Methylation
Recent articles
Unknown isoform adds twist to theory of fragile X origins
Contrary to conventional wisdom, most people with fragile X syndrome express the FMR1 gene — albeit improperly.
Unknown isoform adds twist to theory of fragile X origins
Contrary to conventional wisdom, most people with fragile X syndrome express the FMR1 gene — albeit improperly.
New gene-editing method flags fragile X mutation for repair
The approach prompts cultured cells to correct the genetic mutation in fragile X syndrome using their own DNA repair system, but it still needs to be tested further.
New gene-editing method flags fragile X mutation for repair
The approach prompts cultured cells to correct the genetic mutation in fragile X syndrome using their own DNA repair system, but it still needs to be tested further.
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Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.