9 skills found
Superzchen / IFeatureiFeature is a comprehensive Python-based toolkit for generating various numerical feature representation schemes from protein or peptide sequences. iFeature is capable of calculating and extracting a wide spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. Furthermore, iFeature also integrates five kinds of frequently used feature clustering algorithms, four feature selection algorithms and three dimensionality reduction algorithms.
schumacherlab / STAPLERSTAPLER (Shared TCR And Peptide Language bidirectional Encoder Representations from transformers) is a language model that uses a joint TCRab-peptide input to predict TCRab-peptide specificity.
leonjessen / PepToolsPepTools - An Immunoinformatics (Immunological Bioinformatics) R-package for working with peptide data
Ruheng-W / PepBCLWe propose PepBCL, a novel BERT (Bidirectional Encoder Representation from Transformers)-based Contrastive Learning framework to predict the protein-Peptide binding residues based on protein sequences only.
RoniGurvich / PeptrieverBi-Encoder approach for large-scale protein-peptide binding search
spaenigs / PeptidereactorA tool for an in-depth comparison and benchmarking of peptide encodings.
ZhaoBioinformaticsLab / PlantSSPProtocolsIdentification and functional investigation of genome-encoded, small, secreted peptides in plants
BioGenies / CancerGramPredicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI.
YPZ858 / PPTPPCodes of A novel therapeutic peptide prediction method using physicochemical property encoding and feature representation learning
