Evan Eichler
Professor of Genome Sciences
University of Washington
From this contributor
Autism and the complete human genome: Q&A with Evan Eichler
Scientists have at last filled in the missing gaps — an advance likely to inform every aspect of autism genetics research, Eichler says.
Autism and the complete human genome: Q&A with Evan Eichler
Remembering Steve Warren (1953-2021): A giant in the field of genetics
Steve Warren co-discovered the genetic mechanism that underpins fragile X syndrome and was a generous, inspiring mentor to many.
Remembering Steve Warren (1953-2021): A giant in the field of genetics
Questions for Evan Eichler: An evolving theory of autism
A gene that raises the risk of autism in some people may also give humans an evolutionary boost.
Questions for Evan Eichler: An evolving theory of autism
Explore more from The Transmitter
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.
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.
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.