https://www.genecards.org/cgi-bin/carddisp.pl?gene=NRGN
Aging related gene in capstone4
https://www.genecards.org/cgi-bin/carddisp.pl?gene=NRGN
Aging related gene in capstone4
https://www.nature.com/articles/s41586-021-03922-4
https://twitter.com/SEHanlon/status/1513548800949989377
At #AACR22, @VanAllenLab gives a nice overview of his paper using an interpretable NN model to get insights into determining cancer severity (https://nature.com/articles/s41586-021-03922-4)
Biologically informed deep neural network for prostate cancer discovery
Liked the way he hard-coded specific genes & pathways into the model & looked in detail where the model misclassified specific patients #AACR22 #AACR2022
Also, thought the hard-coding of genes into the model was similar to that in another interpretable AI approach (for brain disease, https://science.org/doi/10.1126/science.aat8464) Could have used the “rank projection trees” from this to highlight important genes #AACR22 #AACR2022
https://mailchi.mp/add7f814b67d/neurodevelopments-720229
https://www.libd.org/neurodevelopments/
the Lieber’s neuroDEVELOPMENTS newsletter, which features the PsychENCODE paper
WORKS IN PROGRESS – SPRING 2019
Decoding DNA
On the hunt for the genetic roots of mental illnesses
By Marcus Banks | March 4, 2019
QT:[[”
The model, a form of artificial intelligence, aims to use abstract knowledge gained in the research lab to improve clinical treatments for real patients. The ultimate goal, says Gerstein, is to use the model to develop pharmaceutical treatments that reduce the impact of schizophrenia. Part of the challenge in developing drugs to treat the disease is the fact that it is not a one-size-fits-all condition. “]]
seems to be better for eQTLs
https://www.nature.com/articles/s41588-018-0268-8
Cleaning up stuff from the psychENCODE rollout (my tag “pecrollout”)
* Some “liked” tweets (not exhaustive, mostly positive)
Private archives of the above :
http://meetings.gersteinlab.org/2018/12.23/Tweet-stuff-from-pecrollout-n-rsgdream18/
* Tagged articles
https://linkstream2.gerstein.info/tag/pecrollout/
* Papers
associated with the Gerstein Lab
http://papers.gersteinlab.org/subject/pecrollout
Science magazie collection
http://www.sciencemag.org/collections/psychencode?_ga=2.143857020.873191909.1545622068-923654032.1534125785
PEC website collection
http://www.psychencode.org/?page_id=227
* Yale pre-print site
http://info.gersteinlab.org/PEC_package_preprints
* Random private archived material
https://www.dropbox.com/home/01-NOT-TOP-LEVEL/ARCHIVE/random-archived-materials-from-pecrollout.x57k
•Click to ‘compose a new tweet’
•Right (R) upper hand corner see emoji icon
•Click on it = find all available emoji by scrolling
🧠
from
https://twitter.com/cmkhealthatwork/status/1073903636982444032