Zobrazeno 1 - 10
of 493
pro vyhledávání: '"Bourne, P. E."'
Autor:
Johnson, Terence R., Bourne, Philip E.
Biological data in digital form has become a, if not the, driving force behind innovations in biology, medicine, and the environment. No study and no model would be complete without access to digital data (including text) collected by others and avai
Externí odkaz:
http://arxiv.org/abs/2311.05668
We propose a fold change visualization that demonstrates a combination of properties from log and linear plots of fold change. A useful fold change visualization can exhibit: (1) readability, where fold change values are recoverable from datapoint po
Externí odkaz:
http://arxiv.org/abs/2303.10829
Scientific experiments study interventions that show evidence of an effect size that is meaningfully large, negligibly small, or inconclusively broad. Previously, we proposed contra-analysis as a decision-making process to help determine which interv
Externí odkaz:
http://arxiv.org/abs/2303.09428
At every phase of scientific research, scientists must decide how to allocate limited resources to pursue the research inquiries with the greatest potential. This prioritization dictates which controlled interventions are studied, awarded funding, pu
Externí odkaz:
http://arxiv.org/abs/2210.04867
Autor:
Bourne, Philip E., Bonazzi, Vivien, Brand, Amy, Carroll, Bonnie, Foster, Ian, Guha, Ramanathan V., Hanisch, Robert, Keller, Sallie Ann, Kennedy, Mary Lee, Kirkpatrick, Christine, Mons, Barend, Nusser, Sarah M., Stebbins, Michael, Strawn, George, Szalay, Alex
On August 2, 2021 a group of concerned scientists and US funding agency and federal government officials met for an informal discussion to explore the value and need for a well-coordinated US Open Research Commons (ORC); an interoperable collection o
Externí odkaz:
http://arxiv.org/abs/2208.04682
With limited resources, scientific inquiries must be prioritized for further study, funding, and translation based on their practical significance: whether the effect size is large enough to be meaningful in the real world. Doing so must evaluate a r
Externí odkaz:
http://arxiv.org/abs/2205.12958
Autor:
Corliss, Bruce A., Brown, Taylor R., Zhang, Tingting, Janes, Kevin A., Shakeri, Heman, Bourne, Philip E.
Statistical insignificance does not suggest the absence of effect, yet scientists must often use null results as evidence of negligible (near-zero) effect size to falsify scientific hypotheses. Doing so must assess a result's null strength, defined a
Externí odkaz:
http://arxiv.org/abs/2201.01239
Autor:
Cai, Tian, Xie, Li, Chen, Muge, Liu, Yang, He, Di, Zhang, Shuo, Mura, Cameron, Bourne, Philip E., Xie, Lei
Advances in biomedicine are largely fueled by exploring uncharted territories of human biology. Machine learning can both enable and accelerate discovery, but faces a fundamental hurdle when applied to unseen data with distributions that differ from
Externí odkaz:
http://arxiv.org/abs/2111.14283
Implementation plans for the National Institutes of Health policy for data management and sharing, which takes effect in 2023, provide an opportunity to reflect on the stakeholders, infrastructures, practice, economics, and sustainability of data sha
Externí odkaz:
http://arxiv.org/abs/2109.01694
Autor:
Zhao, Zheng, Bourne, Philip E.
Reversible covalent kinase inhibitors (RCKIs) are a class of novel kinase inhibitors attracting increasing attention because they simultaneously show the selectivity of covalent kinase inhibitors, yet avoid permanent protein-modification-induced adve
Externí odkaz:
http://arxiv.org/abs/2106.11698