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 ...

Why we need computational models in biology

Many researchers begin the scientific process by making observations of the natural world and collecting data. They then try to extract patterns from these observations and data using statistical analysis. However, defining ...

Supercomputing the evolution of a model flower

Scientists using supercomputers found genes sensitive to cold and drought in a plant help it survive climate change. These findings increase basic understanding of plant adaptation and can be applied to improve crops.

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