NDLI: Deep model-based feature extraction for predicting protein subcellular localizations from bio-images

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Frontiers of Computer Science in China : Volume 11

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Deep model-based feature extraction for predicting protein subcellular localizations from bio-images

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Deep model-based feature extraction for predicting protein subcellular localizations from bio-images

Content Provider	Springer Nature Link
Author	Shao, Wei Ding, Yi Shen, Hong Bin Zhang, Daoqiang
Copyright Year	2017
Abstract	Protein subcellular localization prediction is important for studying the function of proteins. Recently, as significant progress has been witnessed in the field of microscopic imaging, automatically determining the subcellular localization of proteins from bio-images is becoming a new research hotspot. One of the central themes in this field is to determine what features are suitable for describing the protein images. Existing feature extraction methods are usually hand-crafted designed, by which only one layer of features will be extracted, which may not be sufficient to represent the complex protein images. To this end, we propose a deep model based descriptor (DMD) to extract the high-level features from protein images. Specifically, in order to make the extracted features more generic, we firstly trained a convolution neural network (i.e., AlexNet) by using a natural image set with millions of labels, and then used the partial parameter transfer strategy to fine-tune the parameters from natural images to protein images. After that, we applied the Lasso model to select the most distinguishing features from the last fully connected layer of the CNN (Convolution Neural Network), and used these selected features for final classifications. Experimental results on a protein image dataset validate the efficacy of our method.
Starting Page	243
Ending Page	252
Page Count	10
File Format	PDF
ISSN	20952228
Journal	Frontiers of Computer Science in China
Volume Number	11
Issue Number	2
e-ISSN	20952236
Language	English
Publisher	Higher Education Press
Publisher Date	2017-03-02
Publisher Institution	Chinese Universities
Publisher Place	Beijing
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	partial parameter transfer subcellular location classification feature extraction deep model convolution neural network Computer Science
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computer Science

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