TPpred-LE: therapeutic peptide function prediction based on label embedding

TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model

(2022) Ke Yan et al.   BIOINFORMATICS

PrMFTP: Multi-functional therapeutic peptides prediction based on multi-head self-attention mechanism and class weight optimization

(2022) Wenhui Yan et al.   PLoS Computational Biology

DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism

(2021) Duolin Wang et al.   NUCLEIC ACIDS RESEARCH

Learning embedding features based on multisense-scaled attention architecture to improve the predictive performance of anticancer peptides

(2021) Wenjia He et al.   BIOINFORMATICS

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

(2021) Wending Tang et al.   BRIEFINGS IN BIOINFORMATICS

A COVID-19 peptide vaccine for the induction of SARS-CoV-2 T cell immunity

(2021) Jonas S. Heitmann et al.   NATURE

Peptides-based therapeutics: Emerging potential therapeutic agents for COVID-19

(2021) Jagat Narayan Shah et al.   THERAPIE

The Emerging Trends of Multi-Label Learning

(2021) Weiwei Liu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

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

(2020) Davide Chicco et al.   BMC GENOMICS

Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening

(2020) Shaherin Basith et al.   MEDICINAL RESEARCH REVIEWS

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

(2020) Yu P Zhang et al.   BIOINFORMATICS

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach

(2020) Miyssa I. Abdelmageed et al.   Biomed Research International

AntiCP 2.0: an updated model for predicting anticancer peptides

(2020) Piyush Agrawal et al.   BRIEFINGS IN BIOINFORMATICS

Proteomic Screening for Prediction and Design of Antimicrobial Peptides with AmpGram

(2020) Michał Burdukiewicz et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides

(2020) Kaveh Kavousi et al.   Journal of Chemical Information and Modeling

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

(2019) Leyi Wei et al.   BIOINFORMATICS

DRAMP 2.0, an updated data repository of antimicrobial peptides

(2019) Xinyue Kang et al.   Scientific Data

Deep learning improves antimicrobial peptide recognition

(2018) Daniel Veltri et al.   BIOINFORMATICS

Therapeutic peptides: Historical perspectives, current development trends, and future directions

(2018) Jolene L. Lau et al.   BIOORGANIC & MEDICINAL CHEMISTRY

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

(2016) Weizhong Lin et al.   BIOINFORMATICS

Peptide therapeutics: current status and future directions

(2015) Keld Fosgerau et al.   DRUG DISCOVERY TODAY

Deep learning

(2015) Yann LeCun et al.   NATURE

SATPdb: a database of structurally annotated therapeutic peptides

(2015) Sandeep Singh et al.   NUCLEIC ACIDS RESEARCH

Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

(2015) Nuala A. O'Leary et al.   NUCLEIC ACIDS RESEARCH

A Review on Multi-Label Learning Algorithms

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

Predicting Antibacterial Peptides by the Concept of Chou's Pseudo-amino Acid Composition and Machine Learning Methods

(2013) Maede Khosravian et al.   PROTEIN AND PEPTIDE LETTERS

CD-HIT Suite: a web server for clustering and comparing biological sequences

(2010) Ying Huang et al.   BIOINFORMATICS