Predicting the evolution of genetic mutations

Quantitative biologists David McCandlish and Juannan Zhou at Cold Spring Harbor Laboratory have developed an algorithm with predictive power, giving scientists the ability to see how specific genetic mutations can combine ...

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 ...

Predicting electricity demands

Research published in the International Journal of Energy Technology and Policy shows how a neural network can be trained with a genetic algorithm to forecasting short-term demands on electricity load. Chawalit Jeenanunta ...

Deep learning for electron microscopy

Finding defects in electron microscopy images takes months. Now, there's a faster way. It's called MENNDL, the Multinode Evolutionary Neural Networks for Deep Learning. It creates artificial neural networks—computational ...

Evolution is at work in computers as well as life sciences

Artificial intelligence research has a lot to learn from nature. My work links biology with computation every day, but recently the rest of the world was reminded of the connection: The 2018 Nobel Prize in Chemistry went ...

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