Brian D. Athey

Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data

Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals ∼30–50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.

The end-to-end performance effects of parallel TCP sockets on a lossy wide-area network

This paper examines the effects of using parallel TCP flows to improve end-to-end network performance for distributed data intensive applications. A series of transmission experiments were conducted over a wide-area network to assess how parallel flows improve throughput, and to understand the number of flows necessary to improve throughput while avoiding congestion. An empirical throughput expression for parallel flows based on experimental data is presented, and guidelines for the use of parallel flows are discussed.

Chromatin fibers are left-handed double helices with diameter and mass per unit length that depend on linker length.

Four classes of models have been proposed for the internal structure of eukaryotic chromosome fibers--the solenoid, twisted-ribbon, crossed-linker, and superbead models. We have collected electron image and x-ray scattering data from nuclei, and isolated chromatin fibers of seven different tissues to distinguish between these models. The fiber diameters are related to the linker lengths by the equation: D(N) = 19.3 + 0.23 N, where D(N) is the external diameter (nm) and N is the linker length (base pairs). The number of nucleosomes per unit length of the fibers is also related to linker length. Detailed studies were done on the highly regular chromatin from erythrocytes of Necturus (mud puppy) and sperm of Thyone (sea cucumber). Necturus chromatin fibers (N = 48 bp) have diameters of 31 nm and have 7.5 +/- 1 nucleosomes per 10 nm along the axis. Thyone chromatin fibers (N = 87 bp) have diameters of 39 nm and have 12 +/- 2 nucleosomes per 10 nm along the axis. Fourier transforms of electron micrographs of Necturus fibers showed left-handed helical symmetry with a pitch of 25.8 +/- 0.8 nm and pitch angle of 32 +/- 3 degrees, consistent with a double helix. Comparable conclusions were drawn from the Thyone data. The data do not support the solenoid, twisted-ribbon, or supranucleosomal particle models. The data do support two crossed-linker models having left-handed double-helical symmetry and conserved nucleosome interactions.

Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data

MOTIVATION Metabolomics is a rapidly evolving field that holds promise to provide insights into genotype-phenotype relationships in cancers, diabetes and other complex diseases. One of the major informatics challenges is providing tools that link metabolite data with other types of high-throughput molecular data (e.g. transcriptomics, proteomics), and incorporate prior knowledge of pathways and molecular interactions. RESULTS We describe a new, substantially redesigned version of our tool Metscape that allows users to enter experimental data for metabolites, genes and pathways and display them in the context of relevant metabolic networks. Metscape 2 uses an internal relational database that integrates data from KEGG and EHMN databases. The new version of the tool allows users to identify enriched pathways from expression profiling data, build and analyze the networks of genes and metabolites, and visualize changes in the gene/metabolite data. We demonstrate the applications of Metscape to annotate molecular pathways for human and mouse metabolites implicated in the pathogenesis of sepsis-induced acute lung injury, for the analysis of gene expression and metabolite data from pancreatic ductal adenocarcinoma, and for identification of the candidate metabolites involved in cancer and inflammation. AVAILABILITY Metscape is part of the National Institutes of Health-supported National Center for Integrative Biomedical Informatics (NCIBI) suite of tools, freely available at http://metscape.ncibi.org. It can be downloaded from http://cytoscape.org or installed via Cytoscape plugin manager. CONTACT metscape-help@umich.edu; akarnovs@umich.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Monocyte-endothelial adhesion in chronic rheumatoid arthritis. In situ detection of selectin and integrin-dependent interactions.

Blood monocytes are the principal reservoir for tissue macrophages in rheumatoid synovitis. Receptor-mediated adhesive interactions between circulating cells and the synovial venules initiate recruitment. These interactions have been studied primarily in cultured endothelial cells. Thus the functional activities of specific adhesion receptors, such as the endothelial selectins and the leukocytic integrins, have not been evaluated directly in diseased tissues. We therefore examined monocyte-microvascular interactions in rheumatoid synovitis by modifying the Stamper-Woodruff frozen section binding assay initially developed to study lymphocyte homing. Specific binding of monocytes to venules lined by low or high endothelium occurred at concentrations as low as 5 x 10(5) cells/ml. mAbs specific for P-selectin (CD62, GMP-140/PADGEM) blocked adhesion by > 90% in all synovitis specimens examined. In contrast, P-selectin-mediated adhesion to the microvasculature was either lower or absent in frozen sections of normal foreskin and placenta. mAbs specific for E-selectin (ELAM-1) blocked 20-50% of monocyte attachment in several RA synovial specimens but had no effect in others. mAbs specific for LFA-1, Mo1/Mac 1, the integrin beta 2-chain, and L-selectin individually inhibited 30-40% of adhesion. An mAb specific for the integrin beta 1-chain inhibited the attachment of elutriated monocytes up to 20%. We conclude that P-selectin associated with the synovial microvasculature initiates shear-resistant adhesion of monocytes in the Stamper-Woodruff assay and stabilizes bonds formed by other selectins and the integrins. Thus the frozen section binding assay permits direct evaluation of leukocyte-microvascular adhesive interactions in inflamed tissues and suggests a prominent role for P-selectin in monocyte recruitment in vivo.

