DAVID-WS: a stateful web service to facilitate gene/protein list analysis

Summary: The database for annotation, visualization and integrated discovery (DAVID), which can be freely accessed at http://david.abcc.ncifcrf.gov/, is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins. It has been used by researchers from more than 5000 institutes worldwide, with a daily submission rate of ∼1200 gene lists from ∼400 unique researchers, and has been cited by more than 6000 scientific publications. However, the current web interface does not support programmatic access to DAVID, and the uniform resource locator (URL)-based application programming interface (API) has a limit on URL size and is stateless in nature as it uses URL request and response messages to communicate with the server, without keeping any state-related details. DAVID-WS (web service) has been developed to automate user tasks by providing stateful web services to access DAVID programmatically without the need for human interactions

FIVA:Functional Information Viewer and Analyzer extracting biological knowledge from transcriptome data of prokaryotes

FIVA (Function Information Viewer and Analyzer) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software assists in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes.

PGS: a tool for association study of high-dimensional microRNA expression data with repeated measures

Motivation: MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Due to interested in the dynamic nature of the miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNAs expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time. However, the commonly used site-by-site multiple testing may impair the value of repeated or multiple measures data by ignoring the inherent dependent structure, which lead to problems including underpowered results after multiple comparison correction using false discovery rate (FDR) estimation and less biologically meaningful results. Hence, new methods are needed to tackle these issues. Results: We propose a penalized regression model incorporating grid search method (PGS), for analyzing association study of high-dimensional microRNA expression data with repeated measures. The development of this analytical framework was motivated by a real-world miRNA dataset. Comparisons between PGS and the site-by-site testing revealed that PGS provided smaller phenotype prediction errors and higher enrichment of phenotype-related biological pathways than the site-by-site testing. Simulation study showed that PGS provided more accurate estimates and higher sensitivity than site-by-site testing with comparable specificities. Availability: R source code for PGS algorithm, implementation example, and simulation study are available for download at https://github.com/feizhe/PGS

A High Statistics Measurement of the Lambdac+ Lifetime

A high statistics measurement of the Lambdac+ lifetime from the Fermilab fixed-target FOCUS photoproduction experiment is presented. We describe the analysis technique with particular attention to the determination of the systematic uncertainty. The measured value of 204.6 +/- 3.4 (stat.) +/- 2.5 (syst.) fs from 8034 +/- 122 Lambdac -> pKpi decays represents a significant improvement over the present world average.Comment: Submitted to Physical Review Letter

Evidence for a narrow dip structure at 1.9 GeV/c2^2 in 3π+3π−3\pi^+ 3\pi^- diffractive photoproduction

A narrow dip structure has been observed at 1.9 GeV/c$^2$ in a study of diffractive photoproduction of the $~3\pi^+3\pi^-$ final state performed by the Fermilab experiment E687.Comment: The data of Figure 6 can be obtained by downloading the raw data file e687_6pi.txt. v5 (2nov2018): added Fig. 7, the 6 pion energy distribution as requested by a reade

New FOCUS results on charm mixing and CP violation

We present a summary of recent results on CP violation and mixing in the charm quark sector based on a high statistics sample collected by photoproduction experiment FOCUS (E831 at Fermilab). We have measured the difference in lifetimes for the $D^0$ decays: $D^0 \to K^-\pi^+$ and $D^0 \to K^-K^+$. This translates into a measurement of the $y_{CP}$ mixing parameter in the \d0d0 system, under the assumptions that $K^-K^+$ is an equal mixture of CP odd and CP even eigenstates, and CP violation is negligible in the neutral charm meson system. We verified the latter assumption by searching for a CP violating asymmetry in the Cabibbo suppressed decay modes $D^+ \to K^-K^+\pi^+$, $D^0 \to K^-K^+$ and $D^0 \to \pi^-\pi^+$. We show preliminary results on a measurement of the branching ratio $\Gamma(D^{*+}\to \pi^+ (K^+\pi^-))/\Gamma(D^{*+}\to \pi^+ (K^-\pi^+))$.Comment: 9 pages, 6 figures, requires espcrc2.sty. Presented by S.Bianco at CPConf2000, September 2000, Ferrara (Italy). In this revision, fixed several stylistic flaws, add two significant references, fixed a typo in Tab.

