References

Author

Affiliation

University of Colorado
Anschutz School of Medicine

Published

June 1, 2024

Modified

June 2, 2026

Bourgon, Richard, Robert Gentleman, and Wolfgang Huber. 2010. “Independent Filtering Increases Detection Power for High-Throughput Experiments.” Proceedings of the National Academy of Sciences 107 (21): 9546–51. https://doi.org/10.1073/pnas.0914005107.

Brouwer-Visser, Jurriaan, Wei-Yi Cheng, Anna Bauer-Mehren, et al. 2018. “Regulatory T-Cell Genes Drive Altered Immune Microenvironment in Adult Solid Cancers and Allow for Immune Contextual Patient Subtyping.” Cancer Epidemiology, Biomarkers & Prevention 27 (1): 103–12. https://doi.org/10.1158/1055-9965.EPI-17-0461.

Buçinca, Zana, Maja Barbara Malaya, and Krzysztof Z. Gajos. 2021. “To Trust or to Think.” Proceedings of the ACM on Human-Computer Interaction 5 (CSCW1): 1–21. https://doi.org/10.1145/3449287.

Budzyń, Krzysztof, Marcin Romańczyk, Diana Kitala, et al. 2025. “Endoscopist Deskilling Risk After Exposure to Artificial Intelligence in Colonoscopy: A Multicentre, Observational Study.” The Lancet. Gastroenterology & Hepatology 10 (10): 896–903. https://doi.org/10.1016/s2468-1253(25)00133-5.

Buenrostro, Jason D, Paul G Giresi, Lisa C Zaba, Howard Y Chang, and William J Greenleaf. 2013. “Transposition of Native Chromatin for Fast and Sensitive Epigenomic Profiling of Open Chromatin, DNA-binding Proteins and Nucleosome Position.” Nature Methods 10 (12): 1213–18. https://doi.org/10.1038/nmeth.2688.

Buenrostro, Jason D, Beijing Wu, Howard Y Chang, and William J Greenleaf. 2015. “ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide.” Current Protocols in Molecular Biology / Edited by Frederick M. Ausubel ... [Et Al.] 109 (January): 21.29.1–9. https://doi.org/10.1002/0471142727.mb2129s109.

Center, Pew Research. 2016. “Lifelong Learning and Technology.” In Pew Research Center: Internet, Science & Tech. https://www.pewresearch.org/internet/2016/03/22/lifelong-learning-and-technology/.

Crawford, Gregory E, Sean Davis, Peter C Scacheri, et al. 2006. “DNase-chip: A High-Resolution Method to Identify DNase I Hypersensitive Sites Using Tiled Microarrays.” Nature Methods 3 (7): 503–9. http://www.ncbi.nlm.nih.gov/pubmed/16791207?dopt=AbstractPlus.

Crawford, Gregory E, Ingeborg E Holt, James Whittle, et al. 2006. “Genome-Wide Mapping of DNase Hypersensitive Sites Using Massively Parallel Signature Sequencing (MPSS).” Genome Research 16 (1): 123–31. http://www.ncbi.nlm.nih.gov/pubmed/16344561?dopt=AbstractPlus.

DeRisi, J. L., V. R. Iyer, and P. O. Brown. 1997. “Exploring the Metabolic and Genetic Control of Gene Expression on a Genomic Scale.” Science (New York, N.Y.) 278 (5338): 680–86. https://doi.org/10.1126/science.278.5338.680.

Goddard, Kate, Abdul Roudsari, and Jeremy C Wyatt. 2012. “Automation Bias: A Systematic Review of Frequency, Effect Mediators, and Mitigators.” Journal of the American Medical Informatics Association 19 (1): 121–27. https://doi.org/10.1136/amiajnl-2011-000089.

Greener, Joe G., Shaun M. Kandathil, Lewis Moffat, and David T. Jones. 2022. “A Guide to Machine Learning for Biologists.” Nature Reviews Molecular Cell Biology 23 (1): 40–55. https://doi.org/10.1038/s41580-021-00407-0.

