Multiple Knowledge Sources Research Articles

Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

BackgroundBayesian Network (BN) is a powerful approach to reconstructing genetic regulatory networks from gene expression data. However, expression data by itself suffers from high noise and lack of power. Incorporating prior biological knowledge can improve the performance. As each type of prior knowledge on its own may be incomplete or limited by quality issues, integrating multiple sources of prior knowledge to utilize their consensus is desirable.ResultsWe introduce a new method to incorporate the quantitative information from multiple sources of prior knowledge. It first uses the Naïve Bayesian classifier to assess the likelihood of functional linkage between gene pairs based on prior knowledge. In this study we included cocitation in PubMed and schematic similarity in Gene Ontology annotation. A candidate network edge reservoir is then created in which the copy number of each edge is proportional to the estimated likelihood of linkage between the two corresponding genes. In network simulation the Markov Chain Monte Carlo sampling algorithm is adopted, and samples from this reservoir at each iteration to generate new candidate networks. We evaluated the new algorithm using both simulated and real gene expression data including that from a yeast cell cycle and a mouse pancreas development/growth study. Incorporating prior knowledge led to a ~2 fold increase in the number of known transcription regulations recovered, without significant change in false positive rate. In contrast, without the prior knowledge BN modeling is not always better than a random selection, demonstrating the necessity in network modeling to supplement the gene expression data with additional information.Conclusionour new development provides a statistical means to utilize the quantitative information in prior biological knowledge in the BN modeling of gene expression data, which significantly improves the performance.

KNOWLEDGE MANAGEMENT FOR LAND DEGRADATION MONITORING AND ASSESSMENT: AN ANALYSIS OF CONTEMPORARY THINKING

ABSTRACTIt is increasingly recognised that land degradation monitoring and assessment can benefit from incorporating multiple sources of knowledge, using a variety of methods at different scales, including the perspectives of researchers, land managers and other stakeholders. However, the knowledge and methods required to achieve this are often dispersed across individuals and organisations at different levels and locations. Appropriate knowledge management mechanisms are therefore required to more efficiently harness these different sources of knowledge and facilitate their broader dissemination and application. This paper examines what knowledge is, how it is generated and explores how it may be stored, transferred and exchanged between knowledge producers and users before it is applied to monitor and assess land degradation at the local scale. It suggests that knowledge management can also benefit from the development of mechanisms that promote changes in understanding and efficient means of accessing and/or brokering knowledge. Broadly, these processes for knowledge management can (i) help identify and share good practices and build capacity for land degradation monitoring at different scales and in different contexts and (ii) create knowledge networks to share lessons learned and monitoring data among and between different stakeholders, scales and locations. Copyright © 2011 John Wiley & Sons, Ltd.

Metalinguistic contributions to reading and spelling in second and third grade students

Minimal research has been conducted on the simultaneous influence of multiple metalinguistic, linguistic, and processing skills that may impact literacy development in children who are in the process of learning to read and write. In this study, we assessed the phonemic awareness, morphological awareness, orthographic awareness, receptive vocabulary, and rapid naming abilities of second and third grade students (N = 56) and determined how these abilities predicted the children’s reading and spelling skills. Regression analyses revealed that morphological awareness was the sole unique contributor to spelling and, together with orthographic awareness, uniquely contributed to word recognition. Morphological awareness also was significantly related to reading comprehension. The results add to a growing literature base providing evidence that early literacy development is influenced by morphological awareness, an ability that has received considerably less educational attention. Additionally, the findings point to the importance of tapping into multiple sources of metalinguistic knowledge when providing instruction in reading and spelling.

The implementation crisis in conservation planning: could “mental models” help?

Core to the planning–implementation gap in conservation is the failure to achieve the necessary shared vision and collaboration among typically diverse stakeholder groups to translate conservation assessments and plans into sustained on-ground outcomes for conservation. We suggest that a process of describing and sharing mental models—the cognitive frameworks that people use to interpret and understand the world—provides promising and as yet underutilized techniques for conservation planners to improve implementation success. The processes and techniques associated with the mental models concept have been applied in a variety of fields including business and organization science, risk analysis, education, natural resource management, and climate change adaptation. Our review of mental models illustrates that their application can strengthen the success of conservation planning by: (1) contributing to clear and open communication between stakeholders; (2) aiding in overcoming obstacles to incorporating multiple sources of knowledge; (3) enabling shared ownership of a conservation plan; and (4) improving social assessments. Techniques to explicitly communicate mental models can contribute to each phase of a conservation planning process—assessment, planning, management, and review. Conservation planners have much to gain by eliciting and sharing mental models in conservation planning processes.

