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Perspectives of using Cloud computing in integrative analysis of multi-omics data

Dariusz R Augustyn, Łukasz Wyciślik, Dariusz Mrozek
2021 Briefings in Functional Genomics  
This paper shows perspectives of using Cloud computing advances and containerization approach for such a purpose.  ...  However, many omics data analysis solutions focus only on a selected problem, disease, types of data or organisms.  ...  Similarly, GenomeSpace [38] serves as a platform for genome-wide analysis by integrating and disclosing access to several widely accepted analysis and visualization tools and data sources and by providing  ... 
doi:10.1093/bfgp/elab007 pmid:33676373 fatcat:ykypxevpzfftvnuhqj3gtqj544

The Globus Galaxies platform: delivering science gateways as a service

Ravi Madduri, Kyle Chard, Ryan Chard, Lukasz Lacinski, Alex Rodriguez, Dinanath Sulakhe, David Kelly, Utpal Dave, Ian Foster
2015 Concurrency and Computation  
The design and implementation of this platform leverages our several years experience with Globus Genomics, a cloud-based science gateway that has served more than 200 genomics researchers across 30 institutions  ...  Building on that foundation, we have implemented a platform that leverages the popular Galaxy system for application hosting and workflow execution; Globus services for data transfer, user and group management  ...  Cloud-init is a widely used script-based system for installing and configuring software on a newly created instance.  ... 
doi:10.1002/cpe.3486 fatcat:7cbkdtjgzjbc5kasgg4yqhnfny

Serverless computing in omics data analysis and integration

Piotr Grzesik, Dariusz R Augustyn, Łukasz Wyciślik, Dariusz Mrozek
2021 Briefings in Bioinformatics  
We start by reviewing the application of the cloud computing model to a multi-omics data analysis and exposing some shortcomings of the early approaches.  ...  Execution of many such analyses can be accelerated by applying the cloud computing paradigm, which provides scalable resources for storing data of different types and parallelizing data analysis computations  ...  Both approaches provided by Cloud Run are compatible (https://cloud.google.co m/anthos/run/docs/choosing-a-platform).  ... 
doi:10.1093/bib/bbab349 pmid:34505137 pmcid:PMC8499876 fatcat:lqlrhoycnbg3xdygxpfejn6xvu

Experiences building Globus Genomics: a next-generation sequencing analysis service using Galaxy, Globus, and Amazon Web Services

Ravi K. Madduri, Dinanath Sulakhe, Lukasz Lacinski, Bo Liu, Alex Rodriguez, Kyle Chard, Utpal J. Dave, Ian T. Foster
2014 Concurrency and Computation  
We describe Globus Genomics, a system that we have developed for rapid analysis of large quantities of next-generation sequencing (NGS) genomic data.  ...  This system achieves a high degree of end-to-end automation that encompasses every stage of data analysis including initial data retrieval from remote sequencing centers or storage (via the Globus file  ...  We thank Globus Genomics users for their invaluable contributions.  ... 
doi:10.1002/cpe.3274 pmid:25342933 pmcid:PMC4203657 fatcat:glcie6spdzdllakjibkyniqo5y

InfiniCloud: Leveraging the Global InfiniCortex Fabric and OpenStack Cloud for Borderless High Performance Computing of Genomic Data

2015 Supercomputing Frontiers and Innovations  
InfiniCloud is a geographically distributed, high performance InfiniBand HPC Cloud which aims to enable borderless processing of genomic data as the part of the InfiniCortex project.  ...  This paper provides a high-level technical overview of the architecture of InfiniCloud and how it can be used for high performance computation of genomic data in geographically distant sites by encapsulation  ...  This work was supported by the A*STAR Computational Resource Centre through the use of its high performance computing facilities.  ... 
doi:10.14529/jsfi150302 fatcat:yx4acfes4fenjhrowq4kwx6co4

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends

Emad A Mohammed, Behrouz H Far, Christopher Naugler
2014 BioData Mining  
MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters.  ...  The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis.  ...  /[68] 2013 MapReduce algorithms Enhanced algorithm Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing/[69] 2013 Cloud Whole-genome sequencing Study  ... 
doi:10.1186/1756-0381-7-22 pmid:25383096 pmcid:PMC4224309 fatcat:zpis7kklerh2vna5le2gtxc5vi

Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community

Konstantinos Krampis, Tim Booth, Brad Chapman, Bela Tiwari, Mesude Bicak, Dawn Field, Karen E Nelson
2012 BMC Bioinformatics  
Conclusions: Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud.  ...  This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them.  ...  Acknowledgements We would like to thank all the Cloud BioLinux developers and community members that have volunteered their time on this project. Enis Afgan  ... 
doi:10.1186/1471-2105-13-42 pmid:22429538 pmcid:PMC3372431 fatcat:jt7b6p6wmja3hosaekuejm2e2a

The Cancer Genomics Cloud: Collaborative, Reproducible, and Democratized—A New Paradigm in Large-Scale Computational Research