Knowles, Malcolm S., Elwood F. Holton, and Richard A. Swanson. 2005. The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development. 6th ed. Elsevier.

Lawrence, Michael, Wolfgang Huber, Hervé Pagès, Patrick Aboyoun, Marc Carlson, Robert Gentleman, Martin T. Morgan, et al. 2013a. “Software for Computing and Annotating Genomic Ranges.” PLoS Computational Biology 9 (8): e1003118. https://doi.org/10.1371/journal.pcbi.1003118.

Lawrence, Michael, Wolfgang Huber, Hervé Pagès, Patrick Aboyoun, Marc Carlson, Robert Gentleman, Martin T Morgan, et al. 2013b. “Software for Computing and Annotating Genomic Ranges.” PLoS Computational Biology 9 (8): e1003118. https://doi.org/10.1371/journal.pcbi.1003118.

Lee, Hao-Ping (Hank), Advait Sarkar, Lev Tankelevitch, et al. 2025. “The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers.” Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, April 25, 1–22. https://doi.org/10.1145/3706598.3713778.

Libbrecht, Maxwell W., and William Stafford Noble. 2015. “Machine Learning Applications in Genetics and Genomics.” Nature Reviews Genetics 16 (6): 321–32. https://doi.org/10.1038/nrg3920.

Lun, Aaron T. L., Davis J. McCarthy, and John C. Marioni. 2016. “A Step-by-Step Workflow for Low-Level Analysis of Single-Cell RNA-Seq Data with Bioconductor.” F1000Res. 5: 2122. https://doi.org/10.12688/f1000research.9501.2.

McCarthy, Davis J., Kieran R. Campbell, Aaron T. L. Lun, and Quin F. Willis. 2017. “Scater: Pre-Processing, Quality Control, Normalisation and Visualisation of Single-Cell RNA-Seq Data in R.” Bioinformatics 33: 1179–86. https://doi.org/10.1093/bioinformatics/btw777.

Meskó, Bertalan, and Eric J. Topol. 2023. “The Imperative for Regulatory Oversight of Large Language Models (or Generative AI) in Healthcare.” Npj Digital Medicine 6 (1). https://doi.org/10.1038/s41746-023-00873-0.

Messeri, Lisa, and M. J. Crockett. 2024. “Artificial Intelligence and Illusions of Understanding in Scientific Research.” Nature 627 (8002): 49–58. https://doi.org/10.1038/s41586-024-07146-0.

Morgan, Martin, Herve Pages, V Obenchain, and N Hayden. 2016. “Rsamtools: Binary Alignment (BAM), FASTA, Variant Call (BCF), and Tabix File Import.” R Package Version 1 (0): 677–89.

Murdoch, Blake. 2021. “Privacy and Artificial Intelligence: Challenges for Protecting Health Information in a New Era.” BMC Medical Ethics 22 (1). https://doi.org/10.1186/s12910-021-00687-3.

Risso, Davide, and Michael Cole. 2024. scRNAseq: Collection of Public Single-Cell RNA-Seq Datasets. https://doi.org/10.18129/B9.bioc.scRNAseq.

Student. 1908. “The Probable Error of a Mean.” Biometrika 6 (1): 1–25. https://doi.org/10.2307/2331554.

Tsompana, Maria, and Michael J Buck. 2014. “Chromatin Accessibility: A Window into the Genome.” Epigenetics & Chromatin 7 (1): 33. https://doi.org/10.1186/1756-8935-7-33.

Wasserstein, Ronald L., and Nicole A. Lazar. 2016. “The ASA Statement on p -Values: Context, Process, and Purpose.” The American Statistician 70 (2): 129–33. https://doi.org/10.1080/00031305.2016.1154108.

Zeisel, Amit, Ana B. Muñoz-Manchado, Simone Codeluppi, et al. 2015. “Cell Types in the Mouse Cortex and Hippocampus Revealed by Single-Cell RNA-seq.” Science 347 (6226): 1138–42. https://doi.org/10.1126/science.aaa1934.