Deliberative assessment in complex socioecological systems: recommendations for environmental assessment in drylands

Desertification is a complex process, characterised not only by a damaged ecology but also by conflict over access to scarce resources and trade-offs between the needs of multiple stakeholders at multiple scales. As such, orthodox approaches to environmental assessment in drylands, which rely solely on ecological expertise, are gradually losing legitimacy and greater attention is being given to integrated and participatory assessment approaches, which draw on multiple sources of knowledge in order to accurately describe complex socioecological processes. Moreover, there is growing recognition that successful management of desertification requires a strategy that can accommodate the multiple and often competing needs of contemporary and future stakeholders. In light of these conceptual advances, this paper highlights seven key criteria that dryland environmental assessments must meet: (1) accurately understand complex socioecological system processes, (2) focus on slow variables, (3) integrate multiple scales of analysis, (4) integrate multiple stakeholder perspectives and values, (5) ensure that future generations are fairly represented, (6) ensure that less powerful stakeholders are fairly represented and (7) integrate local and scientific knowledge. The virtues and challenges of deliberative environmental assessments, a novel subset of participatory environmental assessment approaches which places emphasis on social learning, argumentation and critical reflection, are considered in relation to each of these requirements. We argue that deliberative approaches have the potential to achieve accurate, progressive and integrated assessment of dryland environments.

Fusing multiple Bayesian knowledge sources

We address the problem of information fusion in uncertain environments. Imagine there are multiple experts building probabilistic models of the same situation and we wish to aggregate the information they provide. There are several problems we may run into by naively merging the information from each. For example, the experts may disagree on the probability of a certain event or they may disagree on the direction of causality between two events (e.g., one thinks A causes B while another thinks B causes A). They may even disagree on the entire structure of dependencies among a set of variables in a probabilistic network. In our proposed solution to this problem, we represent the probabilistic models as Bayesian Knowledge Bases (BKBs) and propose an algorithm called Bayesian knowledge fusion that allows the fusion of multiple BKBs into a single BKB that retains the information from all input sources. This allows for easy aggregation and de-aggregation of information from multiple expert sources and facilitates multi-expert decision making by providing a framework in which all opinions can be preserved and reasoned over.

Cross‐scale monitoring and assessment of land degradation and sustainable land management: A methodological framework for knowledge management

AbstractFor land degradation monitoring and assessment (M&A) to be accurate and for sustainable land management (SLM) to be effective, it is necessary to incorporate multiple knowledges using a variety of methods and scales, and this must include the (potentially conflicting) perspectives of those who use the land. This paper presents a hybrid methodological framework that builds on approaches developed by UN Food & Agriculture Organisation's land degradation Assessment in Drylands (LADA), the World Conservation Approaches and Technologies (WOCAT) programme and the Dryland Development Paradigm (DDP), and is being applied internationally through the EU‐funded DESIRE project. The framework suggests that M&A should determine the progress of SLM towards meeting sustainability goals, with results continually and iteratively enhancing SLM decisions. The framework is divided into four generic themes: (i) establishing land degradation and SLM context and sustainability goals; (ii) identifying, evaluating and selecting SLM strategies; (iii) selecting land degradation and SLM indicators and (iv) applying SLM options and monitoring land degradation and progress towards sustainability goals. This approach incorporates multiple knowledge sources and types (including land manager perspectives) from local to national and international scales. In doing so, it aims to provide outputs for policy‐makers and land managers that have the potential to enhance the sustainability of land management in drylands, from the field scale to the region, and to national and international levels. The paper draws on operational experience from across the DESIRE project to break the four themes into a series of methodological steps, and provides examples of the range of tools and methods that can be used to operationalise each of these steps. Copyright © 2011 John Wiley & Sons, Ltd.

