Deep learning network used to model protein complexes
A new study has developed a deep learning approach that analyses protein interactions, which could improve the design of drugs in the future.
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A new study has developed a deep learning approach that analyses protein interactions, which could improve the design of drugs in the future.
Research suggests that over half of the total $5.2bn investment for artificial intelligence in pharma went to drug design applications in 2019, but overall investment is slowing.
The two organisations have entered into a two-year alliance to improve scientific exchange in the drug discovery industry.
Researchers have produced a mathematical framework enabling quick assessment of how different parameters control interactions between molecules with multiple binding sites.
Laboratory Information Management Systems (LIMS) is becoming increasingly important in GMP regulated environments in order to ensure data integrity and faster working practices.
Researchers have created an algorithm that locates and analyses DNA structures which are linked to the development of certain diseases.
A new discovery could lead to the development of a drug for untreatable strains of TB, which can target uptake of the very amino acid that enables the bacteria to spread within the body.
The ICR has revealed that during drug discovery, researchers should not use general search engines and vendor catalogue information to decide on their use of chemical probes.
Research has found that artificial intelligence in drug discovery will be worth $1,434 million by the end of 2024.
The CyBio FeliX pipetting system was used to perform all liquid handling steps of the library preparation workflow for personal genome analysis.
The imaging equipment, European XFEL, is said to mark a new age of protein movie-making and enables enzymes involved in disease to be observed in real-time.
A novel computational method has led to the discovery of genes whose alteration may contribute to cancer susceptibility and may lead to new therapeutic targets for cancers.
Researchers in Australia and the US have launched the first open-source database detailing genetic variants that impact human health and disease.
New software has been developed that can reveal the detailed RNA-binding properties of proteins, which is important for characterising the pathology of many diseases.
A machine-learning algorithm has been created that automates high-throughput screens of epigenetic medicines.