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GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms

Autor: Yi-Wei Liu, Tz-Wei Hsu, Che-Yu Chang, Wen-Hung Liao, Jia-Ming Chang

Publikováno v: BMC Bioinformatics, Vol 21, Iss S6, Pp 1-16 (2020)

Abstract Background Biological data has grown explosively with the advance of next-generation sequencing. However, annotating protein function with wet lab experiments is time-consuming. Fortunately, computational function prediction can help wet lab

Externí odkaz: https://doaj.org/article/1d53b8a4268f4d1a938689a262ec16d4

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GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms

Autor: Che-Yu Chang, Yi-Wei Liu, Jia-Ming Chang, Wen-Hung Liao, Tz-Wei Hsu

Publikováno v: BMC Bioinformatics
BMC Bioinformatics, Vol 21, Iss S6, Pp 1-16 (2020)

Background Biological data has grown explosively with the advance of next-generation sequencing. However, annotating protein function with wet lab experiments is time-consuming. Fortunately, computational function prediction can help wet labs formula

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0dd74e0dfbd7da42357fa2e1631dc3f
https://pubmed.ncbi.nlm.nih.gov/33203348

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PSLCNN: Protein Subcellular Localization Prediction for Eukaryotes and Prokaryotes Using Deep Learning

Autor: Che-Yu Chang, Tz-Wei Hsu, Jia-Ming Chang

Publikováno v: TAAI

Many machine learning methods have been used to predict prokaryotic and eukaryotic protein subcellular localization. As most algorithms involve specific feature engineering, we carry out prediction using the feature-free property of deep learning met

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::99cf9d8002b66de7c6a1fc1b1a4254c1
https://doi.org/10.1109/taai48200.2019.8959851

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