AI Tackles Biology

Meet some of the people featured in the May 2019 issue of The Scientist.

Our brains have evolved to the point where we can build artificial brains that might help us understand our brains. Let that sink in.

Take a break from the bench to puzzle and peruse.

Algorithms for motion capture help neuroscientists dig into the question of how the brain produces behavior.

AI models can pick up subtle alterations in linguistic and vocal attributes of spoken language that may be indicative of failing health.

A high school student designs a new beehive and gets help from machine learning to monitor for varroa mite infestation.

Researchers are using artificial intelligence to pick out the features of brightfield microscopy images.

Artificially intelligent software has human-like ability to analyze host-pathogen interactions in microscopy images.

Machine learning could be the key to reducing the use of animals in experiments.

A brief history of AI, machine learning, artificial neural networks, and deep learning.

Machine learning algorithms predict the repairs made to DNA after Cas9 cuts.

Researchers are developing computational approaches to extract information from multiple sets of single-cell sequencing data.

The Carnegie Mellon computational biologist thinks machine learning algorithms can direct high-throughput experiments to solve the field’s unanswered questions.

The Yale University cognitive neuroscientist studies how the brain extracts patterns from experiences.

Researchers are using artificial intelligence to identify known and novel resistance genes.

The pharmaceutical industry is looking to machine learning to overcome complex challenges in drug development.

The author of a new book envisions a future when machines advance the research enterprise.

Marvin Minsky engineered the first known artificial neural network, in which “rats” represented as lights learned to solve a maze.

The latest machine learning models can identify many visual and molecular features of a particular cancer. If the technology advances to the clinic, it could help diagnose patients and predict survival.

Neuromorphic technology is fueling fast, large-scale simulations, supporting researchers’ endeavors to build models of the human brain.

Artificially intelligent software has human-like ability to analyze host-pathogen interactions in microscopy images.

Double-strand breaks can produce several different outcomes.