https://pmc.ncbi.nlm.nih.gov/articles/PMC478551/
Spruance, S. L., Reid, J. E., Grace, M., & Samore, M. (2004). Hazard ratio in clinical trials. Antimicrobial Agents and Chemotherapy, 48(8), 2787–2792. https://doi.org/10.1128/aac.48.8.2787-2792.2004
Archive for the 'SciLit' Category
Hazard Ratio in Clinical Trials – PMC
January 26, 2025Paper on human reads in microbiome data
January 25, 2025Interesting paper on how the incomplete human genome can cause privacy issues in analyzing metagenomic data.
https://www.nature.com/articles/s41467-025-56077-5
Genome-wide association studies | Nature Reviews Methods Primers
January 25, 2025g accounts for the cumulative effect of all other variants on the phenotype besides the effect of the specific variant being tested (SNP s).
Although theoretically we should consider the effect of g when testing for GWAS associations, in practice don’t think this happens in standard GWAS tools, such as PLINK and REGENIE (see below).
PLINK: https://www.cog-genomics.org/plink/2.0/assoc
REGENIE: https://www.nature.com/articles/s41588-021-00870-7#Sec10
https://www.nature.com/articles/s43586-021-00056-9
2312.07511 A Hitchhiker’s Guide to Geometric GNNs for 3D Atomic Systems
January 18, 2025https://arxiv.org/abs/2312.07511
Duval, A., Mathis, S., V., Joshi, C. K., Schmidt, V., Miret, S., Malliaros, F. D., Cohen, T., Liò, P., Bengio, Y., & Bronstein, M. (2023, December 12). A Hitchhiker’s guide to Geometric GNNs for 3D atomic Systems. arXiv.org. https://arxiv.org/abs/2312.07511
1803.00567 Computational Optimal Transport
January 18, 2025https://arxiv.org/abs/1803.00567
Peyré, G., & Cuturi, M. (2018, March 1). Computational Optimal transport. arXiv.org. https://arxiv.org/abs/1803.00567
tutorial_on_optimal_transport.pdf
Learning single-cell perturbation responses using neural optimal transport | Nature Methods
January 18, 2025https://www.nature.com/articles/s41592-023-01969-x
Bunne, C., Stark, S. G., Gut, G., Del Castillo, J. S., Levesque, M., Lehmann, K., Pelkmans, L., Krause, A., & Rätsch, G. (2023). Learning single-cell perturbation responses using neural optimal transport. Nature Methods, 20(11), 1759–1768.
https://doi.org/10.1038/s41592-023-01969-x
not so useful for learning OT
Accurate proteome-wide missense variant effect prediction with AlphaMissense | Science
December 31, 2024https://www.science.org/doi/10.1126/science.adg7492
Cheng, J., Novati, G., Pan, J., Bycroft, C., Žemgulytė, A., Applebaum, T., Pritzel, A., Wong, L. H., Zielinski, M., Sargeant, T., Schneider, R. G., W, A., Senior, Jumper, J., Hassabis, D., Kohli, P., & Avsec, Ž. (2023). Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science, 381(6664).
https://doi.org/10.1126/science.adg7492
Limits to economic growth | Nature Physics
December 24, 2024https://www.nature.com/articles/s41567-022-01652-6
Murphy, T. W. (2022). Limits to economic growth. Nature Physics, 18(8), 844–847. https://doi.org/10.1038/s41567-022-01652-6
The persistence of smoke VOCs indoors: Partitioning, surface cleaning, and air cleaning in a smoke-contaminated house | Science Advances
December 22, 2024https://www.science.org/doi/10.1126/sciadv.adh8263
QT:{{”
Many volatile organic compounds (VOCs) persisted days following the smoke injection, providing a longer-term exposure pathway for humans….These rates imply that vapor pressure controls partitioning behavior and that house ventilation plays a minor role in removing smoke VOCs. However, surface cleaning activities (vacuuming, mopping, and dusting) physically removed surface reservoirs and thus reduced indoor smoke VOC concentrations more effectively than portable air cleaners and more persistently than window opening.
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