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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2018
عنوان انگلیسی مقاله:
Intelligent and effective informatic deconvolution of “Big Data” and its future impact on the quantitative nature of neurodegenerative disease therapy
ترجمه فارسی عنوان مقاله:
هوش انعطاف پذیر و موثر اطلاعاتی "داده های بزرگ" و تأثیر آن بر ماهیت کمی در درمان بیماری های نورودنژراتیک
منبع:
Sciencedirect - Elsevier - Alzheimers & Dementia, Corrected proof: doi:10:1016/j:jalz:2018:01:014
نویسنده:
Stuart Maudsleya,b,*,1, Viswanath Devanarayanc,1, Bronwen Martina, Hugo Geertsd, on behalf of the Brain Health Modeling Initiative (BHMI)
چکیده انگلیسی:
Biomedical data sets are becoming increasingly larger and a plethora of high-dimensionality data
sets (“Big Data”) are now freely accessible for neurodegenerative diseases, such as Alzheimer’s
disease. It is thus important that new informatic analysis platforms are developed that allow the
organization and interrogation of Big Data resources into a rational and actionable mechanism for
advanced therapeutic development. This will entail the generation of systems and tools that allow
the cross-platform correlation between data sets of distinct types, for example, transcriptomic, pro
teomic, and metabolomic. Here, we provide a comprehensive overview of the latest strategies,
including latent semantic analytics, topological data investigation, and deep learning techniques
that will drive the future development of diagnostic and therapeutic applications for Alzheimer’s dis
ease. We contend that diverse informatic “Big Data” platforms should be synergistically designed
with more advanced chemical/drug and cellular/tissue-based phenotypic analytical predictive models
to assist in either de novo drug design or effective drug repurposing.
Keywords: Big data; Informatics; High-dimensionality; Alzheimer’s disease; Aging; Molecular signature; Transcriptomics; Metabolomics; Proteomics; Genomics
قیمت: رایگان
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