Cutting edge computational solutions for large scale high-dimensional data sets arising out of new biology
Cutting edge computational solutions for large scale high-dimensional data sets arising out of new biology
New biology is a branch of biology that that deals with the nature of biological phenomenon at the molecular
level. In post genomic era a new language has been created for new biology viz.,Genomics,Functional Genomics,
Proteomics,cDNA,microarrays, Global Gene Expression Patterns .New Computational Tools are used for Sequencing,
Analyzing experimental data, Searching, Pattern matching, Data mining, Gene discovery, Function discovery aiming to
Classify, Identify patterns, predictions, Create models & Prediction, Assessment and Comparison,Optimization,Better utilize
existing knowledge. The new wave of high-throughput technologies in genomics and proteomics are constantly improving and
generating an unprecedented amount of data that can be termed as Big Data means large data sets in terms of volume, variety,
velocity, variability, veracity, & complexity. Bioinformatics researchers are currently confronted with a huge challenge of
handling, processing and moving these large-scale biological data, a problem that will only increase in coming years. Therefore,
cloud computing bears great promise for effectively addressing issues of large-scale data generated by high-throughput
technologies in the fields of genomics, proteomics and other biological research areas. Cloud-based bioinformatics resources
have changed the approaches toward huge datasets, providing much faster data acquisition, analysis rates and storage. New
cloud-based bioinformatics computing tools, algorithms, and workflows are consistently being developed and successfully
deployed. Basically, the cloud refers to software and services that run on the internet instead of one’s computer. The increased
use of next generation sequencing has led to challenges in data analysis, large-scale data storage and management, multi-site
data integration, validation for quality and scale-up of informatics. It is integral to overcome these analysis and informatics
challenges to successfully translate NGS research and data from the lab to clinical stage. Success in the life sciences will depend
on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which
in turn requires us to adopt advances in informatics. New technological advances and the availability of ‘big data’ enable us to
probe deep into the origin of life and to further understand evolutionary processes. This paper reviews the current development
of cloud based computational technologies that can be applied and pinpoints their potential beneficial applications as well as
implications for Life Sciences. Big data Analytics platforms that offer implementations of the Map Reduce computational
pattern e.g., Hadoop make it easy for developers to perform data-intensive computations at scale is also highlighted. The New
Biology approach has the potential to meet critical societal goals in food, the environment, energy, and health.
5th International Conference on Biometrics & Biostatistics October 20-21, 2016 Houston, USA
Ajit Kumar Roy, J Biom Biostat 2016, 7:4(Suppl) http://dx.doi.org/10.4172/2155-6180.C1.001
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