From artificial intelligence to pluripotent stem cells, this year saw the publication of a bevy of intriguing new methods, as well as tweaks to existing protocols.

Scientists used machine learning to analyze the coevolution of physical traits in butterflies.

The proof-of-concept study could be a step toward better assisted communication devices for paralyzed people.

One recent case, in which a scientist claims his submitted manuscript was rejected despite a lack of actual plagiarism, highlights the limitations of automated tools.

Microbiologist Nick Loman talks about the power of artificial intelligence and the best way to use it.

As artificial life forms become more sophisticated, we propose a simple list of criteria to determine whether synthetic biological organisms and robots are living beings.

Machine learning can analyze photographs of cancer, tumor pathology slides, and genomes. Now, scientists are poised to integrate that information into cancer uber-models.

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

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