Francisco S Domingues

Universität zu Lübeck, Lübeck Hansestadt, Schleswig-Holstein, Germany

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Publications (72)324.01 Total impact


  • No preview · Article · Jan 2016 · Parkinsonism & Related Disorders
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    ABSTRACT: Availability: The FamAgg package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg. Contact: Christian.Weichenberger@eurac.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    No preview · Article · Jan 2016 · Bioinformatics
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    ABSTRACT: During the last decade, a great number of extremely valuable large-scale genomics and proteomics datasets have become available to the research community. In addition, dropping costs for conducting high-throughput sequencing experiments and the option to outsource them considerably contribute to an increasing number of researchers becoming active in this field. Even though various computational approaches have been developed to analyze these data, it is still a laborious task involving prudent integration of many heterogeneous and frequently updated data sources, creating a barrier for interested scientists to accomplish their own analysis. We have implemented Dintor, a data integration framework that provides a set of over 30 tools to assist researchers in the exploration of genomics and proteomics datasets. Each of the tools solves a particular task and several tools can be combined into data processing pipelines. Dintor covers a wide range of frequently required functionalities, from gene identifier conversions and orthology mappings to functional annotation of proteins and genetic variants up to candidate gene prioritization and Gene Ontology-based gene set enrichment analysis. Since the tools operate on constantly changing datasets, we provide a mechanism to unambiguously link tools with different versions of archived datasets, which guarantees reproducible results for future tool invocations. We demonstrate a selection of Dintor’s capabilities by analyzing datasets from four representative publications. The open source software can be downloaded and installed on a local Unix machine. For reasons of data privacy it can be configured to retrieve local data only. In addition, the Dintor tools are available on our public Galaxy web service at http://dintor.eurac.edu. Dintor is a computational annotation framework for the analysis of genomic and proteomic datasets, providing a rich set of tools that cover the most frequently encountered tasks. A major advantage is its capability to consistently handle multiple versions of tool-associated datasets, supporting the researcher in delivering reproducible results.
    Preview · Article · Dec 2015 · BMC Genomics

