A Scientific Workflow System For Genomic Data Analysis

<p>Scientific workflows have become increasingly popular as a new computing paradigm for scientists to design and execute complex and distributed scientific processes to enable and accelerate many scientific discoveries. Although several scientific workflow management systems (SWFMSs) have been developed, there is a great need for an integrated scientific workflow system that enables the design and execution of higher-level scientific workflows, which integrate heterogeneous scientific workflows enacted by existing SWFMSs. On one hand, science is becoming increasingly collaborative today, requiring an integrated solution that combines the features and capabilities of different SWFMSs, which are typically developed and optimized towards one single discipline. One the other hand, such an integrated environment can immediately leverage existing and emerging techniques and strengths of various SWFMSs and their supported execution environments, such as Cluster, Grid, and Cloud. The main contributions of this dissertation are: 1) We propose a scientific workflow system, called GENOMEFLOW, to design, develop, and execute higher-level scientific workflows, whose workflow tasks are themselves scientific workflows enacted by existing SWFMSs; 2) We propose a workflow scheduling algorithm, called GSA, to enable the parallel execution of such heterogeneous scientific workflows in their native heterogeneous environments; and 3) We implemented GENOMEFLOW towards the life science community and developed several GENOMEFLOW scientific workflows to demonstrate the capabilities of our system for genome data analysis applications.</p>

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Open Access Dissertation

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2010

Author dc:creator

• Alhiyafi, Jamal Ali Musleh

Contributors dc:contributor

• Shiyong Lu

• bioinformatic
• genomic analysis
• Scientific workflow
• workflow scheduling
• Computer Sciences

Repository record dc:identifier

https://digitalcommons.wayne.edu/oa_dissertations/73

OAI identifier oai:identifier

oai:digitalcommons.wayne.edu:oa_dissertations-1072