HLAB: learning the BiLSTM features from the ProtBert-encoded proteins for the class I HLA-peptide binding prediction

Design of intelligent diabetes mellitus detection system using hybrid feature selection based XGBoost classifier

(2021) Anju Prabha et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

(2021) David R. Bell et al.   Journal of Chemical Information and Modeling

CNN-PepPred: an open-source tool to create convolutional NN models for the discovery of patterns in peptide sets—application to peptide–MHC class II binding prediction

(2021) Valentin Junet et al.   BIOINFORMATICS

BERT-Kcr: prediction of lysine crotonylation sites by a transfer learning method with pre-trained BERT models

(2021) Yanhua Qiao et al.   BIOINFORMATICS

GPS-Uber: a hybrid-learning framework for prediction of general and E3-specific lysine ubiquitination sites

(2021) Chenwei Wang et al.   BRIEFINGS IN BIOINFORMATICS

Artificial intelligence for quality control of oscillometry measures

(2021) Chiara Veneroni et al.   COMPUTERS IN BIOLOGY AND MEDICINE

DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites

(2020) Quanzhong Liu et al.   BRIEFINGS IN BIOINFORMATICS

Recommender Systems in Antiviral Drug Discovery

(2020) Ekaterina A. Sosnina et al.   ACS Omega

Anthem: a user customised tool for fast and accurate prediction of binding between peptides and HLA class I molecules

(2020) Shutao Mei et al.   BRIEFINGS IN BIOINFORMATICS

Application of decision tree-based ensemble learning in the classification of breast cancer

(2020) Mohammad M. Ghiasi et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Enhancing ontology-driven diagnostic reasoning with a symptom-dependency-aware Naïve Bayes classifier

(2019) Ying Shen et al.   BMC BIOINFORMATICS

MHCSeqNet: a deep neural network model for universal MHC binding prediction

(2019) Poomarin Phloyphisut et al.   BMC BIOINFORMATICS

DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity

(2019) Jingcheng Wu et al.   Frontiers in Immunology

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

(2018) Zhen Chen et al.   BIOINFORMATICS

An approach to EEG-based gender recognition using entropy measurement methods

(2018) Jianfeng Hu   KNOWLEDGE-BASED SYSTEMS

Clustering huge protein sequence sets in linear time

(2018) Martin Steinegger et al.   Nature Communications

Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity

(2017) Michal Bassani-Sternberg et al.   PLoS Computational Biology

Pan-Specific Prediction of Peptide–MHC Class I Complex Stability, a Correlate of T Cell Immunogenicity

(2016) Michael Rasmussen et al.   JOURNAL OF IMMUNOLOGY

Quantitative Prediction of Class I MHC/Epitope Binding Affinity Using QSAR Modeling Derived from Amino Acid Structural Information

(2015) Yuanqiang Wang et al.   COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

(2014) B. E. Suzek et al.   BIOINFORMATICS

Improving the prediction of HLA class I-binding peptides using a supertype-based method

(2014) Shufeng Wang et al.   JOURNAL OF IMMUNOLOGICAL METHODS

Mechanistic Peptidomics: Factors That Dictate Specificity in the Formation of Endogenous Peptides in Human Milk

(2014) Andres Guerrero et al.   MOLECULAR & CELLULAR PROTEOMICS

Pathways of Antigen Processing

(2013) Janice S. Blum et al.   Annual Review of Immunology

NetMHCcons: a consensus method for the major histocompatibility complex class I predictions

(2011) Edita Karosiene et al.   IMMUNOGENETICS