More Like this

1. Networks: expanding evolutionary thinking

   https://doi.org/10.1016/j.tig.2013.05.007  

   Bapteste, Eric; van Iersel, Leo; Janke, Axel; Kelchner, Scot; Kelk, Steven; McInerney, James O.; Morrison, David A.; Nakhleh, Luay; Steel, Mike; Stougie, Leen; et al (August 2013, Trends in Genetics)
2. Expanding the BASIL CURE

   https://doi.org/10.35459/tbp.2024.000273  

   Koeppe, Julia R; Dattelbaum, Jonathan D; Hall, Bonnie L; Mills, Stephen A; Offerdahl, Erika G; Pikaart, Michael J; Roberts, Rebecca; Sikora, Arthur; Craig, Paul A (January 2025, The Biophysicist)

   In the Biochemistry Authentic Scientific Inquiry Lab (BASIL) course-based undergraduate research experience, students use a series of computational (sequence and structure comparison, docking) and wet lab (protein expression, purification, and concentration; sodium dodecyl sulfate-polyacrylamide gel electrophoresis [SDS-PAGE]; enzyme activity and kinetics) modules to predict and test the function of protein structures of unknown function found in the Protein Data Bank and UniProt. BASIL was established in 2015 with a core of 10 faculty members on six campuses, with the support of an educational researcher and doctoral student on a seventh campus. Since that time, the number of participating faculty members and campuses has grown, and we have adapted our curriculum to improve access for all who are interested. We have also expanded our curriculum to include new developments that are appearing in computational approaches to life science research. In this article, we provide a history of BASIL, explain our current approach, describe how we have addressed challenges that have appeared, and describe our curriculum development pipeline and our plans for moving forward in a sustainable and equitable fashion. 

   more » « less
3. Specialization at an expanding front

   https://doi.org/10.1103/PhysRevE.108.L032402  

   Li, Lauren H.; Kardar, Mehran (September 2023, Physical Review E)

   As a population grows, spreading to new environments may favor specialization. In this paper, we introduce and explore a model for specialization at the front of a colony expanding synchronously into new territory. We show through numerical simulations that, by gaining fitness through accumulating mutations, progeny of the initial seed population can differentiate into distinct specialists. With competition and selection limited to the growth front, the emerging specialists first segregate into sectors, which then expand to dominate the entire population. We quantify the scaling of the fixation time with the size of the population and observe different behaviors corresponding to distinct universality classes: unbounded and bounded gains in fitness lead to superdiffusive (z = 3/2) and diffusive (z = 2) stochastic wanderings of the sector boundaries, respectively. 

   more » « less
4. Expanding Opportunities through Concurrent Enrollment

   https://doi.org/10.1145/3408877.3439645  

   Fall, Renee (March 2021, SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education)

   null (Ed.)
5. nanoHUB@home: Expanding nanoHUBThroughVolunteer Computing

   Clark, Steven; Haley, Benjamin; Hunt, Martin; Denny, Nathan; Anderson, David (October 2019, Gateways 2019)

   Volunteer computing (VC) uses consumer digital electronics products, such as PCs, mobile devices, and game consoles, for high-throughput scientific computing. Device owners participate in VC by installing a program which, in the background, downloads and executes jobs from servers operated by science projects. Most VC projects use BOINC, an open-source middleware system for VC. BOINC allows scientists create and operate VC projects and enables volunteers to participate in these projects. Volunteers install a single application (the BOINC client) and then choose projects to support. We have developed a BOINC project, nanoHUB@home, to make use of VC in support of the nanoHUB science gateway. VC has greatly expanded the computational resources available for nanoHUB simulations. We are using VC to support “speculative exploration”, a model of computing that explores the input parameters of online simulation tools published through the nanoHUB gateway, pre-computing results that have not been requested by users. These results are stored in a cache, and when a user launches an interactive simulation our system first checks the cache. If the result is already available it is returned to the user immediately, leaving the computational resources free and not re-computing existing results. The cache is also useful for machine learning (ML) studies, building surrogate models for nanoHUB simulation tools that allow us to quickly estimate results before running an expensive simulation. VC resources also allow us to support uncertainty quantification (UQ) in nanoHUB simulation tools, to go beyond simulations and deliver real-world predictions. Models are typically simulated with precise input values, but real-world experiments involve imprecise values for device measurements, material properties, and stimuli. The imprecise values can be expressed as a probability distribution of values, such as a Gaussian distribution with a mean and standard deviation, or an actual distribution measured from experiments. Stochastic collocation methods can be used to predict the resulting outputs given a series of probability distributions for inputs. These computations require hundreds or thousands of simulation runs for each prediction. This workload is well-suited to VC, since the runs are completely separate, but the results of all runs are combined in a statistical analysis. 

   more » « less