R3P-Loc: a compact multi-label predictor using ridge regression and random projection for protein subcellular localization

DOI10.1016/j.jtbi.2014.06.031zbMath1343.92177OpenAlexW2043831725WikidataQ38475141 ScholiaQ38475141MaRDI QIDQ739656

Sun-Yuan Kung, Man-Wai Mak, Shibiao Wan

Publication date: 19 August 2016

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2014.06.031

zbMATH Keywords

multi-label classificationcompact databasesmulti-location proteins

Mathematics Subject Classification ID

Taxonomy, cladistics, statistics in mathematical biology (92B10) Biochemistry, molecular biology (92C40)

Related Items (4)

Jointly evolving and compressing fuzzy system for feature reduction and classification ⋮ Efficient extreme learning machine via very sparse random projection ⋮ mLASSO-Hum: a LASSO-based interpretable human-protein subcellular localization predictor ⋮ R3P-Loc

Uses Software

• iSS-PseDNC
• iCTX-Type
• iMethyl-PseAAC
• GOASVM
• iSNO-PseAAC
• EpiLoc
• iEzy-drug
• Signal-CF

Cites Work

• Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning
• On label dependence and loss minimization in multi-label classification
• The Johnson-Lindenstrauss lemma and the sphericity of some graphs
• Database-friendly random projections: Johnson-Lindenstrauss with binary coins.
• A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction
• Some remarks on protein attribute prediction and pseudo amino acid composition
• Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
• Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition
• \textbf{iLoc-Virus}: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites
• GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition
• iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints
• Extensions of Lipschitz mappings into a Hilbert space
• Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
• Ridge Regression in Practice

This page was built for publication: R3P-Loc: a compact multi-label predictor using ridge regression and random projection for protein subcellular localization