Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate

10.3390/ijms19010183

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Bibliographic Details
Main Authors:	Yu, C.Y, Li, X.X, Yang, H, Li, Y.H, Xue, W.W, Chen, Y.Z, Tao, L, Zhu, F
Other Authors:	PHARMACY
Format:	Review
Published:	2020
Subjects:	evaluation study machine learning procedures proteomics reproducibility sequence analysis software standards Machine Learning Proteomics Reproducibility of Results Sequence Analysis, Protein Software
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/182103
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-182103
record_format	dspace
spelling	sg-nus-scholar.10635-1821032024-04-05T09:03:11Z Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate Yu, C.Y Li, X.X Yang, H Li, Y.H Xue, W.W Chen, Y.Z Tao, L Zhu, F PHARMACY evaluation study machine learning procedures proteomics reproducibility sequence analysis software standards Machine Learning Proteomics Reproducibility of Results Sequence Analysis, Protein Software 10.3390/ijms19010183 International journal of molecular sciences 19 1 2020-10-30T02:11:33Z 2020-10-30T02:11:33Z 2018 Review Yu, C.Y, Li, X.X, Yang, H, Li, Y.H, Xue, W.W, Chen, Y.Z, Tao, L, Zhu, F (2018). Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate. International journal of molecular sciences 19 (1). ScholarBank@NUS Repository. https://doi.org/10.3390/ijms19010183 14220067 https://scholarbank.nus.edu.sg/handle/10635/182103 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Unpaywall 20201031
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	evaluation study machine learning procedures proteomics reproducibility sequence analysis software standards Machine Learning Proteomics Reproducibility of Results Sequence Analysis, Protein Software
spellingShingle	evaluation study machine learning procedures proteomics reproducibility sequence analysis software standards Machine Learning Proteomics Reproducibility of Results Sequence Analysis, Protein Software Yu, C.Y Li, X.X Yang, H Li, Y.H Xue, W.W Chen, Y.Z Tao, L Zhu, F Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
description	10.3390/ijms19010183
author2	PHARMACY
author_facet	PHARMACY Yu, C.Y Li, X.X Yang, H Li, Y.H Xue, W.W Chen, Y.Z Tao, L Zhu, F
format	Review
author	Yu, C.Y Li, X.X Yang, H Li, Y.H Xue, W.W Chen, Y.Z Tao, L Zhu, F
author_sort	Yu, C.Y
title	Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
title_short	Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
title_full	Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
title_fullStr	Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
title_full_unstemmed	Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate
title_sort	assessing the performances of protein function prediction algorithms from the perspectives of identification accuracy and false discovery rate
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/182103
_version_	1800914662408060928

Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate

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