In this most recent ASC study, researchers mapped the genes of 35,584 individuals, of whom 11,986 had autism, to determine how many times each gene is affected by variants with protein disrupting consequences.
Scientists at the Wellcome Sanger Institute, Simon Fraser University in Canada, and Imperial College London combined genomic data, models of bacterial evolution, and predictive modeling to identify how vaccines could be optimized for specific age groups, geographic regions, and different communities of bacteria.
LifeOmic and the Komen Tissue Bank will work together to deploy a Virtual Tissue Bank onto a secure, cloud-based platform to enable researchers around the world to query an extended data model including whole-genome sequencing data.
The authors write that “the MGRB provides a broadly applicable reference cohort for clinical genetics and genomic association studies, and for understanding the genetics of healthy aging.”
The newest collaboration parallels a similar program the two companies kicked off in April focused on developing therapeutics for colorectal cancer (CRC), which the companies said has already yielded several potential drug targets.
In a UC Davis study, researchers described methods by which someone could learn database genotypes by uploading multiple datasets. For example, a person who uploads approximately 900 genomes could recover at least one allele at SNP sites across up to 82% of the genome of a median person of European ancestries.
Taproot has announced an initial five Cornerstone Centers, including three NCI-designated Cancer Centers, that have agreed to work together to provide a high volume of regulatory-grade data to advance precision oncology care.
For the first time, a deep-learning approach has been used to predict disease-associated metal-relevant site mutations in metalloproteins, providing a new platform to tackle human diseases.
The researchers from the German Center for Neurodegenerative Diseases (DZNE) and the University of Bonn analyzed the gene activity of cells found in the blood, which could eventually support conventional diagnostics and accelerate the beginning of therapy.
Enhancements include upgrading the platform’s sponsor-reviewer interaction, adding support for multi-omics, and offering a library of analytical, statistical, and machine learning applications that are both accessible to reviewers and sufficiently powerful for bioinformaticians.