2887282
Rat Genome Database (RGD): mapping disease onto the genome
The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is 'to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community'. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.
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.
6056437
WormBase: a comprehensive data resource for Caenorhabditis biology and genomics
WormBase (http://www.wormbase.org), the model organism database for information about Caenorhabditis elegans and related nematodes, continues to expand in breadth and depth. Over the past year, WormBase has added multiple large-scale datasets including SAGE, interactome, 3D protein structure datasets and NCBI KOGs. To accommodate this growth, the International WormBase Consortium has improved the user interface by adding new features to aid in navigation, visualization of large-scale datasets, advanced searching and data mining. Internally, we have restructured the database models to rationalize the representation of genes and to prepare the system to accept the genome sequences of three additional Caenorhabditis species over the coming year.
2867815
Matchings and matching extensions in graphs
Abstract Let G be a graph with a perfect matching and k be an integer such that 1 ⩽ k vbV ( G ) vb /2. Then G is said to be k -extendable if every matching of size k in G extends to a perfect matching of G . Plummer (1994) proved that every (2 k + 1)-connected K 1,3 -free graph of even order is k -extendable. In this paper, it was proved that every (2 k + n − 2)-connected K 1, n -free graph of even order is k -extendable. Also, an answer to the problem of characterizing maximal k -extendable graphs posted by Plummer (1994) and Saito (1989/90) is given. Besides, we show that a regular graph of even order belongs to the first class if its any two odd cycles have at least a vertex in common.
468820
Tracing knowledge diffusion
Knowledge diffusion is the adaptation of knowledge in a broad range of scientific and engineering research and development. Tracing knowledge diffusion between science and technology is a challenging issue due to the complexity of identifying emerging patterns in a diverse range of possible processes. In this article, we describe an approach that combines complex network theory, network visualization, and patent citation analysis in order to improve the means for the study of knowledge diffusion. In particular, we analyze patent citations in the field of tissue engineering. We emphasize that this is the beginning of a longer-term endeavor that aims to develop and deploy effective, progressive, and explanatory visualization techniques for us to capture the dynamics of the evolution of patent citation networks. The work has practical implications on resource allocation, strategic planning, and science policy.
12098402
Noise-aware repeater insertion and wire-sizing for on-chip interconnect using hierarchical moment-matching
Recently, several algorithms for interconnect optimization via repeater insertion and wire sizing have appeared based on the Elmore delay model. Using the Devgan noise metric a noise-aware repeater insertion technique has also been proposed recently. Recognizing the conservatism of these delay and noise models, we propose a moment-matching based technique to interconnect optimization that allows for much higher accuracy while preserving the hierarchical nature of Elmore-delay-based techniques. We also present a novel approach to noise computation that accurately captures the effect of several attackers in linear time with respect to the number of attackers and wire segments. Our practical experiments with industrial nets indicate that the corresponding reduction in error afforded by these more accurate models justifies this increase in runtime for aggressive designs which is our targeted domain. Our algorithm yields delay and noise estimates within 5% of circuit simulation results.
1853084
Trailblazing the literature of hypertext: author co-citation analysis (1989–1998)
This paper presents the analysis and modelling of two data sets associated with the literature of hypertext as represented by the ACM Hypertext conference series. This work explores new ways of organising and accessing the vast amount of interrelated information. The first data set, including all the full papers published in this series (1987 1998), is structured and visualised as a semantic space. This semantic space provides an access point for each paper in this collection. The second data set, containing author co-citation counts based on nine conferences in the series (1989 1998), is analysed and mapped in its entirety and in three evenly distributed sub-periods. Specialties  major research fronts in the field of hypertext  are identified based on the results of a factor analysis and corresponding author co-citation maps. The names of authors in these maps are linked to the bibliographical and citation summaries of these authors on the WWW.