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Title: Towards Composing Data Aware Systems Biology Workflows on Cloud Platforms: A MeDICi-based Approach

Abstract

Cloud computing is being increasingly adopted for deploying systems biology scientific workflows. Scientists developing these workflows use a wide variety of fragmented and competing data sets and computational tools of all scales to support their research. To this end, the synergy of client side workflow tools with cloud platforms is a promising approach to share and reuse data and workflows. In such systems, the location of data and computation is essential consideration in terms of quality of service for composing a scientific workflow across remote cloud platforms. In this paper, we describe a cloud-based workflow for genome annotation processing that is underpinned by MeDICi - a middleware designed for data intensive scientific applications. The workflow implementation incorporates an execution layer for exploiting data locality that routes the workflow requests to the processing steps that are colocated with the data. We demonstrate our approach by composing two workflowswith the MeDICi pipelines.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1030870
Report Number(s):
PNNL-SA-80025
TRN: US201124%%501
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: Proceedings. 2011 IEEE International World Congress on Services (SERVICES 2011), July 4-9, 2011, Washington DC, 184-191
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; BIOLOGY; COMPUTER CODES; PROGRAMMING; IMPLEMENTATION; PIPELINES; PROCESSING; Scientific workflow; cloud computing; systems biology

Citation Formats

Gorton, Ian, Liu, Yan, Yin, Jian, Kulkarni, Anand V, and Wynne, Adam S. Towards Composing Data Aware Systems Biology Workflows on Cloud Platforms: A MeDICi-based Approach. United States: N. p., 2011. Web. doi:10.1109/SERVICES.2011.22.
Gorton, Ian, Liu, Yan, Yin, Jian, Kulkarni, Anand V, & Wynne, Adam S. Towards Composing Data Aware Systems Biology Workflows on Cloud Platforms: A MeDICi-based Approach. United States. https://doi.org/10.1109/SERVICES.2011.22
Gorton, Ian, Liu, Yan, Yin, Jian, Kulkarni, Anand V, and Wynne, Adam S. 2011. "Towards Composing Data Aware Systems Biology Workflows on Cloud Platforms: A MeDICi-based Approach". United States. https://doi.org/10.1109/SERVICES.2011.22.
@article{osti_1030870,
title = {Towards Composing Data Aware Systems Biology Workflows on Cloud Platforms: A MeDICi-based Approach},
author = {Gorton, Ian and Liu, Yan and Yin, Jian and Kulkarni, Anand V and Wynne, Adam S},
abstractNote = {Cloud computing is being increasingly adopted for deploying systems biology scientific workflows. Scientists developing these workflows use a wide variety of fragmented and competing data sets and computational tools of all scales to support their research. To this end, the synergy of client side workflow tools with cloud platforms is a promising approach to share and reuse data and workflows. In such systems, the location of data and computation is essential consideration in terms of quality of service for composing a scientific workflow across remote cloud platforms. In this paper, we describe a cloud-based workflow for genome annotation processing that is underpinned by MeDICi - a middleware designed for data intensive scientific applications. The workflow implementation incorporates an execution layer for exploiting data locality that routes the workflow requests to the processing steps that are colocated with the data. We demonstrate our approach by composing two workflowswith the MeDICi pipelines.},
doi = {10.1109/SERVICES.2011.22},
url = {https://www.osti.gov/biblio/1030870}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Sep 08 00:00:00 EDT 2011},
month = {Thu Sep 08 00:00:00 EDT 2011}
}

Conference:
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