Ensemble of Multiple Classifiers for Multilabel Classification of Plant Protein Subcellular Localization

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

(2020) Davide Chicco et al.   BMC GENOMICS

Subcellular location prediction of apoptosis proteins using two novel feature extraction methods based on evolutionary information and LDA

(2020) Lei Du et al.   BMC BIOINFORMATICS

Membrane Trafficking and Subcellular Drug Targeting Pathways

(2020) Ajay Kumar et al.   Frontiers in Pharmacology

Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences

(2020) Kenichiro Imai et al.   Frontiers in Genetics

Bird Eye View of Protein Subcellular Localization Prediction

(2020) Ravindra Kumar et al.   Life-Basel

SignalP 5.0 improves signal peptide predictions using deep neural networks

(2019) José Juan Almagro Armenteros et al.   NATURE BIOTECHNOLOGY

Prediction of Protein Subcellular Localization Based on Fusion of Multi-view Features

(2019) Bo Li et al.   MOLECULES

MIC_Locator: a novel image-based protein subcellular location multi-label prediction model based on multi-scale monogenic signal representation and intensity encoding strategy

(2019) Fan Yang et al.   BMC BIOINFORMATICS

Plant-mSubP: a computational framework for the prediction of single and multi-target protein subcellular localization using integrated machine-learning approaches

(2019) Sitanshu S Sahu et al.   AoB Plants

PSO-LocBact: A Consensus Method for Optimizing Multiple Classifier Results for Predicting the Subcellular Localization of Bacterial Proteins

(2019) Supatcha Lertampaiporn et al.   Biomed Research International

Protein sequence information extraction and subcellular localization prediction with gapped k-Mer method

(2019) Yu-hua Yao et al.   BMC BIOINFORMATICS

pLoc-mEuk: Predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC

(2018) Xiang Cheng et al.   GENOMICS

Prediction of human protein subcellular localization using deep learning

(2018) Leyi Wei et al.   JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING

Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC

(2018) Shengli Zhang et al.   JOURNAL OF THEORETICAL BIOLOGY

BUSCA: an integrative web server to predict subcellular localization of proteins

(2018) Castrense Savojardo et al.   NUCLEIC ACIDS RESEARCH

Proteome-wide prediction and annotation of mitochondrial and sub-mitochondrial proteins by incorporating domain information

(2017) Ravindra Kumar et al.   MITOCHONDRION

Predicting human protein subcellular localization by heterogeneous and comprehensive approaches

(2017) Chi-Hua Tung et al.   PLoS One

Prediction of endoplasmic reticulum resident proteins using fragmented amino acid composition and support vector machine

(2017) Ravindra Kumar et al.   PeerJ

LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell

(2017) Jana Sperschneider et al.   Scientific Reports

UniProt: the universal protein knowledgebase

(2016)   NUCLEIC ACIDS RESEARCH

protr/ProtrWeb: R package and web server for generating various numerical representation schemes of protein sequences

(2015) Nan Xiao et al.   BIOINFORMATICS

Predicting the Functional Types of Singleplex and Multiplex Eukaryotic Membrane Proteins via Different Models of Chou’s Pseudo Amino Acid Compositions

(2015) Hong-Liang Zou et al.   JOURNAL OF MEMBRANE BIOLOGY

Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences

(2015) Bin Liu et al.   NUCLEIC ACIDS RESEARCH

LocTree3 prediction of localization

(2014) Tatyana Goldberg et al.   NUCLEIC ACIDS RESEARCH

HybridGO-Loc: Mining Hybrid Features on Gene Ontology for Predicting Subcellular Localization of Multi-Location Proteins

(2014) Shibiao Wan et al.   PLoS One

Assessing identity, redundancy and confounds in Gene Ontology annotations over time

(2013) Jesse Gillis et al.   BIOINFORMATICS

Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets

(2013) Gerard JP van Westen et al.   Journal of Cheminformatics

SCLpredT: Ab initio and homology-based prediction of subcellular localization by N-to-1 neural networks

(2013) Alessandro Adelfio et al.   SpringerPlus

WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms

(2012) S.-M. Chi et al.   BIOINFORMATICS

Prediction of nuclear proteins using nuclear translocation signals proposed by probabilistic latent semantic indexing

(2012) Emily Su et al.   BMC BIOINFORMATICS

mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machines

(2012) Shibiao Wan et al.   BMC BIOINFORMATICS

iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites

(2011) Zhi-Cheng Wu et al.   Molecular BioSystems

Some remarks on protein attribute prediction and pseudo amino acid composition

(2010) Kuo-Chen Chou   JOURNAL OF THEORETICAL BIOLOGY

YLoc—an interpretable web server for predicting subcellular localization

(2010) Sebastian Briesemeister et al.   NUCLEIC ACIDS RESEARCH

Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization

(2010) Kuo-Chen Chou et al.   PLoS One

A New Method for Predicting the Subcellular Localization of Eukaryotic Proteins with Both Single and Multiple Sites: Euk-mPLoc 2.0

(2010) Kuo-Chen Chou et al.   PLoS One

Prediction of subcellular locations of proteins: Where to proceed?

(2010) Kenichiro Imai et al.   PROTEOMICS

ST-scale as a novel amino acid descriptor and its application in QSAM of peptides and analogues

(2009) Li Yang et al.   AMINO ACIDS

A method to improve protein subcellular localization prediction by integrating various biological data sources

(2009) Thai Tung et al.   BMC BIOINFORMATICS

MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

(2009) Torsten Blum et al.   BMC BIOINFORMATICS

NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

(2009) Alex N Nguyen Ba et al.   BMC BIOINFORMATICS

Subcellular targeting strategies for drug design and delivery

(2009) Lawrence Rajendran et al.   NATURE REVIEWS DRUG DISCOVERY

The GOA database in 2009--an integrated Gene Ontology Annotation resource

(2008) D. Barrell et al.   NUCLEIC ACIDS RESEARCH