Cell‐penetrating peptides predictors: A comparative analysis of methods and datasets

Handcrafted versus non-handcrafted (self-supervised) features for the classification of antimicrobial peptides: complementary or redundant?

(2022) César R García-Jacas et al.   BRIEFINGS IN BIOINFORMATICS

Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data

(2022) Katarzyna Sidorczuk et al.   BRIEFINGS IN BIOINFORMATICS

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

(2021) Alexander Rives et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Accurate prediction of protein structures and interactions using a three-track neural network

(2021) Minkyung Baek et al.   SCIENCE

Deep learning improves antimicrobial peptide recognition

(2018) Daniel Veltri et al.   BIOINFORMATICS

Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy

(2018) Balachandran Manavalan et al.   JOURNAL OF PROTEOME RESEARCH

Systematic characterization of autophagy-related genes during the adipocyte differentiation using public-access data

(2018) Mahmoud Ahmed et al.   Oncotarget

KELM-CPPpred: Kernel Extreme Learning Machine Based Prediction Model for Cell-Penetrating Peptides

(2018) Poonam Pandey et al.   JOURNAL OF PROTEOME RESEARCH

CPPred-RF: A Sequence-based Predictor for Identifying Cell-Penetrating Peptides and Their Uptake Efficiency

(2017) Leyi Wei et al.   JOURNAL OF PROTEOME RESEARCH

MLACP: machine-learning-based prediction of anticancer peptides

(2017) Balachandran Manavalan et al.   Oncotarget

Effective Design of Multifunctional Peptides by Combining Compatible Functions

(2016) Christian Diener et al.   PLoS Computational Biology

Overlap and diversity in antimicrobial peptide databases: compiling a non-redundant set of sequences

(2015) Longendri Aguilera-Mendoza et al.   BIOINFORMATICS

Peptide therapeutics: Targeting the undruggable space

(2015) Natia Tsomaia   EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY

CPPsite 2.0: a repository of experimentally validated cell-penetrating peptides

(2015) Piyush Agrawal et al.   NUCLEIC ACIDS RESEARCH

CPPpred: prediction of cell penetrating peptides

(2013) Thérèse A. Holton et al.   BIOINFORMATICS

In silico approaches for designing highly effective cell penetrating peptides

(2013) Ankur Gautam et al.   Journal of Translational Medicine

CPPsite: a curated database of cell penetrating peptides

(2012) A. Gautam et al.   Database-The Journal of Biological Databases and Curation

Prediction of Cell Penetrating Peptides by Support Vector Machines

(2011) William S. Sanders et al.   PLoS Computational Biology

Prediction of Cell-Penetrating Peptides Using Artificial Neural Networks

(2010) Dimitar A. Dobchev et al.   Current Computer-Aided Drug Design

Synthetic therapeutic peptides: science and market

(2009) Patrick Vlieghe et al.   DRUG DISCOVERY TODAY

Applications of 2D Descriptors in Drug Design: A DRAGON Tale

(2008) Aliuska Helguera et al.   CURRENT TOPICS IN MEDICINAL CHEMISTRY

Predicting cell-penetrating peptides

(2007) Mats Hansen et al.   ADVANCED DRUG DELIVERY REVIEWS