ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
ToxIBTL: prediction of peptide toxicity based on information bottleneck and transfer learning
Authors
Keywords
-
Journal
BIOINFORMATICS
Volume -, Issue -, Pages -
Publisher
Oxford University Press (OUP)
Online
2022-01-04
DOI
10.1093/bioinformatics/btac006
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Improved RNA Secondary Structure and Tertiary Base-pairing Prediction Using Evolutionary Profile, Mutational Coupling and Two-dimensional Transfer Learning
- (2021) Jaswinder Singh et al. BIOINFORMATICS
- Trends in peptide drug discovery
- (2021) Markus Muttenthaler et al. NATURE REVIEWS DRUG DISCOVERY
- RNA secondary structure prediction using deep learning with thermodynamic integration
- (2021) Kengo Sato et al. Nature Communications
- ATSE: a peptide toxicity predictor by exploiting structural and evolutionary information based on graph neural network and attention mechanism
- (2021) Lesong Wei et al. BRIEFINGS IN BIOINFORMATICS
- FEGS: a novel feature extraction model for protein sequences and its applications
- (2021) Zengchao Mu et al. BMC BIOINFORMATICS
- Network-based prediction of drug–target interactions using an arbitrary-order proximity embedded deep forest
- (2020) Xiangxiang Zeng et al. BIOINFORMATICS
- ToxDL: Deep learning using primary structure and domain embeddings for assessing protein toxicity
- (2020) Xiaoyong Pan et al. BIOINFORMATICS
- Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning
- (2020) Xiucai Ye et al. Cells
- A Comprehensive Survey on Transfer Learning
- (2020) Fuzhen Zhuang et al. PROCEEDINGS OF THE IEEE
- MotifCNN-fold: protein fold recognition based on fold-specific features extracted by motif-based convolutional neural networks
- (2019) Chen-Chen Li et al. BRIEFINGS IN BIOINFORMATICS
- DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks
- (2019) Bin Liu et al. BRIEFINGS IN BIOINFORMATICS
- DTI-CDF: a cascade deep forest model towards the prediction of drug-target interactions based on hybrid features
- (2019) Yanyi Chu et al. BRIEFINGS IN BIOINFORMATICS
- HMMER web server: 2018 update
- (2018) Simon C Potter et al. NUCLEIC ACIDS RESEARCH
- mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation
- (2018) Balachandran Manavalan et al. BIOINFORMATICS
- The Pfam protein families database in 2019
- (2018) Sara El-Gebali et al. NUCLEIC ACIDS RESEARCH
- Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools
- (2018) Ran Su et al. BRIEFINGS IN BIOINFORMATICS
- Functional classification of protein toxins as a basis for bioinformatic screening
- (2017) Surendra S. Negi et al. Scientific Reports
- Peptide therapeutics: current status and future directions
- (2015) Keld Fosgerau et al. DRUG DISCOVERY TODAY
- 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
- InterProScan 5: genome-scale protein function classification
- (2014) P. Jones et al. BIOINFORMATICS
- In Silico Approach for Predicting Toxicity of Peptides and Proteins
- (2013) Sudheer Gupta et al. PLoS One
- The Future of Peptide-based Drugs
- (2012) David J. Craik et al. Chemical Biology & Drug Design
- Extraordinary metabolic stability of peptides containing α-aminoxy acids
- (2011) Fei Chen et al. AMINO ACIDS
- Chemical Modifications Designed to Improve Peptide Stability: Incorporation of Non-Natural Amino Acids, Pseudo-Peptide Bonds, and Cyclization
- (2010) Luca Gentilucci et al. CURRENT PHARMACEUTICAL DESIGN
- ClanTox: a classifier of short animal toxins
- (2009) G. Naamati et al. NUCLEIC ACIDS RESEARCH
- Predicting linear B‐cell epitopes using string kernels
- (2008) Yasser EL‐Manzalawy et al. JOURNAL OF MOLECULAR RECOGNITION
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search