Validation and refinement of gene-regulatory pathways on a network of physical interactions.
(9/128)
As genome-scale measurements lead to increasingly complex models of gene regulation, systematic approaches are needed to validate and refine these models. Towards this goal, we describe an automated procedure for prioritizing genetic perturbations in order to discriminate optimally between alternative models of a gene-regulatory network. Using this procedure, we evaluate 38 candidate regulatory networks in yeast and perform four high-priority gene knockout experiments. The refined networks support previously unknown regulatory mechanisms downstream of SOK2 and SWI4. (+info)
Informatics challenges for the impending patient information explosion.
(10/128)
As we move toward an era when health information is more readily accessible and transferable, there are several issues that will arise. This article addresses the challenges of information filtering, context-sensitive decision support, legal and ethical guidelines regarding obligations to obtain and use the information, aligning patient and health professionals' expectations in regard to the use and usefulness of the information, and enhancing data reliability. The authors discuss the issues and offer suggestions for addressing them. (+info)
Health@Home: the work of health information management in the household (HIMH): implications for consumer health informatics (CHI) innovations.
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OBJECTIVE: Contemporary health care places enormous health information management demands on laypeople. Insights into their skills and habits complements current developments in consumer health innovations, including personal health records. Using a five-element human factors model of work, health information management in the household (HIMH) is characterized by the tasks completed by individuals within household organizations, using certain tools and technologies in a given physical environment. DESIGN: We conducted a descriptive-exploratory study of the work of HIMH, involving 49 community-dwelling volunteers from a rural Midwestern community. MEASUREMENTS: During in-person interviews, we collected data using semistructured questionnaires and photographs of artifacts used for HIMH. RESULTS: The work of HIMH is largely the responsibility of a single individual, primarily engaged in the tasks of acquiring, managing, and organizing a diverse set of health information. Paper-based tools are most common, and residents develop strategies for storing information in the household environment aligned with anticipated use. Affiliative relationships, e.g., parent-child or spousal, within the household serve as the organization that gives rise to health information management practices. Synthesis of these findings led to identification of several storage strategies employed in HIMH. These strategies are labeled "just-in-time," "just-because," "just-in-case," and "just-at-hand," reflecting location of the artifacts of health information and anticipated urgency in the need to retrieve it. CONCLUSION: Laypeople develop and employ robust, complex strategies for managing health information in the home. Capitalizing on these strategies will complement and extend current consumer health innovations to provide functional support to people who face increasing demands to manage personal health information. (+info)
Exploring and developing consumer health vocabularies.
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Laypersons ("consumers") often have difficulty finding, understanding, and acting on health information due to gaps in their domain knowledge. Ideally, consumer health vocabularies (CHVs) would reflect the different ways consumers express and think about health topics, helping to bridge this vocabulary gap. However, despite the recent research on mismatches between consumer and professional language (e.g., lexical, semantic, and explanatory), there have been few systematic efforts to develop and evaluate CHVs. This paper presents the point of view that CHV development is practical and necessary for extending research on informatics-based tools to facilitate consumer health information seeking, retrieval, and understanding. In support of the view, we briefly describe a distributed, bottom-up approach for (1) exploring the relationship between common consumer health expressions and professional concepts and (2) developing an open-access, preliminary (draft) "first-generation" CHV. While recognizing the limitations of the approach (e.g., not addressing psychosocial and cultural factors), we suggest that such exploratory research and development will yield insights into the nature of consumer health expressions and assist developers in creating tools and applications to support consumer health information seeking. (+info)
A data integration methodology for systems biology: experimental verification.
(13/128)
The integration of data from multiple global assays is essential to understanding dynamic spatiotemporal interactions within cells. In a companion paper, we reported a data integration methodology, designated Pointillist, that can handle multiple data types from technologies with different noise characteristics. Here we demonstrate its application to the integration of 18 data sets relating to galactose utilization in yeast. These data include global changes in mRNA and protein abundance, genome-wide protein-DNA interaction data, database information, and computational predictions of protein-DNA and protein-protein interactions. We divided the integration task to determine three network components: key system elements (genes and proteins), protein-protein interactions, and protein-DNA interactions. Results indicate that the reconstructed network efficiently focuses on and recapitulates the known biology of galactose utilization. It also provided new insights, some of which were verified experimentally. The methodology described here, addresses a critical need across all domains of molecular and cell biology, to effectively integrate large and disparate data sets. (+info)
A data integration methodology for systems biology.
(14/128)
Different experimental technologies measure different aspects of a system and to differing depth and breadth. High-throughput assays have inherently high false-positive and false-negative rates. Moreover, each technology includes systematic biases of a different nature. These differences make network reconstruction from multiple data sets difficult and error-prone. Additionally, because of the rapid rate of progress in biotechnology, there is usually no curated exemplar data set from which one might estimate data integration parameters. To address these concerns, we have developed data integration methods that can handle multiple data sets differing in statistical power, type, size, and network coverage without requiring a curated training data set. Our methodology is general in purpose and may be applied to integrate data from any existing and future technologies. Here we outline our methods and then demonstrate their performance by applying them to simulated data sets. The results show that these methods select true-positive data elements much more accurately than classical approaches. In an accompanying companion paper, we demonstrate the applicability of our approach to biological data. We have integrated our methodology into a free open source software package named POINTILLIST. (+info)
Charting biologically relevant chemical space: a structural classification of natural products (SCONP).
(15/128)
The identification of small molecules that fall within the biologically relevant subfraction of vast chemical space is of utmost importance to chemical biology and medicinal chemistry research. The prerequirement of biological relevance to be met by such molecules is fulfilled by natural product-derived compound collections. We report a structural classification of natural products (SCONP) as organizing principle for charting the known chemical space explored by nature. SCONP arranges the scaffolds of the natural products in a tree-like fashion and provides a viable analysis- and hypothesis-generating tool for the design of natural product-derived compound collections. The validity of the approach is demonstrated in the development of a previously undescribed class of selective and potent inhibitors of 11beta-hydroxysteroid dehydrogenase type 1 with activity in cells guided by SCONP and protein structure similarity clustering. 11beta-hydroxysteroid dehydrogenase type 1 is a target in the development of new therapies for the treatment of diabetes, the metabolic syndrome, and obesity. (+info)
Microparadigms: chains of collective reasoning in publications about molecular interactions.
(16/128)
We analyzed a very large set of molecular interactions that had been derived automatically from biological texts. We found that published statements, regardless of their verity, tend to interfere with interpretation of the subsequent experiments and, therefore, can act as scientific "microparadigms," similar to dominant scientific theories [Kuhn, T. S. (1996) The Structure of Scientific Revolutions (Univ. Chicago Press, Chicago)]. Using statistical tools, we measured the strength of the influence of a single published statement on subsequent interpretations. We call these measured values the momentums of the published statements and treat separately the majority and minority of conflicting statements about the same molecular event. Our results indicate that, when building biological models based on published experimental data, we may have to treat the data as highly dependent-ordered sequences of statements (i.e., chains of collective reasoning) rather than unordered and independent experimental observations. Furthermore, our computations indicate that our data set can be interpreted in two very different ways (two "alternative universes"): one is an "optimists' universe" with a very low incidence of false results (<5%), and another is a "pessimists' universe" with an extraordinarily high rate of false results (>90%). Our computations deem highly unlikely any milder intermediate explanation between these two extremes. (+info)