Understanding pharmacokinetics using realistic computational models of fluid dynamics: biosimulation of drug distribution within the CSF space for intrathecal drugs

We introduce how biophysical modeling in pharmaceutical research and development, combining physiological observations at the tissue, organ and system level with selected drug physiochemical properties, may contribute to a greater and non-intuitive understanding of drug pharmacokinetics and therapeutic design. Based on rich first-principle knowledge combined with experimental data at both conception and calibration stages, and leveraging our insights on disease processes and drug pharmacology, biophysical modeling may provide a novel and unique opportunity to interactively characterize detailed drug transport, distribution, and subsequent therapeutic effects. This innovative approach is exemplified through a three-dimensional (3D) computational fluid dynamics model of the spinal canal motivated by questions arising during pharmaceutical development of one molecular therapy for spinal cord injury. The model was based on actual geometry reconstructed from magnetic resonance imaging data subsequently transformed in a parametric 3D geometry and a corresponding finite-volume representation. With dynamics controlled by transient Navier–Stokes equations, the model was implemented in a commercial multi-physics software environment established in the automotive and aerospace industries. While predictions were performed in silico, the underlying biophysical models relied on multiple sources of experimental data and knowledge from scientific literature. The results have provided insights into the primary factors that can influence the intrathecal distribution of drug after lumbar administration. This example illustrates how the approach connects the causal chain underlying drug distribution, starting with the technical aspect of drug delivery systems, through physiology-driven drug transport, then eventually linking to tissue penetration, binding, residence, and ultimately clearance. Currently supporting our drug development projects with an improved understanding of systems physiology, biophysical models are being increasingly used to characterize drug transport and distribution in human tissues where pharmacokinetic measurements are difficult or impossible to perform. Importantly, biophysical models can describe emergent properties of a system, i.e. properties not identifiable through the study of the system’s components taken in isolation.

Improving conservation and fishery assessments with local knowledge: future directions

While there is great interest in the potential of local knowledge to inform quantitative conservation, there are no formal guidelines for its interpretation or analysis. Our work to quantify retrospective bias in fisher interviews and explore effects on IUCN Red List assessments shows that assumptions made when analyzing local knowledge affect conservation assessments (O’Donnell, Pajaro & Vincent, 2010). Aswani (2010), Daw (2010), and Patterson (2010) suggest several important ways to improve our understanding of local knowledge and its incorporation into conservation and management. We concur with Patterson (2010) who notes that the existence of bias does not render local knowledge useless. As part of ‘re-inventing fisheries management’ (Pitcher, Hart & Pauly, 1998) scientists must confront uncertainty by quantifying and including it in management recommendations (Ludwig, Hilborn & Walters, 1993). Fisher knowledge should be probed with the same analytical rigor as scientifically collected data, and to do so we need methods to quantify and correct bias in local knowledge. Daw suggests research to identify and quantify memory and perception bias that will improve our ability to accurately incorporate local knowledge into quantitative conservation assessments (2010). Psychologists have identified biases that can occur when we recall events from the past (e.g. Bradburn, Rips & Shevell, 1987), but there is currently no approach for quantifying those biases. As Daw (2010) suggests, there is a need for collaboration with psychologists to understand the nature and existence of retrospective bias along with a host of other memory and perception biases (table 1; Daw, 2010). Developing methods of quantifying these biases and/or procedures to correct for them, as we have explored here, would allow researchers to interpret interview responses appropriately, improving conservation assessments. A range of existing techniques should be utilized to help us collect and apply local knowledge as accurately as possible. There is a growing literature about how to design studies, phrase questions, and choose appropriate respondents (e.g. Neis et al., 1999a; Davis & Wagner, 2003; Anadon et al., 2009). Quantitative assessment protocols are being developed that explicitly incorporate local knowledge (e.g. Walmsley, Medley & Howard, 2005). It is necessary to acknowledge memory biases that may be present (Table 1; Daw, 2010) and consider the motivations of respondents to overor underreport (reviewed by Yasue, Kaufman & Vincent, 2010). Comparing multiple sources of local knowledge (‘local’ data-collection methods reviewed by Danielsen, Burgess & Balmford, 2005) with scientific observations can help determine the strengths and weaknesses of both approaches. As well, assumptions about biases should be made explicit in research papers and researchers should experiment with metrics to account for biases and evaluate effects on results. As both Aswani (2010) and Daw (2010) point out, the importance of understanding the perceptions of resource users extends beyond filling data gaps in single-species monitoring. Aswani reminds us that the appropriate application of local knowledge requires a broader understanding of community, beliefs, and economic context of that knowledge (Neis et al., 1999a). For example, our study (O’Donnell et al., 2010) is part of a larger research project to evaluate options for seahorse conservation and management action. We have consulted with a range of stakeholders and experts from fishers to scientists about preferred management options (Martin-Smith et al., 2004). We are currently investigating the spatial and behavioral dynamics of fishing, noted by Aswani (2010) as being necessary for moving beyond managing for single species to a more comprehensive socialecological system. We also agree with Daw’s (2010) suggestion that a better understanding of how humans perceive and recall environmental change can help us understand conflicts in conservation and resource governance. Conflict can arise when there is a gap between fishers’ perceptions and scientific knowledge used to inform management of fishing. From another study conducted in our focal community, Handumon, we

