An Effective Multi-Label Protein Sub-Chloroplast Localization Prediction by Skipped-grams of Evolutionary Profiles using Deep Neural Network-Reference-Cited by-同舟云学术

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An Effective Multi-Label Protein Sub-Chloroplast Localization Prediction by Skipped-grams of Evolutionary Profiles using Deep Neural Network

Published:2020 Issue: Volume: Page:1-1
ISSN:1545-5963
Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
language:
Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Bankapur Sanjay,Patil Nagamma

Funder

Vision Group on Science and Technology Department of Information Technology Biotechnology and Science and Technology Govt. of Karnataka India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/8857/4359833/09257076.pdf?arnumber=9257076

Cited by 4 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. Exploiting feature multi-correlations for multilabel feature selection in robust multi-neighborhood fuzzy β covering space;Information Fusion;2024-04

2. An exhaustive review of computational prediction techniques for PPI sites, protein locations, and protein functions;Network Modeling Analysis in Health Informatics and Bioinformatics;2023-08-31

3. Prediction of protein subplastid localization and origin with PlastoGram;Scientific Reports;2023-05-24

4. The design of electronic medical records system using Skip-gram algorithm;Network Modeling Analysis in Health Informatics and Bioinformatics;2021-02-01

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