https://arxiv.org/abs/1906.02691
Kingma, D. P., & Welling, M. (2019). An introduction to variational autoencoders. Foundations and Trends® in Machine Learning, 12(4), 307–392. https://doi.org/10.1561/2200000056
Archive for the 'SciLit' Category
1906.02691 An Introduction to Variational Autoencoders
February 18, 2025Conformational sampling and interpolation using language-based protein folding neural networks
February 7, 2025Principal component analysis | Nature Reviews Methods Primers
February 4, 2025https://www.nature.com/articles/s43586-022-00184-w
Greenacre, M., Groenen, P. J. F., Hastie, T., D’Enza, A. I., Markos, A., & Tuzhilina, E. (2022). Principal component analysis. Nature Reviews Methods Primers, 2(1).
https://doi.org/10.1038/s43586-022-00184-w
Network Analysis as a Grand Unifier in Biomedical Data Science | Annual Reviews
February 4, 2025https://www.annualreviews.org/content/journals/10.1146/annurev-biodatasci-080917-013444
McGillivray, P., Clarke, D., Meyerson, W., Zhang, J., Lee, D., Gu, M., Kumar, S., Zhou, H., & Gerstein, M. (2018). Network analysis as a grand unifier in biomedical data science. Annual Review of Biomedical Data Science, 1(1), 153–180.
https://doi.org/10.1146/annurev-biodatasci-080917-013444
Hazard Ratio in Clinical Trials – PMC
January 26, 2025https://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
Paper 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
linkstream2 microblog 