The Experts below are selected from a list of 66375 Experts worldwide ranked by ideXlab platform
Sheldon J Mckay - One of the best experts on this subject based on the ideXlab platform.
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using the iplant collaborative Discovery Environment
Current protocols in human genetics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.
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phylogenetic analysis with the iplant Discovery Environment
Current protocols in human genetics, 2013Co-Authors: Naim Matasci, Sheldon J MckayAbstract:The iPlant Collaborative's Discovery Environment is a unified Web portal to many bioinformatics applications and analytical workflows, including various methods of phylogenetic analysis. This unit describes example protocols for phylogenetic analyses, starting at sequence retrieval from the GenBank sequence database, through to multiple sequence alignment inference and visualization of phylogenetic trees. Methods for extracting smaller sub-trees from very large phylogenies, and the comparative method of continuous ancestral character state reconstruction based on observed morphology of extant species related to their phylogenetic relationships, are also presented. © 2013 by John Wiley & Sons, Inc.
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Using the iPlant collaborative Discovery Environment.
Current protocols in bioinformatics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples.
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Current Protocols in Bioinformatics - Using the iPlant collaborative Discovery Environment.
Current Protocols in Bioinformatics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.
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Current Protocols in Bioinformatics - Phylogenetic analysis with the iPlant Discovery Environment.
Current Protocols in Bioinformatics, 2013Co-Authors: Naim Matasci, Sheldon J MckayAbstract:The iPlant Collaborative's Discovery Environment is a unified Web portal to many bioinformatics applications and analytical workflows, including various methods of phylogenetic analysis. This unit describes example protocols for phylogenetic analyses, starting at sequence retrieval from the GenBank sequence database, through to multiple sequence alignment inference and visualization of phylogenetic trees. Methods for extracting smaller sub-trees from very large phylogenies, and the comparative method of continuous ancestral character state reconstruction based on observed morphology of extant species related to their phylogenetic relationships, are also presented. © 2013 by John Wiley & Sons, Inc.
Nirav Merchant - One of the best experts on this subject based on the ideXlab platform.
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Bringing your tools to CyVerse Discovery Environment using Docker
F1000Research, 2016Co-Authors: Upendra Kumar Devisetty, Paul Sarando, Kathleen Kennedy, Nirav Merchant, Eric LyonsAbstract:Docker has become a very popular container-based virtualization platform for software distribution that has revolutionized the way in which scientific software and software dependencies (software stacks) can be packaged, distributed, and deployed. Docker makes the complex and time-consuming installation procedures needed for scientific software a one-time process. Because it enables platform-independent installation, versioning of software Environments, and easy redeployment and reproducibility, Docker is an ideal candidate for the deployment of identical software stacks on different compute Environments such as XSEDE and Amazon AWS. Cyverse's Discovery Environment also uses Docker for integrating its powerful, community-recommended software tools into CyVerse's production Environment for public use. This paper will help users bring their tools into CyVerse DE which will not only allows users to integrate their tools with relative ease compared to the earlier method of tool deployment in DE but also help users to share their apps with collaborators and also release them for public use.
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a genome wide association study platform built on iplant cyber infrastructure
Concurrency and Computation: Practice and Experience, 2015Co-Authors: Liya Wang, Doreen Ware, Nirav Merchant, Carol Lushbough, Lincoln SteinAbstract:Summary We demonstrate a flexible genome-wide association study platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large-scale study of both genotype and phenotype data on clusters. End users can add their own analysis tools and create customized analysis workflows through the graphical user interfaces in both iPlant Discovery Environment and BioExtract server. Copyright © 2014 John Wiley & Sons, Ltd.
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A genome‐wide association study platform built on iPlant cyber‐infrastructure
Concurrency and Computation: Practice and Experience, 2014Co-Authors: Liya Wang, Doreen Ware, Nirav Merchant, Carol Lushbough, Lincoln SteinAbstract:Summary We demonstrate a flexible genome-wide association study platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large-scale study of both genotype and phenotype data on clusters. End users can add their own analysis tools and create customized analysis workflows through the graphical user interfaces in both iPlant Discovery Environment and BioExtract server. Copyright © 2014 John Wiley & Sons, Ltd.
