Shervine Amidi - Google Scholar

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	All	Since 2015
Citations	68	68
h-index	5	5
i10-index	3	3

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30

15

20172018201920204 7 27 30

Co-authors

Afshine AmidiGraduate Student, MITVerified email at mit.edu
Nikos ParagiosProfessor, CentraleSupelec (Ecole Centrale Paris) / Université Paris-Saclay / InriaVerified email at ecp.fr
Evangelia I. ZacharakiVVR Group, Electrical and Computer Engineering, University of Patras, GreeceVerified email at upatras.gr
Dr Dimitrios VlachakisAssistant Professor, Genetics Laboratory, Department of BiotechnologyVerified email at aua.gr

Shervine Amidi

Shervine Amidi

Graduate Student, Stanford University

Verified email at stanford.edu - Homepage

Machine Learning Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation A Amidi, S Amidi, D Vlachakis, V Megalooikonomou, N Paragios, ... PeerJ 6, e4750, 2018	29	2018
Automatic single-and multi-label enzymatic function prediction by machine learning S Amidi, A Amidi, D Vlachakis, N Paragios, EI Zacharaki PeerJ 5, e3095, 2017	14	2017
A machine learning methodology for enzyme functional classification combining structural and protein sequence descriptors A Amidi, S Amidi, D Vlachakis, N Paragios, EI Zacharaki International Conference on Bioinformatics and Biomedical Engineering, 728-738, 2016	14	2016
A detailed example of how to use data generators with Keras A Amidi, S Amidi Accessed: Mar 26, 2019, 2019	6	2019
Recurrent neural networks cheatsheet A Amidi, S Amidi Cited 28-03-2019. Available at: https://stanford. edu/% 7Eshervine/teaching …, 2019	5	2019

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