Machine learning improves COVID-19 drug repurposing efforts
A novel machine-learning technique leverages gene expression data to improve drug repurposing and can even predict interactions between drug candidates and targets based on incomplete data. The framework, which was described in Nature Machine Learning on February 1, was applied to drug repurposing for COVID-19 to generate potential lead compounds in line with clinical evidence. Read More
Acute SARS-CoV-2 infection elicits distinct antibody, T-cell responses
An analysis of antibody and T-cell responses during the entire timeline of SARS-CoV-2 infection reveals the different ways the immune system responds to the virus in the early phases of COVID-19 disease. The results, published in Cell Reports on January 21, suggest that T-cell responses may be important for controlling infection while antibodies provide longer protection. Read More
Protein biosensors show promise for SARS-CoV-2 testing
Scientists have developed biosensors to detect SARS-CoV-2 proteins and antibodies in simulated nasal fluids and human sera, according to a study published in Nature on January 27. The approach promises to be less costly and time-consuming than current COVID-19 testing methods. Read More
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