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Characterization of the retinal proteome during rod photoreceptor genesis

BMC Research Notes 2010年第1期3卷 1-8页

作者： Barnhill, Alison E Hecker, Laura A Kohutyuk, Oksana Buss, Janice E Honavar, Vasant G Greenlee, Heather West Interdepartmental Neuroscience Program Iowa State University Ames IA United States Department of Biomedical Sciences Iowa State University Ames IA United States Bioinformatics and Computational Biology Program Iowa State University Ames IA United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA United States Department of Computer Science Iowa State University Ames IA United States National Animal Disease Center Ames IA 50010 United States Mayo Clinic Department of Ophthalmology Rochester MN 55905 United States

Background. The process of rod photoreceptor genesis, cell fate determination and differentiation is complex and multi-factorial. Previous studies have defined a model of photoreceptor differentiation that relies on intrinsic changes within the presumptive photoreceptor cells as well as changes in surrounding tissue that are extrinsic to the cell. We have used a proteomics approach to identify proteins that are dynamically expressed in the mouse retina during rod genesis and differentiation. Findings. A series of six developmental ages from E13 to P5 were used to define changes in retinal protein expression during rod photoreceptor genesis and early differentiation. Retinal proteins were separated by isoelectric focus point and molecular weight. Gels were analyzed for changes in protein spot intensity across developmental time. Protein spots that peaked in expression at E17, P0 and P5 were picked from gels for identification. There were 239 spots that were picked for identification based on their dynamic expression during the developmental period of maximal rod photoreceptor genesis and differentiation. Of the 239 spots, 60 of them were reliably identified and represented a single protein. Ten proteins were represented by multiple spots, suggesting they were post-translationally modified. Of the 42 unique dynamically expressed proteins identified, 16 had been previously reported to be associated with the developing retina. Conclusions. Our results represent the first proteomics study of the developing mouse retina that includes prenatal development. We identified 26 dynamically expressed proteins in the developing mouse retina whose expression had not been previously associated with retinal development. © 2010 Greenlee et al.;licensee BioMed Central Ltd.

关键词： Protein Spot Mouse Retina Retinal Development Retinal Protein Probability Base Mowse Score

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Analysis of cancer omics data in a semantic web framework

Analysis of cancer omics data in a semantic web framework

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Workshop on Semantic Web Applications and Tools for Life Sciences 2010, SWAT4LS 2010

作者： Holford, Matthew E. McCusker, James P. Cheung, Kei-Hoi Krauthammer, Michael Interdepartmental Program in Computational Biology and Bioinformatics Yale University New Haven CT United States Department of Pathology Yale University New Haven CT United States Department of Computer Science Yale University New Haven CT United States Center for Medical Informatics Yale University New Haven CT United States Department of Genetics Yale University New Haven CT United States

Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell's molecular state and its response to anti-cancer therapy. To study the problem, we have previously focused on data warehousing technologies and statistical data integration. In this paper, we present recent work on extending our analytical capabilities using Semantic Web technology. A key new component presented here is a SPARQL endpoint to our existing data warehouse. This endpoint allows the merging of observed quantitative data with existing data from semantic knowledge sources such as Gene Ontology (GO). We show how such variegated quantitative and functional data can be integrated and accessed in a universal manner using Semantic Web tools. We also demonstrate how Description Logic (DL) reasoning can be used to infer previously unstated conclusions from existing knowledge bases. As proof of concept, we illustrate the ability of our setup to answer complex queries on resistance of cancer cells to Decitabine, a demethylating agent.

