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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Agile parallel bioinformatics workflow management using Pwrake.

Hiroyuki Mishima¹, Kensaku Sasaki, Masahiro Tanaka

¹Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, 1-12-4 Sakamoto, Nagasaki, Nagasaki, Japan. hmishima@nagasaki-u.ac.jp.

BMC Research Notes

|September 9, 2011

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Pwrake offers agile scientific workflow management for bioinformatics, improving iterative development efficiency for next-generation sequencing data analysis. This Ruby-based system enhances workflow flexibility and maintainability.

Area of Science:

Bioinformatics
Computational Biology
Software Engineering

Background:

Scientific workflow systems are crucial for managing computational procedures in bioinformatics.
Existing systems are often over-weighted for practical bioinformatics needs.
Agile development principles, emphasizing iterative phases, align well with bioinformatics workflow management.

Purpose of the Study:

To demonstrate the application of the Pwrake scientific workflow system in bioinformatics.
To evaluate Pwrake's suitability for managing complex bioinformatics workflows.
To test the hypothesis that Pwrake offers advantages in bioinformatics workflow management.

Main Methods:

Implemented Pwrake workflows for next-generation sequencing data processing using GATK and Dindel.

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Developed separate workflow definitions for distinct development phases (definition and parameter adjustment).

Introduced helper methods to simplify workflow descriptions and enhance modularity.

Main Results:

Pwrake facilitated agile management of bioinformatics workflows.
The approach of separating workflow definitions improved iterative development efficiency.
Combined workflows demonstrated the modularity of GATK and Dindel workflows.
Pwrake's Ruby-based DSL provided flexibility and readability.

Conclusions:

Pwrake enables agile and efficient scientific workflow management in bioinformatics.
The system's flexibility, readability, and maintainability support workflow sharing.
Pwrake is a valuable tool for managing complex bioinformatics tasks, such as next-generation sequencing data analysis.