ConceptGen: a gene set enrichment and gene set relation mapping tool

MOTIVATION The elucidation of biological concepts enriched with differentially expressed genes has become an integral part of the analysis and interpretation of genomic data. Of additional importance is the ability to explore networks of relationships among previously defined biological concepts from diverse information sources, and to explore results visually from multiple perspectives. Accomplishing these tasks requires a unified framework for agglomeration of data from various genomic resources, novel visualizations, and user functionality. RESULTS We have developed ConceptGen, a web-based gene set enrichment and gene set relation mapping tool that is streamlined and simple to use. ConceptGen offers over 20,000 concepts comprising 14 different types of biological knowledge, including data not currently available in any other gene set enrichment or gene set relation mapping tool. We demonstrate the functionalities of ConceptGen using gene expression data modeling TGF-beta-induced epithelial-mesenchymal transition and metabolomics data comparing metastatic versus localized prostate cancers.

Michigan Molecular Interactions (MiMI): putting the jigsaw puzzle together

Protein interaction data exists in a number of repositories. Each repository has its own data format, molecule identifier and supplementary information. Michigan Molecular Interactions (MiMI) assists scientists searching through this overwhelming amount of protein interaction data. MiMI gathers data from well-known protein interaction databases and deep-merges the information. Utilizing an identity function, molecules that may have different identifiers but represent the same real-world object are merged. Thus, MiMI allows the users to retrieve information from many different databases at once, highlighting complementary and contradictory information. To help scientists judge the usefulness of a piece of data, MiMI tracks the provenance of all data. Finally, a simple yet powerful user interface aids users in their queries, and frees them from the onerous task of knowing the data format or learning a query language. MiMI allows scientists to query all data, whether corroborative or contradictory, and specify which sources to utilize. MiMI is part of the National Center for Integrative Biomedical Informatics (NCIBI) and is publicly available at: .

Subcellular optochemical nanobiosensors: probes encapsulated by biologically localised embedding (PEBBLEs)

Abstract Described here are arguably the worlds smallest stand-alone devices/sensors, consisting of multicomponent nano-spheres with radii as small as 10 nm, occupying ≈1 ppb of a typical mammalian cell’s volume. The probe is prepared from up to seven ingredients and is optimised for selective and reversible analyte detection, as well as sensor stability and reproducibility. Such a sensor probe encapsulated by biologically localised embedding (PEBBLE), is delivered into a cell by a variety of minimally-invasive techniques, including a pico-injector, a gene gun, liposomal incorporation and natural ingestion. These remote nano-optodes (PEBBLEs) have been prepared for pH, calcium, magnesium, potassium and oxygen. The sensor PEBBLEs can be inserted into a cell individually, in clusters (single analyte), in sets (multi-analyte) or in ensembles (single analyte, multiple locations).

Michigan molecular interactions r2: from interacting proteins to pathways.

Molecular interaction data exists in a number of repositories, each with its own data format, molecule identifier and information coverage. Michigan molecular interactions (MiMI) assists scientists searching through this profusion of molecular interaction data. The original release of MiMI gathered data from well-known protein interaction databases, and deep merged this information while keeping track of provenance. Based on the feedback received from users, MiMI has been completely redesigned. This article describes the resulting MiMI Release 2 (MiMIr2). New functionality includes extension from proteins to genes and to pathways; identification of highlighted sentences in source publications; seamless two-way linkage with Cytoscape; query facilities based on MeSH/GO terms and other concepts; approximate graph matching to find relevant pathways; support for querying in bulk; and a user focus-group driven interface design. MiMI is part of the NIHs; National Center for Integrative Biomedical Informatics (NCIBI) and is publicly available at: http://mimi.ncibi.org.

Improving throughput and maintaining fairness using parallel TCP

Applications that require good network performance often use parallel TCP streams and TCP modifications to improve the effectiveness of TCP. If the network bottleneck is fully utilized, this approach boosts throughput by unfairly stealing bandwidth from competing TCP streams. Improving the effectiveness of TCP is easy, but improving effectiveness while maintaining fairness is difficult. In this paper, we describe an approach we implemented that uses a long virtual round trip time in combination with parallel TCP streams to improve effectiveness on underutilized networks. Our approach prioritizes fairness at the expense of effectiveness when the network is fully utilized. We compared our approach with standard parallel TCP over a wide-area network, and found that our approach preserves effectiveness and is fairer to competing traffic than standard parallel TCP.