Kate Yandell is a Philadelphia-based freelance writer with a love for genomics and neuroscience. She writes for Spectrum‘s Toolbox section.
Kate Yandell
Contributing Writer
Spectrum
From this contributor
With new part, CRISPR can cut RNA in living cells
A new version of the gene-editing tool CRISPR can target and cut RNA, offering a way to tinker with the expression of autism genes.
With new part, CRISPR can cut RNA in living cells
Sequencing approach bares large variety of brain cell types
Analyzing gene expression in a vision center of the mouse brain has revealed 49 different classes of cells.
Sequencing approach bares large variety of brain cell types
Precise program traces firing patterns in neural networks
By tracking calcium’s movement, a new algorithm simultaneously delineates individual neurons’ shapes as well as their firing patterns.
Precise program traces firing patterns in neural networks
Simple steps let star-shaped brain cells thrive in culture
A new method allows researchers to culture cells known as astrocytes from human brains.
Simple steps let star-shaped brain cells thrive in culture
Method marks variants among repeated DNA segments
A new tool trawls sequencing data to reveal single-letter DNA swaps within large duplications.
Method marks variants among repeated DNA segments
Explore more from The Transmitter
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.