Public databases like the Gene Expression Omnibus (GEO) hold enormous amounts of gene expression data from past experiments—hundreds of thousands, in fact. But until recently, finding relevant data in these repositories was like searching for a needle in a haystack. That’s because most searches rely on keywords, and those keywords may not match the exact biology a researcher is studying, especially if the original data wasn’t labeled well.

Researchers from Washington University in St. Louis have developed a new tool called CORESH, a web-based search engine that takes a different approach. Instead of requiring users to search by keyword, CORESH lets them upload a list of genes—for example, the top genes activated in response to a drug or disease. Then, it searches through over 80,000 human and mouse gene expression datasets and finds those that show similar gene activity patterns.

This is especially helpful for scientists using RNA sequencing to discover gene signatures. If they find a group of genes that are particularly active in their samples, CORESH can help them find other experiments where the same genes are active. This can offer clues about what those genes are doing, suggest underlying mechanisms, or even point to potential therapeutic targets.

By making it easier to find related gene expression profiles, CORESH could speed up discoveries and reduce redundant research. It’s a great example of how data science is improving the way we use massive public data resources in biology.

Availability – CORESH is freely accessible at https://alserglab.wustl.edu/coresh/, requires no login, and is regularly updated with the latest GEO data.