Machine learning for biologics: opportunities for protein engineering, developability, and formulation
Successful biologics must satisfy multiple properties including activity and particular
physicochemical features that are globally defined as developability. These multiple …
physicochemical features that are globally defined as developability. These multiple …
Antibody display technologies: selecting the cream of the crop
B Valldorf, SC Hinz, G Russo, L Pekar, L Mohr… - Biological …, 2022 - degruyter.com
Antibody display technologies enable the successful isolation of antigen-specific antibodies
with therapeutic potential. The key feature that facilitates the selection of an antibody with …
with therapeutic potential. The key feature that facilitates the selection of an antibody with …
Logomaker: beautiful sequence logos in Python
Sequence logos are visually compelling ways of illustrating the biological properties of DNA,
RNA and protein sequences, yet it is currently difficult to generate and customize such logos …
RNA and protein sequences, yet it is currently difficult to generate and customize such logos …
Antibody design using LSTM based deep generative model from phage display library for affinity maturation
K Saka, T Kakuzaki, S Metsugi, D Kashiwagi… - Scientific reports, 2021 - nature.com
Molecular evolution is an important step in the development of therapeutic antibodies.
However, the current method of affinity maturation is overly costly and labor-intensive …
However, the current method of affinity maturation is overly costly and labor-intensive …
Deep dive into machine learning models for protein engineering
Protein redesign and engineering has become an important task in pharmaceutical research
and development. Recent advances in technology have enabled efficient protein redesign …
and development. Recent advances in technology have enabled efficient protein redesign …
A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics
Therapeutic monoclonal antibodies and their derivatives are key components of clinical
pipelines in the global biopharmaceutical industry. The availability of large datasets of …
pipelines in the global biopharmaceutical industry. The availability of large datasets of …
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires
Adaptive immune receptor repertoires (AIRR) are key targets for biomedical research as
they record past and ongoing adaptive immune responses. The capacity of machine …
they record past and ongoing adaptive immune responses. The capacity of machine …
High-throughput screening, next generation sequencing and machine learning: advanced methods in enzyme engineering
Enzyme engineering is an important biotechnological process capable of generating
tailored biocatalysts for applications in industrial chemical conversion and biopharma …
tailored biocatalysts for applications in industrial chemical conversion and biopharma …
Directed evolution of aptamer discovery technologies
D Wu, CKL Gordon, JH Shin… - Accounts of Chemical …, 2022 - ACS Publications
Conspectus Although antibodies are a powerful tool for molecular biology and clinical
diagnostics, there are many emerging applications for which nucleic acid-based aptamers …
diagnostics, there are many emerging applications for which nucleic acid-based aptamers …