Posts Tagged ‘from’
From target discovery to clinical drug development with human genetics | Nature
May 18, 2025https://www.nature.com/articles/s41586-023-06388-8
Trajanoska, K., Bhérer, C., Taliun, D., Zhou, S., Richards, J. B., & Mooser, V. (2023). From target discovery to clinical drug development with human genetics. Nature, 620(7975), 737–745.
https://doi.org/10.1038/s41586-023-06388-8
Human genetics evidence supports two-thirds of the 2021 FDA-approved drugs
May 17, 2025https://www.nature.com/articles/d41573-022-00120-3
Ochoa, D., Karim, M., Ghoussaini, M., Hulcoop, D. G., McDonagh, E. M., & Dunham, I. (2022). Human genetics evidence supports two-thirds of the 2021 FDA-approved drugs. Nature Reviews Drug Discovery, 21(8), 551. https://doi.org/10.1038/d41573-022-00120-3
lecture note on mixed state and density matrix
May 11, 2025https://www.henryyuen.net/classes/spring2022/
https://www.henryyuen.net/spring2022/lec2-mixed-states.pdf
lecture notes on mixed states and density matrix.
QT:{{”
Frontiers of Quantum Complexity and Cryptography Lecture 2 – Mixed States and Density Matrices
Lecturer: Henry Yuen Spring 2022
Scribes: Melody Hsu
In the third lecture, we wrapped up a review of the foundational concepts we will need to tackle
later topics, and then started our first quantum complexity topic, state tomography. We briefly
discussed several ways to analyze probabilistic mixtures of quantum states; after the conclusion of
the review, we explored lower bounds on complexity of a classic tomography protocol.
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gen ai book
April 20, 2025Generative Deep Learning: teaching machines to paint, write, compose, and play: Foster, David: 9781492041948: Amazon.com: Books. (n.d.). https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1492041947
World Model page 331
Variational Autoencoders page 59
How evolution builds genes from scratch
March 23, 2025https://www.nature.com/articles/d41586-019-03061-x
Levy, A. (2019). How evolution builds genes from scratch. Nature, 574(7778), 314–316. https://doi.org/10.1038/d41586-019-03061-x
How evolution builds genes from scratch
Scientists long assumed that new genes appear when evolution tinkers with old ones. It turns out that natural selection is much more creative.
2nd “MBB” dept at Yale
March 19, 2025Didn’t realize we are the 2nd “MBB” dept at Yale.
(See “admin” section in the below:
https://en.wikipedia.org/wiki/Joseph_S._Fruton
)
+
https://mbb.yale.edu/sites/default/files/files/A%20Scandalously%20Short%20History%20of%20MBB%20at%20Yale%20University(2).pdf
The Abstract: 8 Compounds That Target Aging
March 18, 2025Guarente, L., Sinclair, D. A., & Kroemer, G. (2024). Human trials exploring anti-aging medicines. Cell Metabolism, 36(2), 354–376. https://doi.org/10.1016/j.cmet.2023.12.007
https://www.cell.com/cell-metabolism/fulltext/S1550-4131(23)00458-8
QT:{{”
In a recent issue of Cell Metabolism, Guarente co-authored a review article about human trials exploring compounds that target pathways and mechanisms of aging along with David Sinclair, Ph.D., one of Dr. Guarente’s postdoctoral mentees and now a professor of genetics at Harvard Medical School, and Guido Kroemer, M.D., Ph.D., a professor at the Université Paris Cité. Guarente and his colleagues focus on eight drugs and compounds: metformin, NAD+ precursors, glucagon-like peptide-1 receptor agonists, TORC1 inhibitors, spermidine, senolytics, probiotics, and anti-inflammatories.
These interventions made the list for four reasons: 1) they’re well-represented in ongoing or completed human clinical trials; 2) they’ve been shown to slow aging in preclinical studies; 3) they’re thought to be sufficiently safe for long-term use in humans; and 4) they work by targeting the hallmarks of aging.
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