Bayesian variable selection and data integration for biological regulatory networks

A substantial focus of research in molecular biology are gene regulatory networks: the set of transcription factors and target genes which control the involvement of different biological processes in living cells. Previous statistical approaches for identifying gene regulatory networks have used gene expression data, ChIP binding data or promoter sequence data, but each of these resources provides only partial information. We present a Bayesian hierarchical model that integrates all three data types in a principled variable selection framework. The gene expression data are modeled as a function of the unknown gene regulatory network which has an informed prior distribution based upon both ChIP binding and promoter sequence data. We also present a variable weighting methodology for the principled balancing of multiple sources of prior information. We apply our procedure to the discovery of gene regulatory relationships in Saccharomyces cerevisiae (Yeast) for which we can use several external sources of information to validate our results. Our inferred relationships show greater biological relevance on the external validation measures than previous data integration methods. Our model also estimates synergistic and antagonistic interactions between transcription factors, many of which are validated by previous studies. We also evaluate the results from our procedure for the weighting for multiple sources of prior information. Finally, we discuss our methodology in the context of previous approaches to data integration and Bayesian variable selection.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS130 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Visual-haptic interactions in multimodal virtual environments

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1999.Includes bibliographical references (leaves 73-75).by Wan-Chen Wu.S.M

Implicit Theories of Ability and Self-Efficacy: Testing Alternative Social Cognitive Models to Science Motivation

Our overall goal was to empirically test what we called the “growth mindset as inoculation” hypothesis using a series of latent profile analytical approaches. This inoculation hypothesis, which is consistent with the way in which Dweck and Leggett (1988) described their social cognitive approach, states that believing in the malleability of intelligence serves a protective role against negative motivational and achievement outcomes. Participants were Grade 6 students (n = 504) from a middle school and Grade 10 students (n = 354) from two high schools in the Southeastern part of the United States. Two distinct patterns emerged, which corresponded to a growth mindset profile, and an all moderate profile. Our findings did not completely confirm or disconfirm the inoculation hypothesis – rather, a more nuanced conclusion should be drawn. Although there was evidence that the growth mindset profile evinced more adaptive outcomes compared to the all moderate alternative, which reinforced Dweck and Leggett’s claims, there was no evidence of any profiles with a distinct fixed theory of ability. This was true even when we forced our data to conform to such a model. Results refine Dweck and Leggett’s social cognitive approach to motivation

Moving the needle—what does RSAP look for and what does it aim to do?

Peer reviewe

CsrA impacts survival of Yersinia enterocolitica by affecting a myriad of physiological activities.

BackgroundA previous study identified a Yersinia enterocolitica transposon mutant, GY448, that was unable to export the flagellar type three secretion system (T3SS)-dependent phospholipase, YplA. This strain was also deficient for motility and unable to form colonies on Lauria-Bertani agar medium. Preliminary analysis suggested it carried a mutation in csrA. CsrA in Escherichia coli is an RNA-binding protein that is involved in specific post-transcriptional regulation of a myriad of physiological activities. This study investigated how CsrA affects expression of the flagellar regulatory cascade that controls YplA export and motility. It also explored the effect of csrA mutation on Y. enterocolitica in response to conditions that cue physiological changes important for growth in environments found both in nature and the laboratory.ResultsThe precise location of the transposon insertion in GMY448 was mapped within csrA. Genetic complementation restored disruptions in motility and the YplA export phenotype (Yex), which confirmed this mutation disrupted CsrA function. Mutation of csrA affected expression of yplA and flagellar genes involved in flagellar T3SS dependent export and motility by altering expression of the master regulators flhDC. Mutation of csrA also resulted in increased sensitivity of Y. enterocolitica to various osmolytes, temperatures and antibiotics.ConclusionsThe results of this study reveal unique aspects of how CsrA functions in Y. enterocolitica to control its physiology. This provides perspective on how the Csr system is susceptible to adaptation to particular environments and bacterial lifestyles

Clustering of genes into regulons using integrated modeling-COGRIM

We present a Bayesian hierarchical model and Gibbs Sampling implementation that integrates gene expression, ChIP binding, and transcription factor motif data in a principled and robust fashion. COGRIM was applied to both unicellular and mammalian organisms under different scenarios of available data. In these applications, we demonstrate the ability to predict gene-transcription factor interactions with reduced numbers of false-positive findings and to make predictions beyond what is obtained when single types of data are considered

Motivation and Beliefs about the Nature of Scientific Knowledge Within an Immersive Virtual Ecosystems Environment

We explored Grade 6 students‘ (n = 202) self-efficacy, epistemic beliefs, and science interest over a 10-day virtual ecology curriculum. Pre- and post-surveys were administered, and analyses revealed that (1) students became more self-efficacious about inquiring scientifically after participating in the activity; (2) students on average evinced a shift toward more constructivist views about the role of authority in justifying scientific claims; (3) students who identified more strongly with being a science person evinced greater gains in self efficacy, developed a less constructivist view about the role of authority in justifying claims, and became more interested in science overall; and (4) students who held an incremental theory of ability evinced greater gains in self-efficacy. We discuss the implications of these findings for science educators and instructional designers in the design and use of immersive virtual worlds for middle school science students

Ideological Becoming in Socialist and Post-Socialist Childhood and Schooling from a Dialogic Framework

This special DPJ issue aims to bring together those who had first-hand experiences with or conduct educational and/or historical research with children and schooling in socialist and post-socialist societies. Socialist and post-socialist childhood and schooling in socialist and post-socialist education systems are usually assumed to be monolithic and authoritarian, far from dialogic. However, by reflecting on our own or others’ experiences, narratives and observations regarding the socialist and post-socialist childhood, we realized that our memories, experiences and observations might offer unique and enriching soil for understanding, exploring, reflecting, and critiquing dialogic pedagogical theories. Through this special issue, we hope to expand the scholarship of this community to the territory of a space and time that were not previously examined (sufficiently) for dialogic pedagogy by creating interests and forums for dialogues

Mixed-Reality Simulations to Build Capacity for Advocating for Diversity, Equity, and Inclusion in Geosciences

We report on data collected at 3 time points during a 1-year intervention designed to teach a purposive sample of geoscience faculty members (n = 29) from 27 universities throughout the United States how to identify and address issues related to diversity, equity, and inclusion in their departments. For the intervention we used mixed-reality simulations to help participants practice specific skills to address common situations in geoscience departments. The intervention also included an intensive 3-day workshop and 3 journal clubs. Using a Bayesian analytical approach we explored: (a) general trends in participants’ self- and collective efficacy for identifying and addressing diversity, equity, and inclusion over a 1-year period; (b) relationships between self-efficacy and collective efficacy; and (c) demographic factors that explain variation in self- and collective efficacy. Results showed that self- and collective efficacy rose sharply from preintervention to 5 months after beginning. Although both self- and collective efficacy retreated toward baseline at the 1-year mark, only 1-year self-efficacy was still credibly higher than preintervention. Also, preintervention self-efficacy predicted 5-month collective efficacy. Efficacy beliefs varied as a function of race/ethnicity. Only collective efficacy varied as a function of academic rank. We discuss these findings in relation to social– cognitive theory and the literature regarding the use of digital learning environments to address diversity, equity, and inclusion