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a gwas platform built on iplant cyber infrastructure
bioRxiv, 2014Co-Authors: Liya Wang, Doreen Ware, Nirav Merchant, Carol Lushbough, Lincoln SteinAbstract:We demonstrated a flexible Genome-Wide Association Study (GWAS) platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large scale study of both genotype and phenotype data on clusters. End users can add their own analysis tools, and create customized analysis workflows through the graphical user interfaces in both iPlant Discovery Environment and BioExtract server.
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using the iplant collaborative Discovery Environment
Current protocols in human genetics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.
Craig A Stewart - One of the best experts on this subject based on the ideXlab platform.
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return on investment for three cyberinfrastructure facilities a local campus supercomputer the nsf funded jetstream cloud system and xsede the extreme science and engineering Discovery Environment
IEEE ACM International Conference Utility and Cloud Computing, 2018Co-Authors: Craig A Stewart, David Y Hancock, Julie Wernert, Matthew R Link, Nancy Wilkinsdiehr, Therese Miller, Kelly Gaither, Winona SnappchildsAbstract:The economics of high performance computing are rapidly changing. Commercial cloud offerings, private research clouds, and pressure on the budgets of institutions of higher education and federally-funded research organizations are all contributing factors. As such, it has become a necessity that all expenses and investments be analyzed and considered carefully. In this paper we will analyze the return on investment (ROI) for three different kinds of cyberinfrastructure resources: the eXtreme Science and Engineering Discovery Environment (XSEDE); the NSF-funded Jetstream cloud system; and the Indiana University (IU) Big Red II supercomputer, funded exclusively by IU for use of the IU community and collaborators. We determined the ROI for these three resources by assigning financial values to services by either comparison with commercially available services, or by surveys of value of these resources to their users. In all three cases, the ROI for these very different types of cyberinfrastructure resources was well greater than 1 - meaning that investors are getting more than $1 in returned value for every $1 invested. While there are many ways to measure the value and impact of investment in cyberinfrastructure resources, we are able to quantify the short-term ROI and show that it is a net positive for campuses and the federal government respectively.
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return on investment for three cyberinfrastructure facilities a local campus supercomputer the nsf funded jetstream cloud system and xsede the extreme science and engineering Discovery Environment
IEEE ACM International Conference Utility and Cloud Computing, 2018Co-Authors: Craig A Stewart, David Y Hancock, Julie Wernert, Matthew R Link, Nancy Wilkinsdiehr, Therese Miller, Kelly Gaither, Winona SnappchildsAbstract:The economics of high performance computing are rapidly changing. Commercial cloud offerings, private research clouds, and pressure on the budgets of institutions of higher education and federally-funded research organizations are all contributing factors. As such, it has become a necessity that all expenses and investments be analyzed and considered carefully. In this paper we will analyze the return on investment (ROI) for three different kinds of cyberinfrastructure resources: the eXtreme Science and Engineering Discovery Environment (XSEDE); the NSF-funded Jetstream cloud system; and the Indiana University (IU) Big Red II supercomputer, funded exclusively by IU for use of the IU community and collaborators. We determined the ROI for these three resources by assigning financial values to services by either comparison with commercially available services, or by surveys of value of these resources to their users. In all three cases, the ROI for these very different types of cyberinfrastructure resources was well greater than 1 - meaning that investors are getting more than $1 in returned value for every $1 invested. While there are many ways to measure the value and impact of investment in cyberinfrastructure resources, we are able to quantify the short-term ROI and show that it is a net positive for campuses and the federal government respectively.
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UCC - Return on Investment for Three Cyberinfrastructure Facilities: A Local Campus Supercomputer, the NSF-Funded Jetstream Cloud System, and XSEDE (the eXtreme Science and Engineering Discovery Environment)
2018 IEEE ACM 11th International Conference on Utility and Cloud Computing (UCC), 2018Co-Authors: Craig A Stewart, David Y Hancock, Julie Wernert, Matthew R Link, Therese Miller, Kelly Gaither, Nancy Wilkins-diehr, Winona Snapp-childsAbstract:The economics of high performance computing are rapidly changing. Commercial cloud offerings, private research clouds, and pressure on the budgets of institutions of higher education and federally-funded research organizations are all contributing factors. As such, it has become a necessity that all expenses and investments be analyzed and considered carefully. In this paper we will analyze the return on investment (ROI) for three different kinds of cyberinfrastructure resources: the eXtreme Science and Engineering Discovery Environment (XSEDE); the NSF-funded Jetstream cloud system; and the Indiana University (IU) Big Red II supercomputer, funded exclusively by IU for use of the IU community and collaborators. We determined the ROI for these three resources by assigning financial values to services by either comparison with commercially available services, or by surveys of value of these resources to their users. In all three cases, the ROI for these very different types of cyberinfrastructure resources was well greater than 1 - meaning that investors are getting more than $1 in returned value for every $1 invested. While there are many ways to measure the value and impact of investment in cyberinfrastructure resources, we are able to quantify the short-term ROI and show that it is a net positive for campuses and the federal government respectively.
