#bioinformatics

#bioinformatics

They set a new standard for analysing raw biological data including DNA, RNA and protein sequences from databases that can contain millions of billions of DNA letters, amounting to petabases' of information, more entries than all the webpages in Google's vast index. Although MetaGraph is tagged as Google for DNA', Chikhi likens the tool to a search engine for YouTube, because the tasks are more computationally demanding.

Researchers have launched a search engine that can quickly sift through the staggering volumes of biological data housed in public repositories. The team integrated data from seven publicly funded data archives, creating 18.8million unique DNA and RNA sequence sets and 210billion amino-acid sequence sets that users can search through using text prompts. The search engine, called MetaGraph, can also uncover genetic patterns hidden deep within expansive sequencing data sets without needing those patterns to be explicitly annotated in advance.

"It's a huge achievement," says Rayan Chikhi, a biocomputing researcher at the Pasteur Institute in Paris. "They set a new standard" for analysing raw biological data - including DNA, RNA and protein sequences - from databases that can contain millions of billions of DNA letters, amounting to 'petabases' of information, more entries than all the webpages in Google's vast index.

AI models like Evo and regLM can generate new sequences of mobile DNA and predict regulatory activity in human cell lines based on prompts.

The website took on a life of its own, showcasing the ongoing evolution and impact of the UCSC Genome Browser, vital for genomic research.