Compressing a dataset with specialized algorithms is typically done in the context of data storage, where compression tools can shrink data to save space on a hard drive. But a group of researchers at MIT has developed tools that compute directly on compressed genomic datasets by exploiting the fact that most sequenced genomes are very similar to previously sequenced genomes.

Led by MIT professor Bonnie Berger, the group has recently released tools called CaBlast and CaBlat, compressive versions of the widely used Blast and Blat alignment tools, respectively.

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Researchers test gene therapy targeting a different cancer protein in a new trial, the New York Times reports.

Pennsylvania State University researchers found that salivary microRNAs could predict which kids would have longer concussion symptoms, according to NPR.

The Associated Press reports Alex Azar, the new Department of Health and Human Services secretary nominee, made millions of dollars as a pharmaceutical executive.

In PNAS this week: immune profiling of breast cancer, transposable element patterns in rice, and more.