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The application of Hadoop in structural bioinformatics
Jamie J Alnasir1, Hugh P Shanahan2
1Institute of Cancer Research, Old Brompton Road, London, United Kingdom.
Briefings in Bioinformatics
|November 22, 2018
Summary
The Hadoop platform offers a framework for analyzing large datasets in structural bioinformatics, aiding high-throughput studies. However, its scalability varies compared to other systems, and usability challenges persist.
Area of Science:
- Structural bioinformatics
- Computational biology
- Big data analytics
Background:
- The Protein Data Bank (PDB) is a critical resource for structural bioinformatics.
- High-throughput studies require efficient analysis of large biological datasets.
- The Hadoop platform offers a distributed computing framework for big data processing.
Purpose of the Study:
- To review the application of the Hadoop platform in structural bioinformatics.
- To assess the scalability and performance of Hadoop implementations in this field.
- To identify barriers and potential improvements for Hadoop adoption in structural bioinformatics.
Main Methods:
- Literature review of existing Hadoop implementations in structural bioinformatics.
- Analysis of reported scalability and performance metrics.
- Identification of common implementation strategies and challenges.
Main Results:
- Hadoop enables high-throughput analyses like protein-ligand docking and structural alignment.
- Implementations often utilize existing executables within MapReduce rather than algorithm rewriting.
- Scalability of Hadoop in structural bioinformatics shows variable performance compared to batch schedulers; Message Passing Interface may scale better.
- Difficulties in interface and configuration are significant barriers to Hadoop adoption.
Conclusions:
- Hadoop presents a valuable framework for large-scale structural bioinformatics analyses.
- Further improvements in Hadoop interfaces (e.g., Spark), cloud integration (Azure, AWS), and standardized workflow languages (WD, CWL, Nextflow) are expected to enhance its usability and adoption.
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