To predict an epidemic, evolution can't be ignored

When scientists try to predict the spread of something across populations—anything from a coronavirus to misinformation—they use complex mathematical models to do so. Typically, they'll study the first few steps in which ...

New algorithm rapidly finds anomalies in gene expression data

Computational biologists at Carnegie Mellon University have devised an algorithm to rapidly sort through mountains of gene expression data to find unexpected phenomena that might merit further study. What's more, the algorithm ...

Neural network fills in data gaps for spatial analysis of chromosomes

Computational methods used to fill in missing pixels in low-quality images or video also can help scientists provide missing information for how DNA is organized in the cell, computational biologists at Carnegie Mellon University ...

Computational 'match game' identifies potential antibiotics

Computational biologists at Carnegie Mellon University have devised a software tool that can play a high-speed "Match Game" to identify bioactive molecules and the microbial genes that produce them so they can be evaluated ...

A smarter habitat for deep space exploration

In order to explore the moon or Mars, astronauts need smart habitats that will support life and remain operational when they are vacant. To advance the design of autonomous systems for space habitats, NASA is funding a multi-university ...

Cleaning our water with groundbreaking 'bioinspired' chemistry

The 20th and 21st centuries have seen an explosion in the use of synthetic chemicals worldwide, including pesticides, medications and household cleaners—many of which end up in our waterways. Even in small amounts these ...

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