Jessica W. Lau, Erik Lehnert, Anurag Sethi, Raunaq Malhotra, Gaurav Kaushik, Zeynep Onder, Nick Groves-Kirkby, Aleksandar Mihajlovic, Jack DiGiovanna, Mladen Srdic, Dragan Bajcic, Jelena Radenkovic (+8 others)
2017 Cancer Research  
The Seven Bridges Cancer Genomics Cloud (CGC; www. cancergenomicscloud.org) enables researchers to rapidly access and collaborate on massive public cancer genomic datasets, including The Cancer Genome  ...  Data of interest can be immediately analyzed in the cloud using more than 200 preinstalled, curated bioinformatics tools and workflows.  ...  Acknowledgments We thank the entire Seven Bridges team, the Cancer Genomics Cloud Pilot teams from the NCI, the Broad Institute, and the Institute of Systems Biology, the Genomic Data Commons team, countless  ... 
doi:10.1158/0008-5472.can-17-0387 pmid:29092927 fatcat:fdpfepbfunaz7o2k2x3gn2wzky

RAPPORT: running scientific high-performance computing applications on the cloud

J. Cohen, I. Filippis, M. Woodbridge, D. Bauer, N. Chue Hong, M. Jackson, S. Butcher, D. Colling, J. Darlington, B. Fuchs, M. Harvey
2012 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences  
Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing  ...  physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure.  ...  We would like to thank JISC and EPSRC for funding the RAPPORT project (EP/I034246/1) under their Pilot Projects for Cloud Computing in Research programme.  ... 
doi:10.1098/rsta.2012.0073 pmid:23230157 fatcat:a2kiquhljffsblicudkazqbqsa

Gathering clouds and a sequencing storm

2010 Nature Biotechnology  
In this approach, a user rents processing time on a computer cluster (e.g., from Amazon) through a virtual operating system (or 'cloud'), which can load software and provide an access point for running  ...  The first software (CrossBow) capable of performing alignment and single nucleotide polymorphism analysis on multiple whole-human data sets on a computing cloud was published just 6 weeks ago (Genome Biol  ... 
doi:10.1038/nbt0110-1 pmid:20062015 fatcat:pub2hypx4zarjljxt3edfuvima

An efficient and robust parallel scheduler for bioinformatics applications in a public cloud: A bigdata approach

Leena Ammanna, Jagadeeshgowda Jagadeeshgowda, Jagadeesh Pujari
2022 Indonesian Journal of Electrical Engineering and Computer Science  
To address the issue with Hadoop's MapReduce framework, a customised MapReduce framework is developed on the Azure cloud platform.  ...  <p>In bioinformatics, genomic sequence alignment is a simple method for handling and analysing data, and it is one of the most important applications in determining the structure and function of protein  ...  For biosequence alignment, the BLASTx algorithm is used, and a parallel MapReduce execution approach based on Azure cloud is used in the BLAST-BSPMR cloud platform.  ... 
doi:10.11591/ijeecs.v25.i2.pp1078-1086 fatcat:cp3alt77wbebbpax4hiya5fpnu

A Review of Scalable Bioinformatics Pipelines

Bjørn Fjukstad, Lars Ailo Bongo
2017 Data Science and Engineering  
The pipelines used to implement analyses must therefore scale with respect to the resources on a single compute node, the number of nodes on a cluster, and also to cost-performance.  ...  Scalability is increasingly important for bioinformatics analysis services, since these must handle larger datasets, more jobs, and more users.  ...  The pipeline can run unmodified analysis tools by wrapping these using their genome data parallel toolkit.  ... 
doi:10.1007/s41019-017-0047-z fatcat:7wyzccy7ffhjdd46pfmljrzioy

The impact of next-generation sequencing on genomics

Jun Zhang, Rod Chiodini, Ahmed Badr, Genfa Zhang
2011 Journal of Genetics and Genomics  
As evidenced throughout this review, NGS technologies will have a striking impact on genomic research and the entire biological field.  ...  But, the massive data produced by NGS also presents a significant challenge for data storage, analyses, and management solutions.  ...  A possible solution is cloud computing. In cloud computing, a user can use a virtual operating system (or "cloud") to process data on a computer cluster for high parallel tasks (Editorial, 2010) .  ... 
doi:10.1016/j.jgg.2011.02.003 pmid:21477781 pmcid:PMC3076108 fatcat:25bsmx6zdnejlc6g5kmh5wejzu

Cloud Computing for Next-Generation Sequencing Data Analysis [chapter]

Shanrong Zhao, Kirk Watrous, Chi Zhang, Baohong Zhang
2017 Cloud Computing - Architecture and Applications  
share the lessons we learned from the implementation of Rainbow, a cloud-based tool for large-scale genome sequencing data analysis.  ...  Genomics studies of large populations are producing a huge amount of data, giving rise to computational issues around the storage, transfer, and analysis of the data.  ...  PeakRanger [48] is a software package for the analysis of ChIP-seq data. It can be run in a parallel cloud computing environment to obtain extremely high performance on large data sets.  ... 
doi:10.5772/66732 fatcat:2ewdbtp2bjhx7j7tj4e3auwqke

Computational solutions to large-scale data management and analysis

Eric E. Schadt, Michael D. Linderman, Jon Sorenson, Lawrence Lee, Garry P. Nolan
2010 Nature reviews genetics  
Cloud-based computing The abstraction of the underlying hardware architectures (for example, servers, storage and networking) that enable convenient, on-demand network access to a shared pool of computing  ...  The GPU port of NAMD, a widely used program for molecular dynamics simulation, running on a 4-GPU cluster outperforms a cluster with 16 quad-core GPPs (48 cores).  ...  ; creating instances in Amazon EC2; and running data-processing programs on those instances, including the analysis of big data sets using MapReduce-based algorithms.  ... 
doi:10.1038/nrg2857 pmid:20717155 pmcid:PMC3124937 fatcat:a43tfxx6nzf4vg6rm5w44olgky
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