A Novel Protein Subcellular Localization Method With CNN-XGBoost Model for Alzheimer's Disease
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Novel Protein Subcellular Localization Method With CNN-XGBoost Model for Alzheimer's Disease
Authors
Keywords
-
Journal
Frontiers in Genetics
Volume 9, Issue -, Pages -
Publisher
Frontiers Media SA
Online
2019-01-18
DOI
10.3389/fgene.2018.00751
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- DincRNA: a comprehensive web-based bioinformatics toolkit for exploring disease associations and ncRNA function
- (2018) Liang Cheng et al. BIOINFORMATICS
- Identifying diseases-related metabolites using random walk
- (2018) Yang Hu et al. BMC BIOINFORMATICS
- InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk
- (2018) Liang Cheng et al. BMC GENOMICS
- GAB2 rs2373115 variant contributes to Alzheimer's disease risk specifically in European population
- (2017) Yang Hu et al. JOURNAL OF THE NEUROLOGICAL SCIENCES
- Rs4878104 contributes to Alzheimer’s disease risk and regulates DAPK1 gene expression
- (2017) Yang Hu et al. NEUROLOGICAL SCIENCES
- Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision
- (2017) Yungang Xu et al. NUCLEIC ACIDS RESEARCH
- mGOF-loc: A novel ensemble learning method for human protein subcellular localization prediction
- (2016) Leyi Wei et al. NEUROCOMPUTING
- DisSim: an online system for exploring significant similar diseases and exhibiting potential therapeutic drugs
- (2016) Liang Cheng et al. Scientific Reports
- OAHG: an integrated resource for annotating human genes with multi-level ontologies
- (2016) Liang Cheng et al. Scientific Reports
- Implementation of Arithmetic Operations With Time-Free Spiking Neural P Systems
- (2015) Xiangrong Liu et al. IEEE TRANSACTIONS ON NANOBIOSCIENCE
- mLASSO-Hum: A LASSO-based interpretable human-protein subcellular localization predictor
- (2015) Shibiao Wan et al. JOURNAL OF THEORETICAL BIOLOGY
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Adaptive Linear and Normalized Combination of Radial Basis Function Networks for Function Approximation and Regression
- (2014) Yunfeng Wu et al. MATHEMATICAL PROBLEMS IN ENGINEERING
- Spiking Neural P Systems with Thresholds
- (2014) Xiangxiang Zeng et al. NEURAL COMPUTATION
- Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion
- (2013) Suxian Cai et al. Computational and Mathematical Methods in Medicine
- WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms
- (2012) S.-M. Chi et al. BIOINFORMATICS
- Combining least-squares support vector machines for classification of biomedical signals: a case study with knee-joint vibroarthrographic signals
- (2011) Yunfeng Wu et al. JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
- iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites
- (2011) Kuo-Chen Chou et al. Molecular BioSystems
- YLoc—an interpretable web server for predicting subcellular localization
- (2010) Sebastian Briesemeister et al. NUCLEIC ACIDS RESEARCH
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation