Linda Geddes is a Bristol-based freelance journalist writing about biology, medicine and technology. Born in Cambridge, she graduated from the University of Liverpool with a first-class degree in cell biology. She spent nine years as an editor and reporter for New Scientist magazine and has received numerous awards for her journalism, including winning the Association of British Science Writers’ award for best investigative journalism and being shortlisted for the Paul Foot Award. Her first book, Bumpology: The myth-busting pregnancy book for curious parents-to-be, was published in 2013.
Linda Geddes
From this contributor
How genetics is revealing rare childhood conditions
A pioneering project is showing how, 17 years since the first draft of the human genome, our genes are giving up their secrets and bringing hope to parents around the world.
How genetics is revealing rare childhood conditions
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Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.