Machine learning-guided protein engineering
Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …
machine learning methods. These methods leverage existing experimental and simulation …
Incorporating machine learning into established bioinformatics frameworks
N Auslander, AB Gussow, EV Koonin - International journal of molecular …, 2021 - mdpi.com
The exponential growth of biomedical data in recent years has urged the application of
numerous machine learning techniques to address emerging problems in biology and …
numerous machine learning techniques to address emerging problems in biology and …
iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model
Tuberculosis (TB) is a worldwide illness caused by the bacteria Mycobacterium tuberculosis.
Owing to the high prevalence of multidrug-resistant tuberculosis, numerous traditional …
Owing to the high prevalence of multidrug-resistant tuberculosis, numerous traditional …
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 …
Amino acid encoding for deep learning applications
Background The number of applications of deep learning algorithms in bioinformatics is
increasing as they usually achieve superior performance over classical approaches …
increasing as they usually achieve superior performance over classical approaches …
[HTML][HTML] Protein representations: Encoding biological information for machine learning in biocatalysis
D Harding-Larsen, J Funk, NG Madsen… - Biotechnology …, 2024 - Elsevier
Enzymes offer a more environmentally friendly and low-impact solution to conventional
chemistry, but they often require additional engineering for their application in industrial …
chemistry, but they often require additional engineering for their application in industrial …
Applications of machine and deep learning in adaptive immunity
M Pertseva, B Gao, D Neumeier… - Annual Review of …, 2021 - annualreviews.org
Adaptive immunity is mediated by lymphocyte B and T cells, which respectively express a
vast and diverse repertoire of B cell and T cell receptors and, in conjunction with peptide …
vast and diverse repertoire of B cell and T cell receptors and, in conjunction with peptide …
Insight into the protein solubility driving forces with neural attention
Protein solubility is a key aspect for many biotechnological, biomedical and industrial
processes, such as the production of active proteins and antibodies. In addition …
processes, such as the production of active proteins and antibodies. In addition …
In silico prediction of in vitro protein liquid–liquid phase separation experiments outcomes with multi-head neural attention
Motivation Proteins able to undergo liquid–liquid phase separation (LLPS) in vivo and in
vitro are drawing a lot of interest, due to their functional relevance for cell life. Nevertheless …
vitro are drawing a lot of interest, due to their functional relevance for cell life. Nevertheless …
Current cancer driver variant predictors learn to recognize driver genes instead of functional variants
Background Identifying variants that drive tumor progression (driver variants) and
distinguishing these from variants that are a byproduct of the uncontrolled cell growth in …
distinguishing these from variants that are a byproduct of the uncontrolled cell growth in …