Real-Time and Low-Cost Sensing Technique Based on Photonic Bandgap Structures

This paper was published in OPTICS LETTERS and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OL.36.002707. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law[EN] A technique for the development of low-cost and high-sensitivity photonic biosensing devices is proposed and experimentally demonstrated. In this technique, a photonic bandgap structure is used as transducer, but its readout is performed by simply using a broadband source, an optical filter, and a power meter, without the need of obtaining the transmission spectrum of the structure; thus, a really low-cost system and real-time results are achieved. Experimental results show that it is possible to detect very low refractive index variations, achieving a detection limit below 2 x 10(-6) refractive index units using this low-cost measuring technique. (C) 2011 Optical Society of America[This work was funded by the Spanish Ministerio de Ciencia e Innovacion (MICINN) under contracts TEC2008-06333, JCI-009-5805, and TEC2008-05490. Support by the Universidad Politecnica de Valencia through program PAID-06-09 and the Conselleria d'Educacio through program GV-2010-031 is acknowledged.García Castelló, J.; Toccafondo, V.; Pérez Millán, P.; Sánchez Losilla, N.; Cruz, JL.; Andres, MV.; García-Rupérez, J. (2011). Real-Time and Low-Cost Sensing Technique Based on Photonic Bandgap Structures. Optics Letters. 36(14):2707-2709. https://doi.org/10.1364/OL.36.002707S270727093614Fan, X., White, I. M., Shopova, S. I., Zhu, H., Suter, J. D., & Sun, Y. (2008). Sensitive optical biosensors for unlabeled targets: A review. 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Gene3D: comprehensive structural and functional annotation of genomes

Gene3D provides comprehensive structural and functional annotation of most available protein sequences, including the UniProt, RefSeq and Integr8 resources. The main structural annotation is generated through scanning these sequences against the CATH structural domain database profile-HMM library. CATH is a database of manually derived PDB-based structural domains, placed within a hierarchy reflecting topology, homology and conservation and is able to infer more ancient and divergent homology relationships than sequence-based approaches. This data is supplemented with Pfam-A, other non-domain structural predictions (i.e. coiled coils) and experimental data from UniProt. In order to enhance the investigations possible with this data, we have also incorporated a variety of protein annotation resources, including protein–protein interaction data, GO functional assignments, KEGG pathways, FUNCAT functional descriptions and links to microarray expression data. All of this data can be accessed through a newly re-designed website that has a focus on flexibility and clarity, with searches that can be restricted to a single genome or across the entire sequence database. Currently Gene3D contains over 3.5 million domain assignments for nearly 5 million proteins including 527 completed genomes. This is available at: http://gene3d.biochem.ucl.ac.uk

CADRE: the Central Aspergillus Data REpository 2012

The Central Aspergillus Data REpository (CADRE; http://www.cadre-genomes.org.uk) is a public resource for genomic data extracted from species of Aspergillus. It provides an array of online tools for searching and visualising features of this significant fungal genus. CADRE arose from a need within the medical community to understand the human pathogen Aspergillus fumigatus. Due to the paucity of Aspergillus genomic resources 10 years ago, the long-term goal of this project was to collate and maintain Aspergillus genomes as they became available. Since our first release in 2004, the resource has expanded to encompass annotated sequence for eight other Aspergilli and provides much needed support to the international Aspergillus research community. Recent developments, however, in sequencing technology are creating a vast amount of genomic data and, as a result, we shortly expect a tidal wave of Aspergillus data. In preparation for this, we have upgraded the database and software suite. This not only enables better management of more complex data sets, but also improves annotation by providing access to genome comparison data and the integration of high-throughput data

Gramene 2013: comparative plant genomics resources

Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology

Gramene 2016: comparative plant genomics and pathway resources

Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to approximately 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials

Methods and strategies for gene structure curation in WormBase

The Caenorhabditis elegans genome sequence was published over a decade ago; this was the first published genome of a multi-cellular organism and now the WormBase project has had a decade of experience in curating this genome's sequence and gene structures. In one of its roles as a central repository for nematode biology, WormBase continues to refine the gene structure annotations using sequence similarity and other computational methods, as well as information from the literature- and community-submitted annotations. We describe the various methods of gene structure curation that have been tried by WormBase and the problems associated with each of them. We also describe the current strategy for gene structure curation, and introduce the WormBase ‘curation tool’, which integrates different data sources in order to identify new and correct gene structures

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces

Bio::Homology::InterologWalk - A Perl module to build putative protein-protein interaction networks through interolog mapping

<p>Abstract</p> <p>Background</p> <p>Protein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction.</p> <p>Results</p> <p>We introduce <monospace>Bio::Homology::InterologWalk</monospace>, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, <it>Drosophila melanogaster</it>. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation.</p> <p>Conclusions</p> <p>Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy to customise the results by post-processing, allowing the putative PPI datasets to be easily integrated into existing analysis workflows. The <monospace>Bio::Homology::InterologWalk</monospace> module, sample scripts and full documentation are freely available from the Comprehensive Perl Archive Network (CPAN) under the GNU Public license.</p