Table 3 Summary of reviewed research in clinical big data analysis using the MapReduce programming model
Study category | Study Name/Reference | Study year | Technology used | Application |
|---|---|---|---|---|
Public database | A drug-adverse event extraction algorithm to support pharmacovigilance knowledge mining from PubMed citations/[30] | 2011 | A MapReduce based algorithm for common adverse drug events (ADE) detection | Biomedical data mining |
Identifying unproven cancer treatments on the health web: Addressing accuracy, generalizability and scalability/[31] | 2012 | Using MapReduce and Markove boundary feature selection | Identify unproven cancer treatments on the health web | |
A user-friendly tool to transform large scale administrative data into wide table format using a MapReduce program with a pig latin based script/[33] | 2012 | MapRedcue and Pig Latin | Administrative data management | |
Biometric | Leveraging the cloud for big data biometrics: Meeting the performance requirements of the next generation biometric systems/[34] | 2011 | MapReduce machine learning algorithms for image regnition on Hadoop paltform | Design of secuirty system using biometric identification |
Iris recognition on hadoop: A biometrics system implementation on cloud computing/[35] | 2011 | Human iris MapReduce search algorithm on the cloud | Data retrival and secuirty system | |
Cloud-ready biometric system for mobile security access/[36] | 2012 | MapReduce algorithm to capture and recognition of biometric information | Biometric-identification mobile phone applications | |
Genome and Protein data analysis | Parallelizing bioinformatics applications with MapReduce/[54] | 2008 | MapRedcue algorithms | Bioinformatics applications |
Cloudblast: Combining MapReduce and virtualization on distributed resources for bioinformatics applications/[55] | 2008 | Cloud/MapReduce | Bioinformatics applications | |
CloudBurst: highly sensitive read mapping with MapReduce/[50] | 2009 | MapRedcue algorithms | Genome sequence mapping tool | |
Cloud technologies for bioinformatics applications/[53] | 2009 | Cloud/MapReduce | Bioinformatics applications | |
The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data/[44] | 2010 | HBase for data management and MapReduce jobs for computation | Genome sequence comparison application | |
Nephele: genotyping via complete composition vectors and MapReduce/[64] | 2011 | MapReduce Algorithms | Genotyping sequence tool | |
A graphical execution platform for MapReduce programs on private and public clouds/[59] | 2012 | Cloud/MapReduce | Bioinformatics applications | |
Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework/[60] | 2012 | MapReduce Algorithms | Bioinformatics applications | |
An efficient algorithm for DNA fragment assembly in MapReduce/[48] | 2012 | MapReduce algorithm for DNA framentation | A tool for DNA fragmentation assembly | |
De novo assembly of high-throughput sequencing data with cloud computing and new operations on string graphs/[43] | 2012 | String graph based on the MapReduce algorithms | Distributed Genome assembler | |
Fractal MapReduce decomposition of sequence alignment/[63] | 2012 | MapReduce Algorithms | Genome sequence alignment tool | |
Genotyping in the cloud with crossbow/[70] | 2012 | Cloud | Genotyping application | |
BioPig: A hadoop-based analytic toolkit for large-scale sequence data [40] | 2013 | MapReduce algorithms | Bioinformatics processing tool known as BioPig | |
Implementation of a parallel protein structure alignment service on cloud/[46] | 2013 | MapReduce alignment algorithm | Protein alignment application | |
BlueSNP: R package for highly scalable genome-wide association studies using hadoop clusters/[47] | 2013 | R alagorithms executed on top of the Hadoop platform | Statistical package in R for Genome analysis | |
Enhancement of accuracy and efficiency for RNA secondary structure prediction by sequence segmentation and MapReduce/[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 Category | Study Name/Reference | Study year | Technology used | Application |
Genome and Protein data analysis | Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes/[62] | 2013 | MapReduce Algorithms | multivariate neuroimaging phenotypes |
Novel and efficient tag SNPs selection algorithms/[37] | 2014 | MapReduce algorithm for efficient selection of SNP | Genom analysis | |
Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment/[66] | 2014 | Cloud | Algorithm for inferring gene networks | |
Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline/[71] | 2014 | Cloud | sequence analysis application | |
Biomedical signal analysis | HBase, MapReduce, and integrated data visualization for processing clinical signal data/[39] | 2011 | HBase for data mangement and MapReduce processing algorithm | Store and processing clinical signals |
Parallel processing of massive EEG data with MapReduce/[73] | 2012 | MapReduce EEMD algorithm | Massive biomedical signal processing | |
Biomedical image analysis | Hadoop-gis: A high performance query system for analytical medical imaging with MapReduce/[74] | 2011 | HBase for data management and MapReduce processing algorithm | Store and processing of medical images |
Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment [76] | 2011 | MapReduce image processing algorithms on the Cloud | Accelerates FDK algorithm for the cone-beam CT | |
Using MapReduce for Large-Scale Medical Image Analysis/[75] | 2012 | MapReduce algorithm | Medical Image Analysis |