Dynamic Influence Networks for Rule-based Models

We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the data produced by KaSim, an open source stochastic simulator of rule-based models written in the Kappa language, DINs provide a node-link diagram that represents the influence that each rule has on the other rules. That is, rather than representing individual biological components or types, we instead represent the rules about them (as nodes) and the current influence of these rules (as links). Using our interactive DIN-Viz software tool, researchers are able to query this dynamic network to find meaningful patterns about biological processes, and to identify salient aspects of complex rule-based models. To evaluate the effectiveness of our approach, we investigate a simulation of a circadian clock model that illustrates the oscillatory behavior of the KaiC protein phosphorylation cycle.Comment: Accepted to TVCG, in pres

Teacher Educators Wrestling with Issues of Diversity in Online Courses

This manuscript provides an overview of the findings of an ongoing qualitative exploratory study that examined how preservice and inservice teachers in two different online education courses (ED 600 and ED 500) developed an understanding of the multifaceted issues that affect diverse learners. The study also investigated the instructors’ reflections about their courses through their individual journals. An analysis of the study participants\u27 Discussion Board posts and interactions online revealed how the Discussion Board forum was used as a critical, reflective space for participants\u27 to engage in self-reflection and to exchange and challenge one another\u27s ideas. The journals also revealed the instructors\u27 overall aspirations for the course, and their role in cultivating an online community in their courses

Social Justice Leadership: A Case Study of Engagement Practices with Multilingual Families

Traditionally established best practices for parent engagement cannot be assumed to be effective when serving culturally and linguistically diverse families. Such practices do not account for cultural variation and linguistic differences in family involvement with school-based activities. School leaders with a social justice orientation are key to challenging established practices and creating school cultures where multilingual families are welcomed and engaged. The authors present a qualitative case study of an administrator and the lead ESL (English as a Second Language) teacher of a large urban charter school in the northeast region of the United States, and their efforts to serve and support the families of English language learners (ELLs) to explore the question: How do school leaders exhibit a commitment to social justice in their leadership and practice? Using Furman’s (2012) dimensions of social justice leadership as a framework for analysis, we identified the following themes from interviews with the school leaders: reflexive leadership; building trust and support; building inclusive communities; creating systemic change; and supporting families in larger sociopolitical contexts. The findings of the study reveal how these two school leaders instantiated social justice perspectives and practices in creating a school that invited inclusion and full participation of multilingual families. The findings of the study can help educational researchers and practitioners rethink the sufficiency of established best practices for schools serving multilingual families

Familial aggregation of components of the multiple metabolic syndrome in the Framingham Heart and Offspring Cohorts: Genetic Analysis Workshop Problem 1

BACKGROUND: The multiple metabolic syndrome is defined by a clustering of risk factors for cardiovascular disease. We sought to evaluate the familial correlations of the components of the syndrome using data from the Framingham Heart Study original and offspring cohorts as provided for the Genetic Analysis Workshop 13. Measures of plasma cholesterol (total and HDL), body mass index (BMI), and systolic blood pressure were used from selected calendar years of exams. Familial correlations were calculated using FCOR in S.A.G.E. RESULTS: The sibling correlations were relatively high for all measures and exams, from 0.17 for systolic blood pressure to 0.27 for HDL cholesterol. The parent-child correlations were very similar, except for systolic blood pressure. The avuncular correlations were much smaller and the cousin correlations were even smaller. For HDL cholesterol the avuncular correlation was half the sibling correlation and the cousin correlation was half that again. Spousal correlations ranged from 0.07 for systolic blood pressure to 0.34 for BMI. Correlations were somewhat lower from 1984 to 1987 examinations than from 1971 to 1975 examinations, except for spousal correlations for systolic blood pressure and BMI. CONCLUSION: The results of the family pair correlations are suggestive of genetic determinants of lipid levels and BMI. These components have been shown to be predictive of cardiovascular disease as well as diabetes. Genes in common with each of the components might also influence development of cardiovascular disease and diabetes, both complex diseases