Superzchen / iLearnLinks
iLearn, a Python Toolkit and Web Server Integrating the Functionality of Feature Calculation, Extraction, Clustering, Feature Selection, Feature Normalization, Dimension Reduction and Model Construction for Classification, Best Model Selection, Ensemble Learning and Result Visualization for DNA, RNA and Protein Sequences.
☆83Updated 3 years ago
Alternatives and similar repositories for iLearn
Users that are interested in iLearn are comparing it to the libraries listed below
Sorting:
- iFeature is a comprehensive Python-based toolkit for generating various numerical feature representation schemes from protein or peptide …☆192Updated 3 years ago
- A Python-based Effective Feature Generation Tool from DNA, RNA, and Protein Sequences☆97Updated 3 years ago
- Protein sequence classification with self-supervised pretraining☆82Updated 3 years ago
- iLearnPlus is the first machine-learning platform with both graphical- and web-based user interface that enables the construction of auto…☆113Updated last year
- Secondary structure prediction of long non-coding RNA: review and experimental comparison of existing approaches, L.A. Bugnon, A.A. Edera…☆18Updated last year
- [Nat. Commun.] Code for paper 'Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely …☆31Updated 3 years ago
- Multi-task and masked language model-based protein sequence embedding models.☆102Updated 4 years ago
- A deep learning framework for high-throughput mechanism-driven phenotype screening☆50Updated 4 years ago
- ☆47Updated 3 years ago
- Modelling the Language of Life - Deep Learning Protein Sequences☆73Updated 4 years ago
- ☆110Updated 3 years ago
- RNA Secondary Structure Prediction using an Ensemble of Two-dimensional Deep Neural Networks and Transfer Learning.☆105Updated 3 months ago
- Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier☆12Updated 5 years ago
- A repository for neural representational learning of RNA secondary structures☆32Updated 5 years ago
- Feature Extraction Package for Biological Sequences☆64Updated last month
- Deep-learning empowered prediction and generation of immunogenic epitopes for T cell immunity☆72Updated 2 years ago
- A structure-aware interpretable deep learning model for sequence-based prediction of protein-protein interactions☆102Updated 2 weeks ago
- Collecting AMP MIC data from different sources, then running a GAN to output promising sequences☆81Updated last year
- DeepTTC: a transformer-based model for predicting cancer drug response☆16Updated 2 years ago
- Interpretation by Deep Generative Masking for Biological Sequences☆37Updated 3 years ago
- ☆57Updated last year
- iFeatureOmega is a comprehensive platform for generating, analyzing and visualizing more than 170 representations for biological sequence…☆34Updated 2 years ago
- A software package for computing features of peptides and proteins☆63Updated last year
- A Python package for extracting protein sequence features☆59Updated 3 years ago
- ☆22Updated 2 years ago
- Protein function prediction using a variational autoencoder☆94Updated 7 years ago
- TEIM: TCR-Epitope Interaction Modeling☆51Updated 2 years ago
- ☆69Updated 4 months ago
- Neural networks for deep mutational scanning data☆69Updated 2 months ago
- Machine learning models for antibody sequences in PyTorch☆41Updated 4 years ago