A measurement of branching ratios of D+D^+ and Ds+D^+_s hadronic decays to four-body final states containing a KSK_S

We have studied hadronic four-body decays of $D^+$ and $D^+_s$ mesons with a $K_S$ in the final state using data recorded during the 1996-1997 fixed-target run at Fermilab high energy photoproduction experiment FOCUS. We report a new branching ratio measurement of $\Gamma(D^+\to K_S K^-\pi^+\pi^+)/\Gamma(D^+\to K_S \pi^+\pi^+\pi^-)=0.0768\pm0.0041\pm0.0032$. We make the first observation of three new decay modes with branching ratios $\Gamma(D^+\to K_S K^+\pi^+\pi^-)/\Gamma(D^+\to K_S \pi^+\pi^+\pi^-)=0.0562\pm0.0039\pm0.0040$, \Gamma(D^+\to\K_S K^+ K^-\pi^+)/\Gamma(D^+\to K_S \pi^+\pi^+\pi^-)=0.0077\pm0.0015\pm0.0009, and $\Gamma(D^+_s\to K_S K^+\pi^+\pi^-)/\Gamma(D^+_s\to K_S K^-\pi^+\pi^+)=0.586\pm0.052\pm0.043$, where in each case the first error is statistical and the second error is systematic.Comment: 4 pages, 1 table, 2 figures, submitted to Physical Review Letter

A Measurement of the Ds+ Lifetime

A high statistics measurement of the Ds+ lifetime from the Fermilab fixed-target FOCUS photoproduction experiment is presented. We describe the analysis of the two decay modes, Ds+ -> phi(1020)pi+ and Ds+ -> \bar{K}*(892)0K+, used for the measurement. The measured lifetime is 507.4 +/- 5.5 (stat.) +/- 5.1 (syst.) fs using 8961 +/- 105 Ds+ -> phi(1020)pi+ and 4680 +/- 90 Ds+ -> \bar{K}*(892)0K+ decays. This is a significant improvement over the present world average.Comment: 5 pages, 3 figures, 2 tables, submitted to PR

Search for CP violation in D0 and D+ decays

A high statistics sample of photoproduced charm particles from the FOCUS (E831) experiment at Fermilab has been used to search for CP violation in the Cabibbo suppressed decay modes D+ to K-K+pi+, D0 to K-K+ and D0 to pi-pi+. We have measured the following CP asymmetry parameters: A_CP(K-K+pi+) = +0.006 +/- 0.011 +/- 0.005, A_CP(K-K+) = -0.001 +/- 0.022 +/- 0.015 and A_CP(pi-pi+) = +0.048 +/- 0.039 +/- 0.025 where the first error is statistical and the second error is systematic. These asymmetries are consistent with zero with smaller errors than previous measurements.Comment: 12 pages, 4 figure

Classification of microarray data using gene networks

BACKGROUND: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation. RESULTS: We propose a method to integrate a priori the knowledge of a gene network in the analysis of gene expression data. The approach is based on the spectral decomposition of gene expression profiles with respect to the eigenfunctions of the graph, resulting in an attenuation of the high-frequency components of the expression profiles with respect to the topology of the graph. We show how to derive unsupervised and supervised classification algorithms of expression profiles, resulting in classifiers with biological relevance. We illustrate the method with the analysis of a set of expression profiles from irradiated and non-irradiated yeast strains. CONCLUSION: Including a priori knowledge of a gene network for the analysis of gene expression data leads to good classification performance and improved interpretability of the results