projects. Based on the popular Tuxedo Protocol, the Green Line was introduced in January 2014 as an easy-to-use workflow to analyze RNA-Seq datasets. The workflow uses iPlant's APIs (http://agaveapi.co/) to access high-performance compute resources of NSF's Extreme Scientific and Engineering Discovery Environment (XSEDE), providing the first easy "on ramp" to biological supercomputing.

AB - DNA Subway bundles research-grade bioinformatics tools, highperformance computing, and databases into easy-to-use workflows. Students have been "riding" different lines since 2010, to predict and annotate genes in up to 150kb of raw DNA sequence (Red Line), identify homologs in sequenced genomes (Yellow Line), identify species using DNA barcodes and construct phylogenetic trees (Blue Line), and examine RNA sequence (RNA-Seq) datasets for transcript abundance and differential expression (Green Line). With support for plant and animal genomes, DNA Subway engages students in their own learning, bringing to life key concepts in molecular biology, genetics, and evolution. Integrated DNA barcoding and RNA extraction wet-lab experiments support a variety of inquiry-based projects using student-generated data. Products of student research can be exported, published, and used in follow-up experiments. To date, DNA Subway has over 8,000 registered users who have produced 51,000 projects. Based on the popular Tuxedo Protocol, the Green Line was introduced in January 2014 as an easy-to-use workflow to analyze RNA-Seq datasets. The workflow uses iPlant's APIs (http://agaveapi.co/) to access high-performance compute resources of NSF's Extreme Scientific and Engineering Discovery Environment (XSEDE), providing the first easy "on ramp" to biological supercomputing.

KW - Cold spring harbor

KW - DNA subway

KW - Education

KW - Fastx toolkit

KW - Green line

KW - Iplant api

KW - Iplant collaborative

KW - Red line

KW - Rna seq

KW - Rna seq data

KW - Undergraduate

UR - http://www.scopus.com/inward/record.url?scp=84905454454&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84905454454&partnerID=8YFLogxK

U2 - 10.1145/2616498.2616575

DO - 10.1145/2616498.2616575

M3 - Conference contribution

AN - SCOPUS:84905454454

SN - 9781450328937

BT - ACM International Conference Proceeding Series

PB - Association for Computing Machinery

ER -