Biomedical subjects

Deyun Pan

Publications and source records attributed to Deyun Pan.

5 recordsLinked to original sources

PubMed2004

KARMA: a web server application for comparing and annotating heterogeneous microarray platforms.

We have developed a universal web server application (KARMA) that allows comparison and annotation of user-defined pairs of microarray platforms based on diverse types of genome annotation data (across different species) collected from multiple sources. The application is an effective tool for diverse microarray platforms, including arrays that are provided by (i) the Keck Microarray Resource at Yale, (ii) commercially available Affymetrix GeneChips and spotted arrays and (iii) custom arrays made by individual academics. The tool provides a web interface that allows users to input pairs of test files that represent diverse array platforms for either single or multiple species. The program dynamically identifies analogous DNA fragments spotted or synthesized on multiple microarray platforms based on the following types of information: (i) NCBI-Unigene identifiers, if the platforms being compared are within the same species or (ii) NCBI-Homologene data, if they are cross-species. The single-species comparison is implemented based on set operations: intersection, union and difference. Other forms of retrievable annotation data, including LocusLink, SwissProt and Gene Ontology (GO), are collected from multiple remote sites and stored in an integrated fashion using an Oracle database. The KARMA database, which is updated periodically, is available on line at the following URL: http://ymd.med.yale.edu/karma/cgi-bin/karma.pl.

Gene Expression Profiling↗

PubMed2003

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

Arabidopsis↗

PubMed2003

Evaluation of light regulatory potential of Calvin cycle steps based on large-scale gene expression profiling data.

Although large-scale gene expression data have been studied from many perspectives, they have not been systematically integrated to infer the regulatory potentials of individual genes in specific pathways. Here we report the analysis of expression patterns of genes in the Calvin cycle from 95 Arabidopsis microarray experiments, which revealed a consistent gene regulation pattern in most experiments. This identified pattern, likely due to gene regulation by light rather than feedback regulations of the metabolite fluxes in the Calvin cycle, is remarkably consistent with the rate-limiting roles of the enzymes encoded by these genes reported from both experimental and modeling approaches. Therefore, the regulatory potential of the genes in a pathway may be inferred from their expression patterns. Furthermore, gene expression analysis in the context of a known pathway helps to categorize various biological perturbations that would not be recognized with the prevailing methods.

Arabidopsis↗

PubMed2003

Genotyping error detection through tightly linked markers.

The identification of genotyping errors is an important issue in mapping complex disease genes. Although it is common practice to genotype multiple markers in a candidate region in genetic studies, the potential benefit of jointly analyzing multiple markers to detect genotyping errors has not been investigated. In this article, we discuss genotyping error detections for a set of tightly linked markers in nuclear families, and the objective is to identify families likely to have genotyping errors at one or more markers. We make use of the fact that recombination is a very unlikely event among these markers. We first show that, with family trios, no extra information can be gained by jointly analyzing markers if no phase information is available, and error detection rates are usually low if Mendelian consistency is used as the only standard for checking errors. However, for nuclear families with more than one child, error detection rates can be greatly increased with the consideration of more markers. Error detection rates also increase with the number of children in each family. Because families displaying Mendelian consistency may still have genotyping errors, we calculate the probability that a family displaying Mendelian consistency has correct genotypes. These probabilities can help identify families that, although showing Mendelian consistency, may have genotyping errors. In addition, we examine the benefit of available haplotype frequencies in the general population on genotyping error detections. We show that both error detection rates and the probability that an observed family displaying Mendelian consistency has correct genotypes can be greatly increased when such additional information is available.

Family↗

PubMedDate not supplied

Methane emissions of rice increased by elevated carbon dioxide and temperature.

Methane (CH4) effluxes by paddy-culture rice (Oryza sativa L.) contribute about 16% of the total anthropogenic emissions. Since radiative forcing of CH4 at current atmospheric concentrations is 21 times greater on a per mole basis than that of carbon dioxide (CO2), it is imperative that the impact of global change on rice CH4 emissions be evaluated. Rice (cv. IR72) was planted in sunlit, closed-circulation, controlled-environment chambers in which CH4 efflux densities were measured daily. The CO2 concentration was maintained at either 330 or 660 micromol mol(-1). Air temperatures were controlled to daily maxima and minima of 32/23, 35/26, and 38/29 degrees C at each CO2 treatment. Emissions of CH4 each day were determined during a 4-h period after venting and resealing the chambers at 0800 h. Diurnal CH4 effluxes on 77, 98, and 119 d after planting (DAP) were obtained similarly at 4-h intervals. Emissions over four-plant hills and over flooded bare soil were measured at 53, 63, and 100 DAP. Emissions were negligible before 40 DAP. Thereafter, emissions were observed first in high-CO2, high-temperature treatments and reached a sustained maximum efflux density of about 7 mg m(-2) h(-1) (0.17 g m(-2) d(-1)) near the end of the growing season. Total seasonal CH4 emission was fourfold greater for high-CO2, high-temperature treatments than for the low-CO2, low-temperature treatment, probably due to more root sloughing or exudates, since about sixfold more acetate was found in the soil at 71 DAP. Both rising CO2 and increasing temperatures could lead to a positive feedback on global warming by increasing the emissions of CH4 from rice.

Air↗