Universally Sloppy Parameter Sensitivities in Systems Biology

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring \emph{in vivo} biochemical parameters is difficult, and collectively fitting them to other data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a `sloppy' spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.Comment: Submitted to PLoS Computational Biology. Supplementary Information available in "Other Formats" bundle. Discussion slightly revised to add historical contex

Quantum Cosmology of Kantowski-Sachs like Models

The Wheeler-DeWitt equation for a class of Kantowski-Sachs like models is completely solved. The generalized models include the Kantowski-Sachs model with cosmological constant and pressureless dust. Likewise contained is a joined model which consists of a Kantowski-Sachs cylinder inserted between two FRW half--spheres. The (second order) WKB approximation is exact for the wave functions of the complete set and this facilitates the product structure of the wave function for the joined model. In spite of the product structure the wave function can not be interpreted as admitting no correlations between the different regions. This problem is due to the joining procedure and may therefore be present for all joined models. Finally, the {s}ymmetric {i}nitial {c}ondition (SIC) for the wave function is analyzed and compared with the ``no bouindary'' condition. The consequences of the different boundary conditions for the arrow of time are briefly mentioned.Comment: 21 pages, uses LaTeX2e, epsf.sty and float.sty, three figures (50 kb); changes: one figure added, new interpretation of quantizing procedure for the joined model and many minor change

Ultraviolet Diversity of Type Ia Supernovae

Ultraviolet (UV) observations of Type Ia supernovae (SNe Ia) probe the outermost layers of the explosion, and UV spectra of SNe Ia are expected to be extremely sensitive to differences in progenitor composition and the details of the explosion. Here we present the first study of a sample of high signal-to-noise ratio SN Ia spectra that extend blueward of 2900 A. We focus on spectra taken within 5 days of maximum brightness. Our sample of ten SNe Ia spans the majority of the parameter space of SN Ia optical diversity. We find that SNe Ia have significantly more diversity in the UV than in the optical, with the spectral variance continuing to increase with decreasing wavelengths until at least 1800 A (the limit of our data). The majority of the UV variance correlates with optical light-curve shape, while there are no obvious and unique correlations between spectral shape and either ejecta velocity or host-galaxy morphology. Using light-curve shape as the primary variable, we create a UV spectral model for SNe Ia at peak brightness. With the model, we can examine how individual SNe vary relative to expectations based on only their light-curve shape. Doing this, we confirm an excess of flux for SN 2011fe at short wavelengths, consistent with its progenitor having a subsolar metallicity. While most other SNe Ia do not show large deviations from the model, ASASSN-14lp has a deficit of flux at short wavelengths, suggesting that its progenitor was relatively metal rich.Comment: 9 pages, 6 figures, submitted to MNRA

Fear of the unknown: a pre-departure qualitative study of Turkish international students

This paper presents findings from eleven in-depth interviews with Turkish undergraduate students, who were, by the time of data collection, about to spend a semester at a European university under the Erasmus exchange scheme. The students all agreed to be interviewed about their feelings about studying in a foreign culture, and were found to be anxious prior to departure about the quality of accommodation in the new destination, their language ability and the opportunity to form friendships. Fears were expressed about possible misconceptions over Turkey as a Muslim and a developing country. Suggestions are made for HEI interventions to allay student travellers’ concerns

The sloppy model universality class and the Vandermonde matrix

In a variety of contexts, physicists study complex, nonlinear models with many unknown or tunable parameters to explain experimental data. We explain why such systems so often are sloppy; the system behavior depends only on a few `stiff' combinations of the parameters and is unchanged as other `sloppy' parameter combinations vary by orders of magnitude. We contrast examples of sloppy models (from systems biology, variational quantum Monte Carlo, and common data fitting) with systems which are not sloppy (multidimensional linear regression, random matrix ensembles). We observe that the eigenvalue spectra for the sensitivity of sloppy models have a striking, characteristic form, with a density of logarithms of eigenvalues which is roughly constant over a large range. We suggest that the common features of sloppy models indicate that they may belong to a common universality class. In particular, we motivate focusing on a Vandermonde ensemble of multiparameter nonlinear models and show in one limit that they exhibit the universal features of sloppy models.Comment: New content adde