scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/bib/WangWLC19 |
P356 | DOI | 10.1093/BIB/BBX086 |
P932 | PMC publication ID | 6488939 |
P698 | PubMed publication ID | 28968677 |
P2093 | author name string | Xiaoming Wang | |
Carolyn Williams | |||
Zhen Hua Liu | |||
Joe Croghan | |||
P2860 | cites work | Big data: teaching must evolve to keep up with advances | Q59065944 |
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Genetic studies of body mass index yield new insights for obesity biology | Q22305005 | ||
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Big Data Application in Biomedical Research and Health Care: A Literature Review | Q26769605 | ||
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A Dimensional Bus model for integrating clinical and research data | Q28394891 | ||
Making sense of big data in health research: Towards an EU action plan | Q28597362 | ||
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Computers read the fossil record | Q40775406 | ||
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TensorFlow: Biology's Gateway to Deep Learning? | Q50516290 | ||
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The entity-relationship model---toward a unified view of data | Q54151498 | ||
Data science and prediction | Q55919439 | ||
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Translational research platforms integrating clinical and omics data: a review of publicly available solutions | Q28652234 | ||
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Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility | Q29417007 | ||
Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support | Q29547407 | ||
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The minimum information about a proteomics experiment (MIAPE) | Q29615391 | ||
A new initiative on precision medicine | Q29615654 | ||
Genetic screens in human cells using the CRISPR-Cas9 system | Q29617411 | ||
Inverted files for text search engines | Q30054512 | ||
Indicators for the Data Usage Index (DUI): an incentive for publishing primary biodiversity data through global information infrastructure | Q30282040 | ||
What is biomedical informatics? | Q30379894 | ||
ImmPort: disseminating data to the public for the future of immunology | Q30813520 | ||
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Efficient Execution Methods of Pivoting for Bulk Extraction of Entity-Attribute-Value-Modeled Data | Q30885429 | ||
How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems | Q30938588 | ||
From big data analysis to personalized medicine for all: challenges and opportunities | Q30976798 | ||
Privacy protection for clinical and genomic data. The use of privacy-enhancing techniques in medicine | Q30982141 | ||
Big Data Clinical Research: Validity, Ethics, and Regulation. | Q30986372 | ||
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The Common Data Elements for cancer research: remarks on functions and structure. | Q31082863 | ||
Mindtagger: A Demonstration of Data Labeling in Knowledge Base Construction | Q31090225 | ||
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Improving the value of clinical research through the use of Common Data Elements | Q31108589 | ||
Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences | Q31144431 | ||
Data extraction and ad hoc query of an entity-attribute-value database | Q31970070 | ||
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Common data element (CDE) management and deployment in clinical trials. | Q33196883 | ||
The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data | Q33535114 | ||
Extraction of standardized archetyped data from Electronic Health Record systems based on the Entity-Attribute-Value Model | Q33600693 | ||
STRIDE--An integrated standards-based translational research informatics platform | Q33626790 | ||
The National Institutes of Health's Biomedical Translational Research Information System (BTRIS): design, contents, functionality and experience to date | Q33632571 | ||
Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). | Q34399891 | ||
Defining the role of common variation in the genomic and biological architecture of adult human height | Q34441746 | ||
Text summarization in the biomedical domain: a systematic review of recent research | Q34663938 | ||
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ChIP-chip: considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments | Q35676599 | ||
National Database for Autism Research (NDAR): Big Data Opportunities for Health Services Research and Health Technology Assessment. | Q35800876 | ||
BigQ: a NoSQL based framework to handle genomic variants in i2b2. | Q35881016 | ||
Towards an Oncology Database (ONCOD) Using a Warehousing Approach. | Q36082936 | ||
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Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension | Q37324554 | ||
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Sharing and reporting the results of clinical trials | Q37403368 | ||
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Using Electronic Health Records for Population Health Research: A Review of Methods and Applications. | Q38669361 | ||
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Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas | Q38804228 | ||
Functional genetic screens for enhancer elements in the human genome using CRISPR-Cas9. | Q38805040 | ||
Automatically explaining machine learning prediction results: a demonstration on type 2 diabetes risk prediction | Q38836207 | ||
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P433 | issue | 1 | |
P921 | main subject | big data | Q858810 |
data management | Q1149776 | ||
research data management | Q30089794 | ||
P304 | page(s) | 156-167 | |
P577 | publication date | 2017-08-07 | |
P1433 | published in | Briefings in Bioinformatics | Q4967031 |
P1476 | title | Big data management challenges in health research-a literature review | |
P478 | volume | 20 |
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