关键词： Semantic Web

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Multistate modeling and simulation for regulatory networks 10

Multistate modeling and simulation for regulatory networks

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Simulation Winter Conference

作者： Zhen Liu Umme Juka Mobassera Clifford A. Shaffer Layne T. Watson Yang Cao Department of Computer Science Virginia Technology Blacksburg VA USA Program in Genetics Bioinformatics and Computational Biology Virginia Technology Blacksburg VA USA Department of Computer Science Department of Mathematics Virginia Technology Blacksburg VA USA

ISBN: (纸本)9781424498642

Many protein regulatory models contain chemical species best represented as having multiple states. Such models stem from the potential for multiple levels of phosphorylation or from the formation of multiprotein complexes. We seek to support such models by augmenting an existing modeling and simulation system. Interactions between multistate species can lead to a combinatorial explosion in the potential state space. This creates a challenge when using Gillespie's stochastic simulation algorithm (SSA). Both the network-free algorithm (NFA) and various rules-based methods have been proposed to more efficiently simulate such models. We show how to further improve NFA to integrate population-based and particle-based features. We then present a population-based scheme for the stochastic simulation of rule-based models. A complexity analysis is presented comparing the proposed simulation methods. We present numerical experiments for two sample models that demonstrate the power of the proposed simulation methods.

关键词： Mathematical model Biological system modeling Numerical models Chemicals Stochastic processes Equations Proteins

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Computing H/D-Exchange rates of single residues from data of proteolytic fragments

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BMC bioinformatics 2010年第1期11卷 1-12页

作者： Althaus, Ernst Canzar, Stefan Ehrler, Carsten Emmett, Mark R. Karrenbauer, Andreas Marshall, Alan G. Meyer-Bäse, Anke Tipton, Jeremiah D. Zhang, Hui-Min Institut für Informatik Fachbereich 08 Staudingerweg 9 55099 Mainz Germany Algorithmic Computational Biology Centrum Wiskunde and Informatica Amsterdam Netherlands Center for Bioinformatics Computer Science Department Saarland University 66041 Saarbrücken Germany Ion Cyclotron Resonance Program National High Magnetic Field Laboratory Florida State University 1800 East Paul Dirac Drive Tallahassee FL 32310-4005 United States Department of Chemistry and Biochemistry Florida State University 95 Chieftain Way Tallahassee FL 32306 United States Institute of Mathematics EPFL Station 8 1015 Lausanne Switzerland Department of Scientific Computing Florida State University Tallahassee FL 32306-4120 United States

Background: Protein conformation and protein/protein interaction can be elucidated by solution-phase Hydrogen/Deuterium exchange (sHDX) coupled to high-resolution mass analysis of the digested protein or protein complex. In sHDX experiments mutant proteins are compared to wild-type proteins or a ligand is added to the protein and compared to the wild-type protein (or mutant). The number of deuteriums incorporated into the polypeptides generated from the protease digest of the protein is related to the solvent accessibility of amide protons within the original protein ***: In this work, sHDX data was collected on a 14.5 T FT-ICR MS. An algorithm was developed based on combinatorial optimization that predicts deuterium exchange with high spatial resolution based on the sHDX data of overlapping proteolytic fragments. Often the algorithm assigns deuterium exchange with single residue ***: With our new method it is possible to automatically determine deuterium exchange with higher spatial resolution than the level of digested fragments. © 2010 Althaus et al;licensee BioMed Central Ltd.

关键词： Proteins

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Genetic correlates of autoreactivity and autoreactive potential in human Ig heavy chains

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Immunome Research 2009年第1期5卷 1-8页

作者： Volpe, Joseph M Kepler, Thomas B Center for Computational Immunology Duke University Durham NC United States Departments of Biostatistics and Bioinformatics and Immunology Duke University Medical Center Durham NC United States Computational Biology and Bioinformatics Graduate Program Institute for Genome Sciences and Policy Duke University Durham NC United States

