PMID- 29374408
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20191120
IS  - 2476-762X (Electronic)
IS  - 1513-7368 (Print)
IS  - 1513-7368 (Linking)
VI  - 19
IP  - 1
DP  - 2018 Jan 27
TI  - Cancer Diagnosis Epigenomics Scientific Workflow Scheduling in the Cloud 
      Computing Environment Using an Improved PSO Algorithm.
PG  - 243-246
AB  - Objective: Epigenetic modifications involving DNA methylation and histone statud 
      are responsible for the stable maintenance of cellular phenotypes. Abnormalities 
      may be causally involved in cancer development and therefore could have 
      diagnostic potential. The field of epigenomics refers to all epigenetic 
      modifications implicated in control of gene expression, with a focus on better 
      understanding of human biology in both normal and pathological states. 
      Epigenomics scientific workflow is essentially a data processing pipeline to 
      automate the execution of various genome sequencing operations or tasks. Cloud 
      platform is a popular computing platform for deploying large scale epigenomics 
      scientific workflow. Its dynamic environment provides various resources to 
      scientific users on a pay-per-use billing model. Scheduling epigenomics 
      scientific workflow tasks is a complicated problem in cloud platform. We here 
      focused on application of an improved particle swam optimization (IPSO) algorithm 
      for this purpose. Methods: The IPSO algorithm was applied to find suitable 
      resources and allocate epigenomics tasks so that the total cost was minimized for 
      detection of epigenetic abnormalities of potential application for cancer 
      diagnosis. Result: The results showed that IPSO based task to resource mapping 
      reduced total cost by 6.83 percent as compared to the traditional PSO algorithm. 
      Conclusion: The results for various cancer diagnosis tasks showed that IPSO based 
      task to resource mapping can achieve better costs when compared to PSO based 
      mapping for epigenomics scientific application workflow.
CI  - Creative Commons Attribution License
FAU - N, Sadhasivam
AU  - N S
AD  - Department of Computer Science and Engineering, Bannari Amman Institute of 
      Technology, Sathyamangalam, Erode, India. Email: sadhasivamn82@gmail.com
FAU - R, Balamurugan
AU  - R B
FAU - M, Pandi
AU  - M P
LA  - eng
PT  - Journal Article
DEP - 20180127
PL  - Thailand
TA  - Asian Pac J Cancer Prev
JT  - Asian Pacific journal of cancer prevention : APJCP
JID - 101130625
PMC - PMC5844625
OTO - NOTNLM
OT  - *Cancer diagnosis
OT  - *genomics
OT  - *gene expression
OT  - *particle swam optimization
OT  - *scientific workflow
OT  - *scheduling
EDAT- 2018/01/28 06:00
MHDA- 2018/01/28 06:01
PMCR- 2018/03/01
CRDT- 2018/01/28 06:00
PHST- 2018/01/28 06:00 [pubmed]
PHST- 2018/01/28 06:01 [medline]
PHST- 2018/01/28 06:00 [entrez]
PHST- 2018/03/01 00:00 [pmc-release]
AID - APJCP-19-243 [pii]
AID - 10.22034/APJCP.2018.19.1.243 [doi]
PST - epublish
SO  - Asian Pac J Cancer Prev. 2018 Jan 27;19(1):243-246. doi: 
      10.22034/APJCP.2018.19.1.243.