49 skills found · Page 1 of 2
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.
programmablebio / PepmlmTarget Sequence-Conditioned Generation of Peptide Binders via Masked Language Modeling
dosorio / PeptidesAn R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.
MSGFPlus / MsgfplusMS-GF+ (aka MSGF+ or MSGFPlus) performs peptide identification by scoring MS/MS spectra against peptides derived from a protein sequence database.
alexarnimueller / LSTM PeptidesLong short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.
alexarnimueller / ModlAMPPython package for peptide sequence generation, peptide descriptor calculation and sequence analysis.
novonordisk-research / PepfunnPython package for the analysis of natural and modified peptides using a set of modules to study their sequences
ShutaoChen97 / IIDL PepPIProgressive Transfer Learning for Peptide-Protein-Specific Interaction Profiling based on Interpretable Biological Sequence Pragmatic Analysis
wilhelm-lab / DlomixPython framework for Deep Learning in Proteomics
mnielLab / NetTCR 2.0NetTCR-2.0. Sequence-based prediction of peptide-TCR binding
ParisaH-Lab / CyclicMPNNA fine-tuned version of ProteinMPNN for generating stable cyclic peptide sequences
TRON-Bioinformatics / NeofoxAnnotation of mutated peptide sequences with published or novel potential neoantigen descriptors
pcpLiu / DeepSeqPanA sequence-based pan model for peptide-MHC I binding affinity prediction.
wilhelm-lab / PROSPECTProteomics Mass Spectrometry Datasets for Machine Learning
pcpLiu / DeepSeqPanIIA sequence-based pan model for peptide-MHC II binding affinity prediction.
plissonf / ML Guided Discovery And Design Of Non Hemolytic PeptidesClassification models for hemolytic nature and hemolytic activity predictions in peptide/protein sequences
williamdee1 / LMPred AMP PredictionA novel approach to the classification of antimicrobial peptides (AMPs) using pre-trained language models to create contextual vectorized embeddings of each peptide sequence before a convolutional neural network is used as the classifier.
brandonsie / EpitopefindrR package to BLAST peptide sequences against each other and identify the minimal overlap of aligning regions.
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.
tacular-omics / PeptacularA Python package for peptide sequence analysis built around ProForma 2.1 notation. Calculate masses, generate fragments, predict isotopic patterns, and more. Peptacular uses type annotations extensively, so it is type safe.