  • No preview · Article · Dec 2015 · Vascular Pharmacology
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    ABSTRACT: The aims of the present study were to profile the expression of several candidate microRNAs (miRNAs) in blood from l-dopa-treated and drug-naive patients with Parkinson disease (PD) vs unaffected controls and to interpret the miRNA expression data in a biological context. We analyzed RNAs from peripheral blood of 36 l-dopa-treated, 10 drug-naive patients with PD and unaffected controls matched 1:1 by sex and age. We evaluated expression by reverse transcription-quantitative real-time PCR, and we analyzed data using a 2-tailed paired t test. To detect miRNA targets, several miRNA resources were combined to generate an overall score for each candidate gene using weighted rank aggregation. Significant overexpression of miR-103a-3p (p < 0.0001), miR-30b-5p (p = 0.002), and miR-29a-3p (p = 0.005) in treated patients with PD was observed, and promising candidate target genes for these were revealed by an integrated in silico analysis. We revealed 3 candidate biomarkers for PD. miRNAs 30b-5p and 29a-3p replicated a documented deregulation in PD albeit opposite to published data, while for miR-103a-3p, we demonstrated for the first time an overexpression in treated patients with PD. Expression studies in patients and/or in isolated peripheral blood mononuclear cells before and after l-dopa administration are necessary to define the involvement of l-dopa treatment in the observed overexpression. Our in silico analysis to prioritize targets of deregulated miRNAs identified candidate target genes, including genes related to neurodegeneration and PD. Despite the preliminary character of our study, the results provide a rationale for further clarifying the role of the identified miRNAs in the pathogenesis of PD and for validating their diagnostic potential. © 2015 American Academy of Neurology.
    No preview · Article · Jan 2015 · Neurology
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    ABSTRACT: Hepatitis C virus (HCV) is a major cause of chronic liver disease affecting around 130 million people worldwide. While great progress has been made to define the principle steps of the viral life cycle, detailed knowledge how HCV interacts with its host cells is still limited. To overcome this limitation we conducted a comprehensive whole-virus RNA interference-based screen and identified 40 host dependency and 16 host restriction factors involved in HCV entry/replication or assembly/release. Of these factors, heterogeneous nuclear ribonucleoprotein K (HNRNPK) was found to suppress HCV particle production without affecting viral RNA replication. This suppression of virus production was specific to HCV, independent from assembly competence and genotype, and not found with the related Dengue virus. By using a knock-down rescue approach we identified the domains within HNRNPK required for suppression of HCV particle production. Importantly, HNRNPK was found to interact specifically with HCV RNA and this interaction was impaired by mutations that also reduced the ability to suppress HCV particle production. Finally, we found that in HCV-infected cells, subcellular distribution of HNRNPK was altered; the protein was recruited to sites in close proximity of lipid droplets and colocalized with core protein as well as HCV plus-strand RNA, which was not the case with HNRNPK variants unable to suppress HCV virion formation. These results suggest that HNRNPK might determine efficiency of HCV particle production by limiting the availability of viral RNA for incorporation into virions. This study adds a new function to HNRNPK that acts as central hub in the replication cycle of multiple other viruses.
    Full-text · Article · Jan 2015 · PLoS Pathogens
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    ABSTRACT: Background An important aspect of studying the relationship between protein sequence, structure and function is the molecular characterization of the effect of protein mutations. To understand the functional impact of amino acid changes, the multiple biological properties of protein residues have to be considered together. Results Here, we present a novel visual approach for analyzing residue mutations. It combines different biological visualizations and integrates them with molecular data derived from external resources. To show various aspects of the biological information on different scales, our approach includes one-dimensional sequence views, three-dimensional protein structure views and two-dimensional views of residue interaction networks as well as aggregated views. The views are linked tightly and synchronized to reduce the cognitive load of the user when switching between them. In particular, the protein mutations are mapped onto the views together with further functional and structural information. We also assess the impact of individual amino acid changes by the detailed analysis and visualization of the involved residue interactions. We demonstrate the effectiveness of our approach and the developed software on the data provided for the BioVis 2013 data contest. Conclusions Our visual approach and software greatly facilitate the integrative and interactive analysis of protein mutations based on complementary visualizations. The different data views offered to the user are enriched with information about molecular properties of amino acid residues and further biological knowledge.
    Full-text · Article · Aug 2014 · BMC proceedings
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    ABSTRACT: Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting approximately 1-2% of the general population over age 60. It is characterized by a rather selective loss of dopaminergic neurons in the substantia nigra and the presence of α-synuclein-enriched Lewy body inclusions. Mutations in the Parkin gene (PARK2) are the major cause of autosomal recessive early-onset parkinsonism. The Parkin protein is an E3 ubiquitin ligase with various cellular functions, including the induction of mitophagy upon mitochondrial depolarizaton, but the full repertoire of Parkin-binding proteins remains poorly defined. Here we employed tandem affinity purification interaction screens with subsequent mass spectrometry to profile binding partners of Parkin. Using this approach for two different cell types (HEK293T and SH-SY5Y neuronal cells), we identified a total of 203 candidate Parkin-binding proteins. For the candidate proteins and the proteins known to cause heritable forms of parkinsonism, protein-protein interaction data were derived from public databases, and the associated biological processes and pathways were analyzed and compared. Functional similarity between the candidates and the proteins involved in monogenic parkinsonism was investigated, and additional confirmatory evidence was obtained using published genetic interaction data from Drosophila melanogaster. Based on the results of the different analyses, a prioritization score was assigned to each candidate Parkin-binding protein. Two of the top ranking candidates were tested by co-immunoprecipitation, and interaction to Parkin was confirmed for one of them. New candidates for involvement in cell death processes, protein folding, the fission/fusion machinery, and the mitophagy pathway were identified, which provide a resource for further elucidating Parkin function.
    Full-text · Article · Nov 2013 · PLoS ONE
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    Dataset: Figure S1
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Choice of sphere radius and Gaussian smoothing parameters. Black histograms represent the distribution of the number of residues included in proximities of a radius indicated on the corresponding plot on the left. Red histograms illustrate the sum of Gaussian normalizing factor per each residue. Mean with variance in brackets of each distribution are indicated in legends. (TIFF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S4
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Correlation of features in the initial feature set. Histograms show distribution of the Pearson correlation of all features of the structural descriptor (left panel), of the features of the clonal model (middle panel) and of the features of the clonal model with the remaining features of the structural descriptor (right panel). Median, percentage of feature pair with correlation >0.5 and >0.75 are indicated in the legend. (TIFF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S9
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Side-chains of the V3 loop in the unbound (A, structure 2B4C) and bound (B, structure 2QAD) conformation. In the bound conformation the residues of CS1 (304 and 307) and CS2 (319–321) are closely located and form bonds between two sides of the loop stem. (TIF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S10
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Clusters of selected features mapped on the 2B4C structure. (TIF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S7
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Effect of indels on the prediction accuracy of the clonal model. The curves illustrate the prediction performance of the clonal model based on a dataset containing only sequences with indels (black curve) and only sequences with indels (red curve). Similar performance of the clonal model based on both datasets suggests there is a limited effect of the presence of indels on the model accuracy. (TIF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S14
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Separation of amino acid indices into 12 clusters – the separation that showed the largest silhouette value. (TIFF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S5
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Comparison of the clonal and g2p models in the precision-recall space. The curves show the relationship between true positive rate (recall) and positive predictive value (precision). Area under the curve shows a higher predictive performance of the clonal model compared to the g2p model. (TIFF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S12
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: V3 residue numbering. The numbering of V3 residues used in this manuscript is shown on the 2B4C structure. Top numbers indicate residue position within V3 loop, bottom numbers are assigned according to HXBc2, a numbering used also in the 2B4C annotation [18]. Figure from [21]. (TIFF)
    Preview · Dataset · Mar 2013
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    Dataset: Text S2
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Overlap of features selected by different feature selection methods. (PDF)
    Preview · Dataset · Mar 2013
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    Dataset: Figure S3
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Distance on the 3D structure of features selected by different feature selection methods. Plot in D illustrates the overall distance of spheres of the features of the initial feature set. Plots in A–C illustrate the distance of the highly correlated features as defined above. The highly correlated features can be found among features selected by different methods and they pertain to locations in close proximity on the structure, which is the potential reason for the low overlap of features selected by different methods. (TIFF)
    Preview · Dataset · Mar 2013
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    Dataset: Table S3
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Therapy outcome prediction using g2p model. (XLS)
    Preview · Dataset · Mar 2013
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    Dataset: Table S2
    Katarzyna Bozek · Thomas Lengauer · Saleta Sierra · Rolf Kaiser · Francisco S. Domingues
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    ABSTRACT: Therapy outcome prediction using structure-based model. (XLS)
    Preview · Dataset · Mar 2013

Publication Stats

3k Citations
324.01 Total Impact Points

Institutions

  • 2013-2016
    • Universität zu Lübeck
      Lübeck Hansestadt, Schleswig-Holstein, Germany
  • 2003-2011
    • Max Planck Institute for Informatics
      • Department 3: Computational Biology and Applied Algorithmics
      Saarbrücken, Saarland, Germany
  • 2007
    • Universität des Saarlandes
      Saarbrücken, Saarland, Germany
  • 1997-2002
    • University of Salzburg
      • Center for Applied Molecular Engineering
      Salzburg, Salzburg, Austria