While glycans are crucial for biological processes, existing analysis modalities make it difficult for researchers with limited computational background to include these diverse carbohydrates into workflows. Here, we present glycowork, an open-source...
MOTIVATION: Monoclonal antibody (mAb) therapeutics are often produced from non-human sources (typically murine), and can therefore generate immunogenic responses in humans. Humanization procedures aim to produce antibody therapeutics that do not elic...
MOTIVATION: For immune system monitoring in large-scale studies at the single-cell resolution using CyTOF, (semi-)automated computational methods are applied for annotating live cells of mixed cell types. Here, we show that the live cell pool can be ...
Machine-learning-guided protein design is rapidly emerging as a strategy to find high-fitness multi-mutant variants. In this issue of Cell Systems, Wittman et al. analyze the impact of design decisions for machine-learning-assisted directed evolution...
The Journal of clinical investigation
Nov 15, 2021
Air pollution is a well-known contributor to asthma. Air toxics are hazardous air pollutants that cause or may cause serious health effects. Although individual air toxics have been associated with asthma, only a limited number of studies have specif...
The Journal of the American Academy of Orthopaedic Surgeons
Nov 15, 2021
OBJECTIVES: Accurately stratifying patients in the preoperative period according to mortality risk informs treatment considerations and guides adjustments to bundled reimbursements. We developed and compared three machine learning models to determine...
Advances in machine learning, computer vision and artificial intelligence methods, in combination with those in processing and cloud computing capability, portend the advent of true decision support during interventions in real-time and soon perhaps ...
A fundamental challenge at the interface of machine learning and neuroscience is to uncover computational principles that are shared between artificial and biological neural networks. In deep learning, normalization methods such as batch normalizatio...
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