New bioinformatics tool accurately tracks synthetic DNA
A team has demonstrated that their bioinformatics approach, PlasmidHawk, can analyse DNA sequences to identify the source of engineered plasmids.
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A team has demonstrated that their bioinformatics approach, PlasmidHawk, can analyse DNA sequences to identify the source of engineered plasmids.
Researchers have developed a new technique called mim-tRNAseq to measure, map and analyse tRNAs in cells, providing insight into disease.
Researchers have used computer simulations to model how the SARS-CoV-2 fusion peptide interacts with and penetrates the cell membrane.
With the right solution organisations can simplify their lab-based working, while ensuring the highest level of compliance with regulatory requirements.
Researchers have developed a computer modelling programme that can produce genetic circuits for cellular engineering.
A study has used artificial intelligence to reveal adeno-associated virus (AAV) capsid variants for use in gene therapies.
In this ebook, we’ll see how digitally enabling your organisation can increase capacity and improve vaccine production.
Researchers have developed a personalised medicine platform that could advance genomic medicine research for cancer.
In this whitepaper we explore some of the major bottlenecks in the development lifecycle and the current barriers to effective digital transformation.
Discover how workflows are being accelerated to speed up the vaccine research and development process while maintaining safety and immunogenicity.
In this article, Ramya Sriram describes how data science is driving innovations in medical biotechnology and genomics.
Computational drug screening has shown that chemotherapy drug pralatrexate could potentially be repurposed to treat COVID-19.
Dr Isaac Karimi and his team explain how compounds to treat COVID-19 could be found in Kurdish ethnomedicine, selecting some plants for computational drug discovery.
Scientists have created a drug discovery platform that enables the discovery and optimisation of RNA-targeting compounds.
Scientists have trained a computer algorithm to identify differences in cancer cell lines based on microscopic images, preventing the misclassification of cells.