GLORIA

GEOMAR Library Ocean Research Information Access

X
feed icon rss

Ihre E-Mail wurde erfolgreich gesendet. Bitte prüfen Sie Ihren Maileingang.

Leider ist ein Fehler beim E-Mail-Versand aufgetreten. Bitte versuchen Sie es erneut.

Vorgang fortführen?

Exportieren
  • 1
    facet.materialart.
    Unbekannt
    Design, implementation and practice of JBEI-ICE: an open source biological part registry platform and tools (2012)
    Oxford University Press
    Details
    Publikationsdatum: 2012-10-10
    Beschreibung: The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 2
    facet.materialart.
    Unbekannt
    Characterizing RNA ensembles from NMR data with kinematic models (2014)
    Oxford University Press
    Details
    Publikationsdatum: 2014-09-02
    Beschreibung: Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem–loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention.
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 3
    facet.materialart.
    Unbekannt
    Epidaurus: aggregation and integration analysis of prostate cancer epigenome (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-01-24
    Beschreibung: Integrative analyses of epigenetic data promise a deeper understanding of the epigenome. Epidaurus is a bioinformatics tool used to effectively reveal inter-dataset relevance and differences through data aggregation, integration and visualization. In this study, we demonstrated the utility of Epidaurus in validating hypotheses and generating novel biological insights. In particular, we described the use of Epidaurus to (i) integrate epigenetic data from prostate cancer cell lines to validate the activation function of EZH2 in castration-resistant prostate cancer and to (ii) study the mechanism of androgen receptor ( AR ) binding deregulation induced by the knockdown of FOXA1 . We found that EZH2 's noncanonical activation function was reaffirmed by its association with active histone markers and the lack of association with repressive markers. More importantly, we revealed that the binding of AR was selectively reprogramed to promoter regions, leading to the up-regulation of hundreds of cancer-associated genes including EGFR . The prebuilt epigenetic dataset from commonly used cell lines (LNCaP, VCaP, LNCaP-Abl, MCF7, GM12878, K562, HeLa-S3, A549, HePG2) makes Epidaurus a useful online resource for epigenetic research. As standalone software, Epidaurus is specifically designed to process user customized datasets with both efficiency and convenience.
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 4
    facet.materialart.
    Unbekannt
    Identification of RNA polymerase III-transcribed Alu loci by computational screening of RNA-Seq data (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-01-24
    Beschreibung: Of the ~1.3 million Alu elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which Alu transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq data sets and unique Alu DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual Alu elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci corresponding to detectable transcripts, with ~120 of them expressed in at least three cell lines. In vitro transcription of selected Alu s did not reflect their in vivo expression properties, and required the native 5'-flanking region in addition to internal promoter. We also identified a cluster of expressed Alu Ya5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu -unrelated downstream moiety. Autonomous Pol III transcription was also revealed for Alu s nested within Pol II-transcribed genes. The ability to investigate Alu transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant Alu RNAs and the assessment of Alu expression alteration under pathological conditions.
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 5
    facet.materialart.
    Unbekannt
    DEEP: a general computational framework for predicting enhancers (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-01-10
    Beschreibung: Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo -derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/ .
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 6
    facet.materialart.
    Unbekannt
    HiTSelect: a comprehensive tool for high-complexity-pooled screen analysis (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-02-18
    Beschreibung: Genetic screens of an unprecedented scale have recently been made possible by the availability of high-complexity libraries of synthetic oligonucleotides designed to mediate either gene knockdown or gene knockout, coupled with next-generation sequencing. However, several sources of random noise and statistical biases complicate the interpretation of the resulting high-throughput data. We developed HiTSelect, a comprehensive analysis pipeline for rigorously selecting screen hits and identifying functionally relevant genes and pathways by addressing off-target effects, controlling for variance in both gene silencing efficiency and sequencing depth of coverage and integrating relevant metadata. We document the superior performance of HiTSelect using data from both genome-wide RNAi and CRISPR/Cas9 screens. HiTSelect is implemented as an open-source package, with a user-friendly interface for data visualization and pathway exploration. Binary executables are available at http://sourceforge.net/projects/hitselect/ , and the source code is available at https://github.com/diazlab/HiTSelect .
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 7
    facet.materialart.
    Unbekannt
    ModuleBlast: identifying activated sub-networks within and across species (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-02-18
    Beschreibung: Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein.
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 8
    facet.materialart.
    Unbekannt
    RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-02-18
    Beschreibung: RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with ~94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ~83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA-protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred .
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 9
    facet.materialart.
    Unbekannt
    Enhancer modeling uncovers transcriptional signatures of individual cardiac cell states in Drosophila (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-02-18
    Beschreibung: Here we used discriminative training methods to uncover the chromatin, transcription factor (TF) binding and sequence features of enhancers underlying gene expression in individual cardiac cells. We used machine learning with TF motifs and ChIP data for a core set of cardiogenic TFs and histone modifications to classify Drosophila cell-type-specific cardiac enhancer activity. We show that the classifier models can be used to predict cardiac cell subtype cis -regulatory activities. Associating the predicted enhancers with an expression atlas of cardiac genes further uncovered clusters of genes with transcription and function limited to individual cardiac cell subtypes. Further, the cell-specific enhancer models revealed chromatin, TF binding and sequence features that distinguish enhancer activities in distinct subsets of heart cells. Collectively, our results show that computational modeling combined with empirical testing provides a powerful platform to uncover the enhancers, TF motifs and gene expression profiles which characterize individual cardiac cell fates.
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
  • 10
    facet.materialart.
    Unbekannt
    GRASP: Guided Reference-based Assembly of Short Peptides (2015)
    Oxford University Press
    Details
    Publikationsdatum: 2015-02-18
    Beschreibung: Protein sequences predicted from metagenomic datasets are annotated by identifying their homologs via sequence comparisons with reference or curated proteins. However, a majority of metagenomic protein sequences are partial-length, arising as a result of identifying genes on sequencing reads or on assembled nucleotide contigs, which themselves are often very fragmented. The fragmented nature of metagenomic protein predictions adversely impacts homology detection and, therefore, the quality of the overall annotation of the dataset. Here we present a novel algorithm called GRASP that accurately identifies the homologs of a given reference protein sequence from a database consisting of partial-length metagenomic proteins. Our homology detection strategy is guided by the reference sequence, and involves the simultaneous search and assembly of overlapping database sequences. GRASP was compared to three commonly used protein sequence search programs (BLASTP, PSI-BLAST and FASTM). Our evaluations using several simulated and real datasets show that GRASP has a significantly higher sensitivity than these programs while maintaining a very high specificity. GRASP can be a very useful program for detecting and quantifying taxonomic and protein family abundances in metagenomic datasets. GRASP is implemented in GNU C++, and is freely available at http://sourceforge.net/projects/grasp-release .
    Schlagwort(e): Computational Methods
    Print ISSN: 0305-1048
    Digitale ISSN: 1362-4962
    Thema: Biologie
    Publiziert von Oxford University Press
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    PAPER CURRENT
Schließen ⊗
Diese Webseite nutzt Cookies und das Analyse-Tool Matomo. Weitere Informationen finden Sie hier...