Background. Immature bone marrow B cells are known to have longer CDR3 than mature peripheral B cells, and this genetic characteristic has been shown to correlate with autoreactivity in these early cells. B-cell Central tolerance eliminates these cells, but it is known that autoreactive B cells nevertheless appear commonly in healthy human blood. We examined over 7,300 Ig genes from Genbank, including those annotated by their discoverers as associated with autoreactivity, to determine the genetic correlates of autoreactivity in mature B cells. Results. We find differential biases in gene segment usage and higher mutation frequency in autoreactivity-associated Ig genes, but the CDR3 lengths do not differ between autoreactive and non-autoreactive Ig genes. The most striking genetic signature of autoreactivity is an increase in the proportion of N-nucleotides relative to germline-encoded nucleotides in CDR3 from autoreactive genes. Conclusion. We hypothesize that peripheral autoreactivity results primarily from somatic mutation, and that the genetic correlates of autoreactivity in mature B-cells are not the same as those for autoreactivity in immature B cells. What is seen in mature autoreactive B cells are the correlates of autoreactive potential, not of autoreactivity per se. The autoreactive potential is higher for V(D)J rearrangements encoded to a large extent by N-nucleotides rather than by the gene segments that, we posit, have been selected in germline evolution for their suppression of autoreactive potential.

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An approach to comparing tiling array and high throughput sequencing technologies for genomic transcript mapping

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BMC Research Notes 2009年第1期2卷 1-7页

作者： Sasidharan, Rajkumar Agarwal, Ashish Rozowsky, Joel Gerstein, Mark Molecular Biophysics and Biochemistry Department Yale University New Haven CT 06520 United States Department of Plant Biology Carnegie Institution for Science Stanford CA 94305 United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 United States Department of Computer Science Yale University New Haven CT 06520 United States

Background. There are two main technologies for transcriptome profiling, namely, tiling microarrays and high-throughput sequencing. Recently there has been a tremendous amount of excitement about the latter because of the advent of next-generation sequencing technologies and its promises. Consequently, the question of the moment is how these two technologies compare. Here we attempt to develop an approach to do a fair comparison of transcripts identified from tiling microarray and MPSS sequencing data. Findings. This comparison is a challenging task because the sequencing data is discrete while the tiling array data is continuous. We use the published rice and Arabidopsis datasets which provide currently best matched sets of arrays and sequencing experiments using a slightly earlier generation of sequencing, the MPSS tag sequencing technology. After scoring the arrays consistently in both the organisms, a first pass comparison reveals a surprisingly small overlap in transcripts of 22% and 66% respectively, in rice and Arabidopsis. However, when we do the analysis in detail, we find that this is an underestimate. In particular, when we map the probe intensities onto the sequencing tags and then look at their intensity distribution, we see that they are very similar to exons. Furthermore, restricting our comparison to only protein-coding gene loci revealed a very good overlap between the two technologies. Conclusion. Our approach to compare genome tiling microarray and MPSS sequencing data suggests that there is actually a reasonable overlap in transcripts identified by the two technologies. This overlap is distorted by the scoring and thresholding in the tiling array scoring procedure. © 2009 Sasidharan et al;licensee BioMed Central Ltd.

关键词： Tiling Array Transcript Mapping Tile Path Tiling Microarray Intergenic Transcript

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A pathway analysis applied to Genetic Analysis Workshop 16 genome-wide rheumatoid arthritis data

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BMC proceedings 2009年第7期3 Suppl 7卷 S91页

作者： David H Ballard Chatchawit Aporntewan Ji Young Lee Joon Sang Lee Zheyang Wu Hongyu Zhao Program in Computational Biology and Bioinformatics Yale University 300 George Street Suite 503 New Haven Connecticut 06511 USA. david.ballard@yale.edu.

The identification of several hundred genomic regions affecting disease risk has proven the ability of genome-wide association studies have proven their ability to identify genetic contributors to disease. Currently, single-nucleotide polymorphism (SNP) association analysis is the most widely used method of genome-wide association data, but recent research shows that multi-marker tests of association may provide greater power, especially when more than one mutation is present within a gene and the mutations are in low linkage disequilibrium with each other. Here we use a multi-marker association test based on regression to SNPs located within known genes to obtain a gene-level score of association. We then perform pathway analysis using this score as a measure of gene importance. We use two tests of pathway enrichment - a binomial test and a random set method. By utilizing publicly available gene and pathway information, we identify B cell, cytokine and inflammation response, and antigen presentation pathways as being associated with rheumatoid arthritis. These results confirm known biological mechanisms for auto-immunity disorders, of which rheumatoid arthritis is one.

