An algorithm designed by researchers from Carnegie Mellon University's Computational Biology Department and St. Petersburg State University in Russia could help scientists identify unknown molecules. The algorithm, called MolDiscovery, uses mass spectrometry data from molecules to predict the identity of unknown substances, telling scientists early in their research whether they have stumbled on something new or merely rediscovered something already known. This development could save time and money in the search for new naturally occurring products that could be used in medicine.
Forsight to present clinical data of their blood-based MRD detection platform for DLBCL that detects relapse 200 days earlier than other methods.
Local rice varieties in Vietnam could be used to help breed improved crops with higher resilience to climate change, according to a new study published in Rice. Earlham Institute researchers are part of an international collaboration with genebanks and rice breeders in Vietnam -- championed by the International Rice Research Institute (IRRI) to help abolish world poverty and hunger -- are aiming to identify varieties that can survive an increasingly unpredictable climate.
Researchers at the Human Genome Sequencing Center at Baylor College of Medicine have identified genetic variant discrepancies between the hg19 and hg28 reference genomes, creating guidance for laboratories to take advantage of an improved human reference genome.
The human gut microbiome is a complex community of trillions of microbes that are constantly interacting with each other and our bodies. It supports our wellbeing, immune system and mental health -- but how is it sustained?
Honeybees bring back more than just nectar from their floral feasts and these microbes may help them survive turbulent times.
In future, it will be increasingly important to be able to predict the yields of individual varieties of cereals such as wheat as accurately as possible in a given environment. An international research team led by the IPK Leibniz Institute has compiled, processed and analyzed extensive data sets for this purpose. Ultimately, Big Data was able to double the prediction accuracy for yield.
UC San Diego School of Medicine researchers discovered gene expression patterns associated with pandemic viral infections, providing a map to help define patients' immune responses, measure disease severity, predict outcomes and test therapies -- for current and future pandemics.
Maritime litter is among the most urgent global pollution issues. Marine scientist Nikoleta Bellou and her team at Helmholtz-Zentrum Hereon have published an overview study of solutions for prevention, monitoring, and removal in the renowned scientifically journal Nature Sustainability. They found that reducing ocean pollution requires more support, integration, and creative political decisiveness.
An inter-university research group has succeeded in constructing the gene expression network behind the vascular development process in plants. They achieved this by performing bioinformatics analysis using the 'VISUAL' tissue culture platform, which generates vascular stem cells from leaf cells. In this network, they also discovered a new BES/BZR transcription factor, BEH3, and illuminated its role in vascular cell maintenance.