On 10 April, astrophysicists announced that they had captured the first ever image of a black hole. This was exhilarating news, but none of the giddy headlines mentioned that the image would have been impossible without open-source software. The image was created using Matplotlib, a Python library for graphing data, as well as other components of the open-source Python ecosystem. Just five days later, the US National Science Foundation (NSF) rejected a grant proposal to support that ecosystem, saying that the software lacked sufficient impact. It’s a familiar problem: open-source software is widely acknowledged as crucially important in science, yet it is funded non-sustainably.
Computerized genetic-design tools automate the process by which researchers design complex genetic circuits that can program cells — especially bacteria and yeast — to carry out specific actions, such as activating a particular enzyme or churning out a certain protein. Synthetic biologists have used single-celled organisms in this way to produce drugs, biological sensors that include cells or antibodies, enzymes for use in industry, and more.
Chalk up another win for computers. Software developed at the University of Rochester in New York has outstripped humans in its ability to identify emotions in speech. The researchers plan to use it to understand the effects of emotion in parent-child interactions.