关键词： Rheumatoid Arthritis Major Histocompatibility Complex Major Histocompatibility Complex Class Binomial Test Gene Score

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Article Commentary: Snapshots of Tree Space

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Evolutionary bioinformatics 2009年 5卷

作者： Wang, Zheng López-Giréidez, Francesc Townsend, Jeffrey P. Department of Ecology and Evolutionary Biology Yale University New Haven 06520 CT United States Program in Computational Biology and Bioinformatics Yale University New Haven 06520 CT United States

Achievement of the best balance between the accuracy and efficiency is always an important issue when searching a tree space of large data sets. In the 5th issue in 2009, Rodrigo et al used bootstrapped topologies as fixed genealogies to distribute an MCMC analysis across a cluster of computers, resulting in an efficiency yielding results 37 times faster than in the standard MCMC methods. Tree searches can seldom be guided with certainty, so that such snapshots sampling partial but “more-likely” tree space facilitated by parallel programs on computer clusters may provide great promise among a few choices that are computationally affordable when tree space is large and complicated. © 2009 SAGE Publications.

关键词： computer cluster large phylogeny tree sampling

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Francisella tularensis subsp. novicida isolated from a human in Arizona

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BMC Research Notes 2009年第1期2卷 1-6页

作者： Birdsell, Dawn N Stewart, Tasha Vogler, Amy J Lawaczeck, Elisabeth Diggs, Alisa Sylvester, Tammy L Buchhagen, Jordan L Auerbach, Raymond K Keim, Paul Wagner, David M Center for Microbial Genetics and Genomics Northern Arizona University Flagstaff AZ 86011-4073 United States Maricopa County Department of Public Health Phoenix AZ 85012 United States Arizona Department of Health Services Phoenix AZ 85007 United States Translational Genomics Research Institute Phoenix AZ 85004 United States Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 United States

Background. Francisella tularensis is the etiologic agent of tularemia and is classified as a select agent by the Centers for Disease Control and Prevention. Currently four known subspecies of F. tularensis that differ in virulence and geographical distribution are recognized:tularensis (type A), holarctica (type B), mediasiatica, and novicida. Because of the Select Agent status and differences in virulence and geographical location, the molecular analysis of any clinical case of tularemia is of particular interest. We analyzed an unusual Francisella clinical isolate from a human infection in Arizona using multiple DNA-based approaches. Findings. We report that the isolate is F. tularensis subsp. novicida, a subspecies that is rarely isolated. Conclusion. The rarity of this novicida subspecies in clinical settings makes each case study important for our understanding of its role in disease and its genetic relationship with other F. tularensis subspecies. © 2009 Wagner et al;licensee BioMed Central Ltd.

关键词： Clinical Isolate Coccidioidomycosis Tularemia Francisella Tularensis Tularensis Subsp

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Multiple Routes to Characterize the Folding of a Small DNA Hairpin†

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Angewandte Chemie 2010年第42期122卷

作者： Guillem Portella Modesto Orozco Joint IRB‐BSC Research Program in Computational Biology Institute for Research in Biomedicine (IRB) Josep Samitier 1‐5 Barcelona 08028 (Spain) Barcelona Supercomputing Centre (BSC) Jordi Girona 29 Barcelona 08034 (Spain) Departament de Bioquímica i Biología Molecular Facultat de Biología Universitat de Barcelona Avgda Diagonal 645 Barcelona 08028 (Spain) National Institute of Bioinformatics Parc Científic de Barcelona Josep Samitier 1–5 Barcelona 08028 (Spain)

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