big data in biology

Biology : The big challenges of big data
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BY VIVIEN MARX Biologists are joining the big – data club. With the advent of high-throughput genomics, life scientists are starting to grapple with massive data sets, encountering challenges with handling, processing and moving information that were once the domain of

Big data : The future of biocuration
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Centre for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization of Information and Systems, Yata, Mishima 411-8540, Japan. Takashi Gojobori. J. Craig Venter Institute, Applied Bioinformatics, Rockville, Maryland 20850, USA

What difference does quantity make On the epistemology of Big Data in biology
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Is Big Data science a whole new way of doing research And what difference does data quantity make to knowledge production strategies and their outputs I argue that the novelty of Big Data science does not lie in the sheer quantity of data involved, but rather in (1) the

Big data : astronomical or genomical
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Genomics is a Big Data science and is going to get much bigger, very soon, but it is not known whether the needs of genomics will exceed other Big Data domains. Projecting to the year 2025, we compared genomics with three other major generators of Big Data

Big Science and Big Data in Biology : From the International Geophysical Year through the International Biological Program to the Long Term Ecological Research
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This paper discusses the historical connections between two large-scale undertakings that became exemplars for worldwide data -driven scientific initiatives after World War II: the International Geophysical Year (1957 1958) and the International Biological Program Biology is now one of the fastest growing fields of big data science. Cloud computing and big data technologies can be used to deal with biologys big data sets. Challenges associated with cloud computing and big data technologies in biology are discussed. Abstract Big data biology bioinformatics, computational biology , systems biology (including omics), and synthetic biology raises a number of issues for the philosophy of science. This article deals with several such: Is data -intensive biology a new kind of science, presumably post

Big data and the future of ecology
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the era of big data , and their successes clearly show that individual ecologists could achieve more if they changed their practices toward more open models of research and began treating data as a scientific product of enduring value. For example, in areas of biology that use [HTML]

From big data analysis to personalized medicine for all: challenges and opportunities
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Abstract Recent advances in high-throughput technologies have led to the emergence of systems biology as a holistic science to achieve more precise modeling of complex diseases This is mirrored by an increasing lag between our ability to generate and analyze big data

Big data bioinformatics
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maintained across distinct conditions. Machine learning methods can be applied to perform effective integrative analyses, which are expected to fulfill the promise of big data in biology . Big Data (sets). An enormous amount of

Lean Big Data integration in systems biology and systems pharmacology
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Data sets from recent large-scale projects can be integrated into one unified puzzle that can provide new insights into how drugs and genetic perturbations applied to human cells are linked to whole-organism phenotypes. Data that report how drugs affect the phenotype of

Big questions for social media big data : Representativeness, validity and other methodological pitfalls
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Consequently, Twitter has emerged as a model organism of big data . In biology , model organisms refer to species which have been selected for intensive examination by the re- search community in order to shed light on key biological processes such as fundamental

Cloud and heterogeneous computing solutions exist today for the emerging big data problems in biology
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Figure 1| Applying a MapReduce approach in the cloud to solve embarrassingly parallelizable problems. To traverse a 1 petabyte (PB) data set, Trelles et al. mistakenly assume that the 1 PB data set needs to be traversed by every node. The ideal MapReduce

Big data analytics in healthcare
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4.2. Reconstruction of Regulatory Networks. Pathway analysis approaches do not attempt to make sense of high-throughput big data in biology as arising from the integrated operation of a dynamical system [25]. There are multiple

Systems biology in the context of big data and networks
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Science is going through two rapidly changing phenomena: one is the increasing capabilities of the computers and software tools from terabytes to petabytes and beyond, and the other is the advancement in high-throughput molecular biology producing piles of

VFDB 2016: hierarchical and refined dataset for big data analysis 10 years on
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VFDB 2016: hierarchical and refined dataset for big data analysis 10 years on. Lihong Chen. MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology , Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100176

Making sense of big data
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Redundancy Control in Pathway Databases (ReCiPa): An Application for Improving Gene-Set Enrichment Analysis in Omics Studies and Big Data Biology . 29 July 2013 | OMICS: A Journal of Integrative Biology , Vol. 17, No

Why the current insistence on open access to scientific data Big data , knowledge production, and the political economy of contemporary biology
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The collection and dissemination of data on human and nonhuman organisms has become a central feature of 21st-century biology and has been endorsed by funding agencies in the United States and Europe as crucial to translating biological research into therapeutic and

Bioinformatics clouds for big data manipulation
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As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap- forward from in-house computing infrastructure into utility-supplied cloud computing

Biology must develop its own big – data systems
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The last week of April was designated Big Data Week. But in modern biology , every week is big – data week: life-sciences research now routinely churns out more information than scientists can analyse without help. That help increasingly comes in the form of expensive

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