Second Graders as Spellers: What Types of Errors Are They Making?

Beginning second-grade students ( N = 60) were administered a researcher-developed, dictated spelling test. Spelling errors of students were analyzed by grade-level spelling patterns and linguistic characteristics: phonological, orthographic, orthographic image, transposition, and morphological. Results revealed that morphological spelling pattern errors occurred most frequently. The frequency of linguistic category errors for this sample, ranging from least to most, was transposition, phonological, orthographic image, orthographic, and morphological. Further analysis of the bottom quarter of students, as determined by their performance on a timed word reading measure, indicated a pattern of spelling errors similar to the rest of the sample, but occurring in significantly greater quantity on average. These findings support previous research suggesting poor spellers display similar error patterns as better spelling peers, but with higher frequency. Initial implications suggest to educators that in spite of the wide range of spelling ability in their classrooms, the pattern of knowledge appears similar. Students rely on multiple sources of linguistic knowledge, and by analyzing their spelling errors based on the information students use to generate their spellings, instruction may be provided to explicitly and systematically target students’ weaknesses.

Bridging the Agricultural Knowledge and Information Divide: The Case of Selected Telecenters and Rural Radio in Tanzania

AbstractInformation and communication technologies (ICTs) are important resources for enabling poor farmers to make informed decision regarding their farming activities, especially in the rural areas of developing countries. Effective public access ICTs (telecenters and rural radio) based on farmers needs and with farmers’ rural and socio‐economic constraints can bridge the knowledge and information divide and contribute to agricultural growth. This paper looks at the public access ICTs (telecenters and rural radio) in Tanzania, by assessing their knowledge and information services that focus on supporting farming activities of small‐scale farmers, use of telecenters and barriers faced by telecenters in their knowledge and information services. A qualitative approach was deployed to interview eight telecenter operators, where two of them provided radio broadcasting services. The study found that there was low use of internet for knowledge acquisition, while cell phones were becoming popular for farmers to communicate with telecenter operators and rural radio in case of emergency or advice regarding farming activities. With consistent government funding and conducive regulatory environment, telecenters can develop demand led services and sustain their services by strengthening the following: regular information needs assessments; capacity building; knowledge culture; collaboration among farmers and other related organizations; and utilization of multiple sources of knowledge (such as, ICTs and indigenous communication approaches) in order to meet the disparate farmers’ needs.

Digital Stories: Incorporating Narrative Pedagogy

An ever-increasingly complex health care environment requires practitioners who can solve clinical problems from a range of perspectives and synthesize multiple sources of knowledge. Narrative pedagogy was the framework for a digital story assignment for a senior-level synthesis and clinical decision making course. This article describes how the use of digital stories enhanced students' clinical thinking strategies from a narrative pedagogy perspective.

