The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.
The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...
Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...
Researchers developed a machine learning model that predicts high-yield antibody-producing cell lines early in manufacturing, ...
The Register on MSN
Machine learning could yield faster, cheaper lithium-ion battery development
Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...
Abbreviations: Carbo or cis, carboplatin or cisplatin; Cyclo, cyclophosphamide; Doxo, doxorubicin; ER, estrogen receptor; Her (per), pertuzumab; Her (TRAS ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...
Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...
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