Shafaq Zia is a science journalist and a graduate student in the Graduate Program in Science Writing at the Massachusetts Institute of Technology. Previously, she was a reporting intern at STAT, covering the COVID-19 pandemic and the latest research in health technology.
Shafaq Zia
From this contributor
Spotted around the web: COVID-19 during pregnancy, sleep problems, eugenics
Here is a roundup of news and research for the week of 6 June.
Spotted around the web: COVID-19 during pregnancy, sleep problems, eugenics
By
Jill Adams, Angie Voyles Askham, Peter Hess, Shafaq Zia
10 June 2022 | 3 min read
New resource tracks genetic variations in Han Chinese populations
An online database called NyuWa catalogs genetic variations among nearly 3,000 individuals and provides a comprehensive reference genome for the Han people.
New resource tracks genetic variations in Han Chinese populations
By
Shafaq Zia
9 December 2021 | 3 min read
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The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
By
Marc Coutanche
13 November 2026 | 6 min read
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
By
Claudia López Lloreda
12 November 2026 | 1 min watch
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
By
Giorgia Guglielmi
12 November 2026 | 4 min read