Belief and Feeling in Self-reports of Emotion: Evidence for Semantic Infusion Based on Self-esteem

When people make verbal reports of their emotional experience, they can rely on multiple sources of knowledge, including generalized beliefs about the self. To the extent that generalized beliefs about the self are used, we term the resultant consequence a semantic infusion effect. Across three studies, we demonstrate the predictable consequences of making emotion judgments more quickly versus more slowly, based on a recent model of the emotional self-report process (Robinson & Clore, 2002a). As predicted, when participants (Ns = 69, 37, and 44) made emotion judgments involving long time frames (e.g., last couple of months; Studies 1–3), faster judgments were associated with emotion ratings that were more consistent with global self-esteem. By contrast, when making emotion judgments involving a short time frame (right now; Study 3), the same pattern was not found. Results are interpreted in terms of semantic infusion effects, although other theoretical frameworks are also discussed. The results have implications for understanding global self-esteem and emotion self-reports.

Training implications of harmful effects of psychological treatments.

The goal of this article is to delineate training implications regarding harmful effects associated with psychotherapy. The authors strongly recommend that trainees be made aware of (and encouraged to examine carefully) the potentially harmful treatments that have been recently identified (Lilienfeld, 2007). Consistent with a broad perspective on evidence-based practice, it is also argued that additional guidelines for the prevention and repair of harmful impacts can be derived from psychotherapy research on process (technique and relationship) and participant (client and therapist) variables. For example, rigid adherence to the application of psychotherapy techniques can be a potentially harmful therapist behavior that necessitates careful training on the nature and flexible use of interventions. Furthermore, the authors suggest that trainers and supervisors tentatively consider training implications linked to clinical observations and theoretical assertions, such as the premature use of clinical interpretations, with the assumption that more confidence in such therapeutic guidelines can be gained when they are supported by multiple knowledge sources (empirical, clinical, conceptual). Finally, training implications related to the monitoring of harmful effects in terms of treatment outcome and process are demarcated.

Transcription Factor-Target Gene Mapping Enhanced by Integrating Motif Search, Function Annotation and Expression Data

Transcriptional regulation is essential for all eukaryotes. Defining regulatory networks, linking transcription factors (TF) to target genes, is of fundamental importance to biology. Developing predictive models for TF-target mapping is critical to test current understandings and to propose new hypotheses. Nevertheless, predicting target genes remains challenging because TF binding motifs are often short, degenerated and widely-spread. Moreover, the binding mechanisms are generally more complex than recognizing a specific sequence. Thus, apart from leveraging the motif identification accuracy, it may be helpful to integrate alternative knowledge depicting the relationship between the TF and the targets.Herein we developed an integrated TF-target mapping strategy and examined its performance. The candidate genes were predicted by a sum of three factors: the enrichment and quality of the putative motifs, identified via an optimized position weighted matrix (PWM) score over phylogenetically conserved promoter regions; a Gene Ontology-based semantic functional relevancy measure; and a causal relationship measure between the gene and the TF derived from expression profiles. The evaluation was conducted using 52 transcription factors covering most of the known, PWM-available TFs in higher eukaryotes, and their total of 1315 curated target genes.The integrated strategy achieved a considerably higher accuracy with an area under receiver operating characteristic curve (AUC) of 0.67, compared to the commonly-adopted method relying on solely a motif enrichment score (AUC of 0.56). In particular, optimizing the PWM score in phylogenetically conserved promoters increased both sensitivity and specificity; functional relevancy and causal correlation further lowered the false positives.The results illustrate the feasibility of integrating multiple knowledge sources to improve TF-target mapping. The presented strategy is readily scalable to genome-wide, and can be applied along with other inference tools to assist the regulatory network reengineering.

Knowledge of Tobacco Control Policies Among U.S. Southeast Asians

Some of the highest smoking rates in the U.S. have been reported among Southeast Asians. The largest numbers of Southeast Asians reside in California. While California has a comprehensive and generally effective tobacco control program, it is unclear how immigrant groups learn of this public health effort. In a study of tobacco norms and practices among two generations of Southeast Asians we collected qualitative data on respondents' knowledge and awareness of tobacco control policies. Data were collected through in-person interviews with 164 respondents aged 15-87, evenly divided by smoking status, gender and generation in the U.S. Due to multiple sources of knowledge, general awareness of tobacco control policies and of secondhand smoke were high among both generations of Southeast Asians and the policies were attributed with changes in smoking behavior. Tobacco control regulations may be an effective means to impact tobacco use among immigrants with limited English proficiency.

