Katharine Gammon is an award-winning independent science journalist based in Santa Monica, California. Her work has appeared in The New York Times, The Atlantic, WIRED, The Guardian, Undark, Popular Science, MIT Technology Review, Nature, Hakai and beyond.
Katharine Gammon
From this contributor
Spotted around the web: Mapping histones; COVID-19 births; acetaminophen lawsuits
Here is a roundup of news and research for the week of 31 October.
Spotted around the web: Mapping histones; COVID-19 births; acetaminophen lawsuits
A mix of common and rare variants shapes autism inheritance patterns
The study also reveals a link between language development and common variants.
A mix of common and rare variants shapes autism inheritance patterns
Zebrafish point to new gene involved in brain overgrowth, autism
The gene, YTHDF2, has not previously been linked to autism.
Zebrafish point to new gene involved in brain overgrowth, autism
Lags in genetic testing, variant reporting hinder autism research
Few autistic people undergo the recommended genetic testing for their condition, and test results often do not make their way into public databases, where researchers and clinicians can learn from them.
Lags in genetic testing, variant reporting hinder autism research
Explore more from The Transmitter
Leucovorin saga, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 June.
Leucovorin saga, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 June.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.