[HTML][HTML] The language of proteins: NLP, machine learning & protein sequences
Natural language processing (NLP) is a field of computer science concerned with automated
text and language analysis. In recent years, following a series of breakthroughs in deep and …
text and language analysis. In recent years, following a series of breakthroughs in deep and …
Protein sequence design with deep generative models
Protein engineering seeks to identify protein sequences with optimized properties. When
guided by machine learning, protein sequence generation methods can draw on prior …
guided by machine learning, protein sequence generation methods can draw on prior …
Large language models generate functional protein sequences across diverse families
Deep-learning language models have shown promise in various biotechnological
applications, including protein design and engineering. Here we describe ProGen, a …
applications, including protein design and engineering. Here we describe ProGen, a …
SignalP 6.0 predicts all five types of signal peptides using protein language models
Signal peptides (SPs) are short amino acid sequences that control protein secretion and
translocation in all living organisms. SPs can be predicted from sequence data, but existing …
translocation in all living organisms. SPs can be predicted from sequence data, but existing …
Advances in machine learning for directed evolution
Machine learning (ML) can expedite directed evolution by allowing researchers to move
expensive experimental screens in silico. Gathering sequence-function data for training ML …
expensive experimental screens in silico. Gathering sequence-function data for training ML …
Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs)
are tremendous, the design and discovery of new candidates remain a time and cost …
are tremendous, the design and discovery of new candidates remain a time and cost …
A roadmap for metagenomic enzyme discovery
SL Robinson, J Piel, S Sunagawa - Natural Product Reports, 2021 - pubs.rsc.org
Covering: up to 2021 Metagenomics has yielded massive amounts of sequencing data
offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While …
offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While …
Machine learning to navigate fitness landscapes for protein engineering
CR Freschlin, SA Fahlberg, PA Romero - Current opinion in biotechnology, 2022 - Elsevier
Machine learning (ML) is revolutionizing our ability to understand and predict the complex
relationships between protein sequence, structure, and function. Predictive sequence …
relationships between protein sequence, structure, and function. Predictive sequence …
Protein design via deep learning
Proteins with desired functions and properties are important in fields like nanotechnology
and biomedicine. De novo protein design enables the production of previously unseen …
and biomedicine. De novo protein design enables the production of previously unseen …
TULIP: A transformer-based unsupervised language model for interacting peptides and T cell receptors that generalizes to unseen epitopes
B Meynard-Piganeau, C Feinauer… - Proceedings of the …, 2024 - National Acad Sciences
The accurate prediction of binding between T cell receptors (TCR) and their cognate
epitopes is key to understanding the adaptive immune response and developing …
epitopes is key to understanding the adaptive immune response and developing …