The Role of Virtual Communities of Practice in Supporting Collaborative Learning among Social Workers

The advent of technology has been instrumental in creating access for social workers to research on evidence-based interventions. However, for many social problems there remains a gap in the availability of proven evidence-based strategies (Rosen et al., 1999). For social workers facing problems for which there is a lack of research evidence, the solution is to develop practice innovations that can be evaluated (Sabah and Cook-Craig, 2008a, b). Virtual communities of practice (VCoP's) are a promising venue for housing reviews of research evidence and engaging social workers to share tacit knowledge and invent practice innovations. During the past two years, the Israeli Ministry of Social Affairs has developed eighteen VCoP's social work practitioners. Those communities are designed to enable practitioners to review and use multiple sources of professional relevant knowledge in user-friendly repositories and to facilitate a collaborative inter-organizational learning and innovativeness. This exploratory study reviews evaluation data collected on the VCoP's. It includes quantitative analysis of secondary data and survey data on usage patterns of VCoP members. Findings related VCoP usage, the impact that organizational endorsement of organizational learning has on worker involvement in the community, and the development of weak professional ties between members were evaluated.

Talk, think, read (if absolutely necessary): The impact of social, personal, and documentary knowledge on task performance

Abstract The organizational memory literature has compared social sources to documentary archives as potential sources of knowledge that decision makers can use when they seek information needed to carry out business activities, but has not considered how an individual's personal stock of relevant knowledge will shape the benefits of such organizational sources of knowledge. This study considers how social interaction, access to documents, and personal knowledge directly and jointly contribute to individual task performance. A multi‐stage laboratory experiment finds that task performance increases most when decision makers can talk with colleagues and then from drawing on their own personal knowledge, while books offer benefits only if people lack colleagues and/or personal knowledge. In turn, social interaction and personal knowledge become more important as tasks became more complex. When available in combination, meanwhile, multiple knowledge sources generate only diminishing marginal returns.

Multiple sources of local knowledge: a global review of ways to reduce nuisance from the beneficial weaver ant Oecophylla

The weaver ants Oecophylla smaragdina and O. longinoda are abundant in tropical Asia, Australia and Africa. Although local people and a handful of scientists appreciate the benefits these tree-dwelling ants bring in terms of medicinal and food source, protection of tree crops, and enhancement of fruit and nut quality, Oecophylla has one major drawback: it also bites people. Perception of this nuisance, and the response to it, is influenced by the frequency of encounters and the perceived benefits gained from Oecophylla. We used a range of methods in more than ten countries to document how people reduce weaver ant nuisance, including interactive rural radio programs. Apart from growers, also ant brood collectors, fruit-pickers and intermediaries in the value chain hold in-depth ecological knowledge on weaver ants. Ways to make Oecophylla more widely accepted and build ecological literacy at various levels of the society are discussed.

A sparse‐grid, nonintrusive formulation of acoustic field uncertainty in ocean waveguides.

The inclusion of environmental uncertainty in simulations of acoustic wave propagation in ocean waveguides is important for the development of simulation‐based prediction methods that quantify the influence of multiple sources of incomplete environmental knowledge on the simulation results. Polynomial chaos expansions have been suggested as a natural mathematical framework for describing both environmental and acoustic field uncertainties, their interaction, and propagation through the waveguide [S. Finette, J. Acoust. Soc. Am. 120 (2006)]. Previous research has described the inclusion of these expansions directly into the propagation equation (the intrusive approach), yielding coupled differential equations for the expansion coefficients. The solution for the coefficients contains the statistical properties of the uncertain field. Here we describe an alternative nonintrusive formulation, where existing acoustic propagation codes can be used to estimate the chaos coefficients rather than solve for them via a complex set of coupled differential equations. The nonintrusive formulation involves multiple solutions of an existing deterministic code, e.g., a wide‐angle parabolic equation solver, in conjunction with the Smolyak sparse‐grid interpolation and multidimensional quadrature to obtain uncertainty statistics on the acoustic field. [Research supported by the Office of Naval Research.]