A deep learning model that can predict how human genes and medicines will interact has identified at least 10 compounds that may hold promise as treatments for COVID-19.
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Scientists have assembled a combination of data mining, machine-learning algorithms and compression-based analytics to bring the most useful data to the fore on an office computer.
Using machine learning, a team of Western computer scientists and biologists have identified an underlying genomic signature for 29 different COVID-19 DNA sequences.
A new study could help scientists mitigate the future spread of zoonotic and livestock diseases caused by existing viruses.
Researchers used an artificial intelligence (AI) algorithm to sift through terabytes of gene expression data to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu.
Progressive Mechanoporation makes it possible to mechanically disrupt the membranes of cells for a short time period and let drugs or genes inside cells.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days.
The Fraunhofer Institutes project M³Infekt aims to develop a multi-modal, modular and mobile system of sensors for monitoring infectious diseases.
The new device can continuously sense levels of virtually any protein or molecule in the blood. The researchers say it could be transformative for disease detection, patient monitoring and biomedical research.
An AI platform derives an optimal combination of available therapies against SARS-CoV-2 - the optimal drug therapy was a combination of the drugs remdesivir, ritonavir, and lopinavir at specific doses.
Researchers have examined how mobile technologies have been used in monitoring and mitigating the effects of the Covid-19 pandemic.
Scientists have demonstrated a VR technique which should help in developing drugs against the SARS-CoV-2 virus – and enable researchers to share models and collaborate in new ways.
Researchers have built a low-cost multiplex test that can rapidly provide three different types of data on COVID-19.
Researchers havee repurposed robotic technology normally used for synthetic biology research to help with testing for COVID-19.
Scientists are launching a project to apply machine learning methods to assess the role of climate variables in disease transmission