Biology subjects

Dale, R.

Publications and source records attributed to Dale, R..

6 recordsLinked to original sources

bioRxiv2018

Four assessment methods to measure student gains in a graduate course on mathematical modeling in cell biology

The push for mathematics and quantitative skill development in biology is greater than ever before. The perceptions of these techniques are a barrier to their implementation on a grand scale. Methods to assess the efficacy of approaches to teaching quantitative skills are needed to determine if they effectively overcome social stereotypes and fears of math. In our project we study the effect of a mathematical modeling course in cell biology. We developed four assessments to understand if hands-on modeling increases student understanding of the concepts while simultaneously reducing fear of math. Two concept inventories track students learning gains both in general and specific knowledge to the course content. Two surveys quantify students quantitative confidence and opinions of the usefulness of these techniques in biology. We discuss the effectiveness of our methods and the implications for assessment development in mathematical biology education.

scientific communication and education↗

bioRxiv2018

Hierarchical modeling of the effect of pre-exposure prophylaxis on HIV in the US

1.AO_SCPLOWBSTRACTC_SCPLOWIn this paper we present a differential equation model stratified by behavioral risk and sexual activity. Some susceptible individuals have higher rates of risky behavior that increase their chance of contracting the disease. Infected individuals can be considered to be generally sexually active or inactive. The sexually active infected population is at higher risk of transmitting the disease to a susceptible individual. We further divide the sexually active population into diagnosed or undiagnosed infected individuals. We define model parameters for both the national and the urban case. These parameter sets are used to study the predicted population dynamics over the next 5 years. Our results indicate that the undiagnosed high risk infected group is the largest contributor to the epidemic. Finally, we apply a preventative medication protocol to the susceptible population and observe the effective reduction in the infected population. The simulations suggest that preventative medication effectiveness extends outside of the group that is taking the drug (herd immunity). Our models suggest that a strategy targeting the high risk undiagnosed infected group would have the largest impact in the next 5 years. We also find that such a protocol has similar effects for the national as the urban case, despite the smaller sexual network found in rural areas.

epidemiology↗

bioRxiv2017

Is the HIV epidemic over? Investigating population dynamics using Bayesian methodology to estimate epidemiological parameters for a system of stochastic differential equations

Current estimates of the HIV epidemic indicate a decrease in the incidence of the disease in the undiagnosed subpopulation over the past 10 years. However, a lack of access to care has not been considered when modeling the population. Populations at high risk for contracting HIV are twice as likely to lack access to reliable medical care. In this paper, we consider three contributors to the HIV population dynamics: susceptible pool exhaustion, lack of access to care, and usage of anti-retroviral therapy (ART) by diagnosed individuals. We consider the change in the proportion of undiagnosed individuals as the parameter in a simple Markov model. We obtain conservative estimates for the proportional change of the infected subpopulations using hierarchical Bayesian statistics. The estimated proportional change is used to derive epidemic parameter estimates for a system of stochastic differential equations (SDEs). Epidemic parameters are modified to capture the dynamics of each of the three contributors, as well as all their possible combinations. Model fit is quantified to determine the best explanation for the observed dynamics in the infected subpopulations.\n\nAuthor summaryUsing a combination of statistics and mathematical modeling, we look at some possible reasons for the reported decrease in the number of undiagnosed people living with HIV. One possibility is that the population of people at significant risk to contract HIV is being depleted (susceptibles). This might happen if significant risk for HIV infection occurs in small percentages of the overall population. Another possibility is that infected individuals lack access to care in some regions due to poverty or other cause. In this case we have to question the accuracy of the estimated size of that population. Finally, most diagnosed individuals report being on medication that reduces their viral load. This greatly reduces their chance to transmit HIV to susceptible individuals. We also combine these possibilities and look at the best explanation for the infected population size.

epidemiology↗

bioRxiv2017

Bioconda: A sustainable and comprehensive software distribution for the life sciences

We present Bioconda (https://bioconda.github.io), a distribution of bioinformatics software for the lightweight, multiplatform and language-agnostic package manager Conda. Currently, Bioconda offers a collection of over 3000 software packages, which is continuously maintained, updated, and extended by a growing global community of more than 200 contributors. Bioconda improves analysis reproducibility by allowing users to define isolated environments with defined software versions, all of which are easily installed and managed without administrative privileges.

bioinformatics↗

bioRxiv2017

Practical computational reproducibility in the life sciences

Many areas of research suffer from poor reproducibility. This problem is particularly acute in computationally intensive domains where results rely on a series of complex methodological decisions that are not well captured by traditional publication approaches. Various guidelines have emerged for achieving reproducibility, but practical implementation of these practices remains difficult. This is because reproducing published computational analyses requires installing many software tools plus associated libraries, connecting tools together into the complete pipeline, and specifying parameters. Here we present a suite of recently emerged technologies which make computational reproducibility not just possible, but, finally, practical in both time and effort. By combining a system for building highly portable packages of bioinformatics software, containerization and virtualization technologies for isolating reusable execution environments for these packages, and an integrated workflow system that automatically orchestrates the composition of these packages for entire pipelines, an unprecedented level of computational reproducibility can be achieved.

bioinformatics↗

bioRxiv2017

Abnormal cell sorting underlies the unique X-linked inheritance of PCDH19 Epilepsy

X-linked diseases typically exhibit more severe phenotypes in males than females. In contrast, Protocadherin 19 (PCDH19) mutations cause epilepsy in heterozygous females but spare hemizygous males. The cellular mechanism responsible for this unique pattern of X-linked inheritance is unknown. We show that PCDH19 contributes to highly specific combinatorial adhesion codes such that mosaic expression of Pcdh19 in heterozygous female mice leads to striking sorting between WT PCDH19- and null PCDH19-expressing cells in the developing cortex, correlating with altered network activity. Complete deletion of PCDH19 in heterozygous mice abolishes abnormal cell sorting and restores normal network activity. Furthermore, we identify variable cortical malformations in PCDH19 epilepsy patients. Our results highlight the role of PCDH19 in determining specific adhesion codes during cortical development and how disruption of these codes is associated with the unique X-linked inheritance of PCDH19 epilepsy.

developmental biology↗