Directed evolution of proteins in sequence space with gradients
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Updated
Jun 26, 2024 - Jupyter Notebook
Directed evolution of proteins in sequence space with gradients
Inference code for PoET: A generative model of protein families as sequences-of-sequences
Interpretable genotype-phenotype landscape modeling
Fusion of protein sequence and structural information, using denoising pre-training network for protein engineering (zero-shot).
PyPEF – Pythonic Protein Engineering Framework
Automancer is a software application that enables researchers to design, automate, and manage their experiments.
A curated list of awesome protein design research, software and resources.
Protein language models-assisted optimization of a uracil-N-glycosylase variant enables programmable T-to-G and T-to-C base editing
A curated list of awesome Molecular Modeling And Drug Discovery 🔥
PyPEF – Pythonic Protein Engineering Framework
How to build a large dataset of enzyme variants to evaluate enzyme design algorithms
Code, data and notebooks for engineering enzymes with ultra-high throughput microfluidics. Please read our accompanying paper for details.
Nucleotide augmentation for machine learning-guided protein engineering (https://doi.org/10.1093/bioadv/vbac094, 2022)
Phage library sequence generator with degenerate basepairs.
De novo enzyme design of oxirane:NAD(P)H reductase enzyme
Developing classification models for DNA-Binding proteins through machine learning and large language models
Directed Evolution in Silico
Developing assembled functional classifications models via optimized machine learning algorithms
Exploring digital signal processing combined with physicochemical properties support by NLP techniques
Protein engineering with large language models
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