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XSEDE - Methods For Creating XSEDE Compatible Clusters
Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment - XSEDE '14, 2014Co-Authors: Jeremy Fischer, Richard Knepper, Craig A Stewart, David Lifka, Matthew Standish, Resa Alvord, Barbara Hallock, Victor HazlewoodAbstract:The Extreme Science and Engineering Discovery Environment has created a suite of software that is collectively known as the basic XSEDE-compatible cluster build. It has been distributed as a Rocks roll for some time. It is now available as individual RPM packages, so that it can be downloaded and installed in portions as appropriate on existing and working clusters. In this paper, we explain the concept of the XSEDE-compatible cluster and explain how to install individual components as RPMs through use of Puppet and the XSEDE compatible cluster YUM repository.
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XSEDE Campus Bridging – Cluster software distribution strategy and tactics
2013Co-Authors: Victor Hazlewood, Richard Knepper, David Lifka, Steven Lee, John-paul Navarro, Craig A StewartAbstract:XSEDE is supported by National Science Foundation Grant 1053575 (XSEDE: eXtreme Science and Engineering Discovery Environment).
Upendra K. Devisetty - One of the best experts on this subject based on the ideXlab platform.
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Read Mapping and Transcript Assembly: A Scalable and High-Throughput Workflow for the Processing and Analysis of Ribonucleic Acid Sequencing Data.
Frontiers in genetics, 2020Co-Authors: Sateesh Peri, Eric Lyons, Sarah Roberts, Isabella R Kreko, Lauren B Mchan, Alexandra Naron, Archana Ram, Rebecca L. Murphy, Brian D. Gregory, Upendra K. DevisettyAbstract:Next-generation RNA-sequencing is an incredibly powerful means of generating a snapshot of the transcriptomic state within a cell, tissue, or whole organism. As the questions addressed by RNA-sequencing (RNA-seq) become both more complex and greater in number, there is a need to simplify RNA-seq processing workflows, make them more efficient and interoperable, and capable of handling both large and small datasets. This is especially important for researchers who need to process hundreds to tens of thousands of RNA-seq datasets. To address these needs, we have developed a scalable, user-friendly, and easily deployable analysis suite called RMTA (Read Mapping, Transcript Assembly). RMTA can easily process thousands of RNA-seq datasets with features that include automated read quality analysis, filters for lowly expressed transcripts, and read counting for differential expression analysis. RMTA is containerized using Docker for easy deployment within any compute Environment [cloud, local, or high-performance computing (HPC)] and is available as two apps in CyVerse's Discovery Environment, one for normal use and one specifically designed for introducing undergraduates and high school to RNA-seq analysis. For extremely large datasets (tens of thousands of FASTq files) we developed a high-throughput, scalable, and parallelized version of RMTA optimized for launching on the Open Science Grid (OSG) from within the Discovery Environment. OSG-RMTA allows users to utilize the Discovery Environment for data management, parallelization, and submitting jobs to OSG, and finally, employ the OSG for distributed, high throughput computing. Alternatively, OSG-RMTA can be run directly on the OSG through the command line. RMTA is designed to be useful for data scientists, of any skill level, interested in rapidly and reproducibly analyzing their large RNA-seq data sets.
Shannon L Oliver - One of the best experts on this subject based on the ideXlab platform.
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using the iplant collaborative Discovery Environment
Current protocols in human genetics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.
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Using the iPlant collaborative Discovery Environment.
Current protocols in bioinformatics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples.
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Current Protocols in Bioinformatics - Using the iPlant collaborative Discovery Environment.
Current Protocols in Bioinformatics, 2013Co-Authors: Shannon L Oliver, Nirav Merchant, Andrew J Lenards, Roger A Barthelson, Sheldon J MckayAbstract:The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.