PurifyR: An R Package for Highly Automated, Reproducible Variable Extraction and Standardization-Reference-Cited by-同舟云学术

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PurifyR: An R Package for Highly Automated, Reproducible Variable Extraction and Standardization

Published:2020-01-01 Issue:1 Volume:3 Page:1-7
ISSN:2573-3370
Container-title:Systems Medicine
language:en
Short-container-title:Systems Medicine

Author:

Omta Wienand A.¹²³,van Heesbeen Roy G.⁴,Shen Ian²,Feelders Ad J.²,Brinkhuis M.J.S.²,Egan David A.³,Spruit Marco R.²

Affiliation:

1. Department of Cell Biology, Centre for Molecular Medicine, UMC Utrecht, Utrecht, The Netherlands.

2. Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands.

3. Core Life Analytics B.V., Utrecht, The Netherlands.

4. Department of Cell Biology, NKI-AVL, Amsterdam, The Netherlands.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/sysm.2019.0007

Reference32 articles.

1. Impact of high-throughput screening in biomedical research

2. High-throughput and ultra-high-throughput screening: solution- and cell-based approaches

3. Genetic risk factors in Parkinson’s disease

4. Survey statistics of automated segmentations applied to optical imaging of mammalian cells

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Self-Service Data Science for Adverse Event Prediction in Electronic Healthcare Records;Research and Innovation Forum 2020;2021

2. Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening;SLAS DISCOVERY: Advancing the Science of Drug Discovery;2020-05-13

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