Identifying multi-functional bioactive peptide functions using multi-label deep learning

Application of multi-label classification models for the diagnosis of diabetic complications

(2021) Liang Zhou et al.   BMC Medical Informatics and Decision Making

PPTPP: A novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning

(2020) Yu P Zhang et al.   BIOINFORMATICS

iATC-FRAKEL: a simple multi-label web server for recognizing anatomical therapeutic chemical classes of drugs with their fingerprints only

(2020) Jian-Peng Zhou et al.   BIOINFORMATICS

AntiCP 2.0: an updated model for predicting anticancer peptides

(2020) Piyush Agrawal et al.   BRIEFINGS IN BIOINFORMATICS

Anti-cancer peptides: classification, mechanism of action, reconstruction and modification

(2020) Mingfeng Xie et al.   Open Biology

mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning

(2019) Zhenzhen Zou et al.   Frontiers in Genetics

PreAIP: Computational Prediction of Anti-inflammatory Peptides by Integrating Multiple Complementary Features

(2019) Mst. Shamima Khatun et al.   Frontiers in Genetics

PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning

(2019) Leyi Wei et al.   BIOINFORMATICS

AMAP: Hierarchical multi-label prediction of biologically active and antimicrobial peptides

(2019) Sadaf Gull et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification

(2019) Guoqiang Wu et al.   NEURAL NETWORKS

DeepSimulator: a deep simulator for Nanopore sequencing

(2018) Yu Li et al.   BIOINFORMATICS

iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences

(2018) Zhen Chen et al.   BIOINFORMATICS

OUP accepted manuscript

(2018)   NUCLEIC ACIDS RESEARCH

Cost-sensitive multi-label learning with positive and negative label pairwise correlations

(2018) Guoqiang Wu et al.   NEURAL NETWORKS

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation

(2018) Balachandran Manavalan et al.   BIOINFORMATICS

Prediction of anti-inflammatory proteins/peptides: an insilico approach

(2017) Sudheer Gupta et al.   Journal of Translational Medicine

iPTM-mLys: identifying multiple lysine PTM sites and their different types

(2016) Wang-Ren Qiu et al.   BIOINFORMATICS

Imbalanced multi-label learning for identifying antimicrobial peptides and their functional types

(2016) Weizhong Lin et al.   BIOINFORMATICS

Lift: Multi-Label Learning with Label-Specific Features

(2015) Min-Ling Zhang et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

CancerPPD: a database of anticancer peptides and proteins

(2014) Atul Tyagi et al.   NUCLEIC ACIDS RESEARCH

Potential therapeutic applications of multifunctional host-defense peptides from frog skin as anti-cancer, anti-viral, immunomodulatory, and anti-diabetic agents

(2014) J. Michael Conlon et al.   PEPTIDES

iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types

(2013) Xuan Xiao et al.   ANALYTICAL BIOCHEMISTRY

A Review on Multi-Label Learning Algorithms

(2013) Min-Ling Zhang et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

From antimicrobial to anticancer peptides. A review

(2013) Diana Gaspar et al.   Frontiers in Microbiology

CD-HIT: accelerated for clustering the next-generation sequencing data

(2012) Limin Fu et al.   BIOINFORMATICS

Classifier chains for multi-label classification

(2011) Jesse Read et al.   MACHINE LEARNING

Multilabel classification via calibrated label ranking

(2008) Johannes Fürnkranz et al.   MACHINE LEARNING