6671949
Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach
Gene expression profiling by microarray technology is usually difficult to interpret into a simpler pattern. One approach to resolve the complexity of gene expression profiles is the application of artificial neural networks (ANNs). A potential difficulty in this strategy, however, is that the non-linear nature of ANN makes it essentially a 'black-box' computation process. Addition of a fuzzy logic approach is useful because it can complement ANN by explicitly specifying membership function during computation. We employed a hybrid approach of neural network and fuzzy logic to further analyze a published microarray study of gene responses to eight bacteria in human macrophages. The original analysis by hierarchical clustering found common gene responses to all bacteria but did not address individual responses. Our method allowed exploration of the gene response of the host to individual bacterium. We implemented a two-layer, feed-forward neural network containing the principle of 'competitive learning' (i.e. 'winner-take-all'). The weights of the trained neural network were fed into a fuzzy logic inference system. A new measurement, called the impact rating (IR) was also introduced to explore the degree of importance of each gene. To assess the reliability of the IR value, a bootstrap re-sampling method was applied to the dataset and a confidence level for each IR was obtained. Our approach has successfully uncovered the unique features of host response to individual bacterium. Further, application of gene ontology (GO) annotation to the genes of high IR values in each response has suggested new biological pathways for individual host-pathogen interactions.
14219803
A new method to measure the semantic similarity of GO terms
MOTIVATION
Although controlled biochemical or biological vocabularies, such as Gene Ontology (GO) (http://www.geneontology.org), address the need for consistent descriptions of genes in different data sources, there is still no effective method to determine the functional similarities of genes based on gene annotation information from heterogeneous data sources.


RESULTS
To address this critical need, we proposed a novel method to encode a GO term's semantics (biological meanings) into a numeric value by aggregating the semantic contributions of their ancestor terms (including this specific term) in the GO graph and, in turn, designed an algorithm to measure the semantic similarity of GO terms. Based on the semantic similarities of GO terms used for gene annotation, we designed a new algorithm to measure the functional similarity of genes. The results of using our algorithm to measure the functional similarities of genes in pathways retrieved from the saccharomyces genome database (SGD), and the outcomes of clustering these genes based on the similarity values obtained by our algorithm are shown to be consistent with human perspectives. Furthermore, we developed a set of online tools for gene similarity measurement and knowledge discovery.


AVAILABILITY
The online tools are available at: http://bioinformatics.clemson.edu/G-SESAME.


SUPPLEMENTARY INFORMATION
http://bioinformatics.clemson.edu/Publication/Supplement/gsp.htm.
3245287
Study and Comparison of 3D Face Generation
Four techniques to generate 2.5 D face surfaces from a set of 2D images are compared using both rendering results and surface distance comparison for Orthogonal Views (OV), Photometric Stereo (PSM), Automatic and Interactive Binocular Stereo (ABS and IBS) using Dur database of 20 face surfaces. PSM obtains the best rendered surfaces.
61209915
CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature
This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature—an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981–2004) and terrorism (1990–2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified. © 2006 Wiley Periodicals, Inc.
15960465
InterPlaNetary Internet: state-of-the-art and research challenges
The developments in the space technologies are enabling the realization of deep space scientific missions such as Mars exploration. InterPlaNetary (IPN) Internet is expected to be the next step in the design and development of deep space networks as the Internet of the deep space planetary networks. However, there exist significant challenges to be addressed for the realization of this objective. Many researchers and several international organizations are currently engaged in defining and addressing these challenges and developing the required technologies for the realization of the InterPlaNetary Internet. In this paper, the current status of the research efforts to realize the InterPlaNetary Internet objective is captured. The communication architecture is presented, and the challenges posed by the several aspects of the InterPlaNetary Internet are introduced. The existing algorithms and protocols developed for each layer and the other related work are explored, and their shortcomings are pointed out along with the open research issues for the realization of the InterPlaNetary Internet. The objective of this survey is to motivate the researchers around the world to tackle these challenging problems and help to realize the InterPlaNetary Internet.
6693843
From Spatial Proximity to Semantic Coherence: A Quantitative Approach to the Study of Group Dynamics in Collaborative Virtual Environments
This article describes a quantitative approach to the study of group dynamics in Collaborative Information Visualization Environments (CIVEs). This approach characterizes group dynamics in terms of two concepts introduced in this articlespatial proximity and semantic coherence. The concepts are crucial to the understanding of profound interrelationships between spatial, semantic, and social navigation. Furthermore, this article describes three visualization techniquessemantic indentation chat sequence displays, activity maps, and clock-face mapsthat permit the identification of important features of group interaction that are related to semantic coherence and spatial proximity. The approach is illustrated by applying it to the analysis of an empirical study in which four groups of subjects performed collaborative search tasks through 3D visualizations of knowledge domains. The major contribution of the work is the conceptualization and quantification of group coherence as a generic methodology for the study of a range of collaborative virtual environments such as collaborative learning, distance learning, social networks, collaborative information visualization, and digital libraries. Further research challenges for the study of group behavior in collaborative information-visualization environments are identified.
15331077
Precoded V-BLAST for ISI MIMO channels
The V-BLAST (vertical Bell labs layered space-time) system is one of the MIMO systems designed to achieve a good multiplexing gain. In the recent literature, a V-BLAST precoder has been added in the transmitter which exploits channel information. This precoder forces each symbol stream to have identical MSE (mean square error). It can be viewed as an alternative to the bitloading method. In this paper, this precoded V-BLAST is extended to the case of ISI MIMO channels. Both the FIR and OFDM types of transceivers are derived