178 research outputs found
Matrices of Pairwise Genetic Distances for 339 Spider Species
No full textSpiders were collected from locations across Canada by various collectors. Sequencing was performed at the Canadian Centre for DNA Barcoding, and the sequences uploaded to BOLD Systems. Sequence data was obtained by Sujeevan Ratnasingham from BOLD Systems and compiled as a matrix
Matrices of Pairwise Geographic Distances for 339 Spider Species
No full textSpiders were collected from locations across Canada by various collectors. GPS coordinates were obtained at the time of collection, or looked up at a later date on Google Earth based on name of collection location. Coordinate data was obtained by Sujeevan Ratnasingham from BOLD Systems and compiled as a matrix
mBRAVE: The Multiplex Barcode Research And Visualization Environment
No full textWidespread interest in the study of metabarcoding has resulted in data proliferation and the development of a multitude of powerful computational tools. Yet consistent and reproducible interpretation of the data remains challenging. The integration of different data types, software tools, and analytical parameters pose a barrier to scaling research. Further, though the majority of the necessary tools for performing these analyses are already implemented, there is limited support for high throughput analysis due to the requirement for heavy computational capacity. As a result of these complexities, many researchers lack the time, training, or infrastructure to work with larger datasets.
mBRAVE, the Multiplex Barcode Research And Visualization Environment, is a cloud-based data storage and analytics platform with standardized pipelines and a sophisticated web interface for transforming raw high-throughput sequencing (HTS) data into biological insights. mBRAVE integrates common analytical methods and links to the Barcode of Life Data (BOLD) System for reference datasets, presenting users with the ability to analyze large volumes of data, without requiring special technical training. mBRAVE's cloud architecture provides centralized and automated storage and compute capacity, thereby reducing the burden on individual researchers.
The mBRAVE platform seeks to alleviate the main informatic challenges faced by the metabarcoding research community: the storage and consistent interpretation of HTS data. It is now available for researcher use at www.mbrave.net
BOLD & mBRAVE: Purpose-Built Research Data Platforms in the Biodiversity Domain
No full textUpdate on the BOLD and mBRAVE projects, part of the International Barcode of Life Project.</p
WF.ACTIAS: A workflow for a better integration of biodiversity data from diverse sources
No full textInternational audienceOur knowledge of global biodiversity remains incomplete and beset by knowledge shortfalls affecting both the census of species (i.e. the Linnean shortfall) and our understanding of their distributions (i.e. the Wallacean shortfall; Hortal et al. 2015). While alarming rates of species extinction have been reported in most groups of organisms, our capacity to assess extinction threats is limited by these shortfalls and it has become imperative to optimize our use of existing information for the analyses of biodiversity data. There are two major challenges when integrating biodiversity data from heterogeneous sources to ultimately analyzing them:The frequent disparity in taxon names used to refer to the same organisms;Geographical inconsistencies on specimen information. The first refers to disagreements about the taxon concepts attached to names alongside the different interpretations and applications (e.g. gender agreement in taxonomic names) of the existing nomenclatural rules that ensure universality and stability of scientific names. The development of new methods for species delineation, and in particular with the growing integration of genetic data in the practice of taxonomy (e.g. DNA barcoding; Ratnasingham and Hebert 2013), has increased our ability to discriminate closely related species. This enhances the resolution level at which biodiversity is documented, described and analyzed(Goldstein and DeSalle 2011). One frequent outcome is the redefinition of species boundaries; either through merging (synonymy) or splitting of previously recognized species. In understudied groups such as insects, the resulting inflation of names, sometimes provisional, further defies the reconciliation of names used by different sources.The second challenge refers to the completeness and accuracy of geographical information. Specimen records in biodiversity databases often lack GPS coordinates. Consequently we need to accurately infer the latitude and longitude from place names. Other frequent inaccuracies include erroneous georeferencing, imprecision and/or error in the location of a record (Soberón and Peterson 2004).Integration of data on the basis of taxon names and their geographic information is a major challenge that either results in excluding a significant number of records, or in merging incompatible records, leading to erroneous outcomes. Therefore, we have developed WF.ACTIAS, a computational workflow that gathers data from several sources and provides the user with tools to make objective and reproducible decisions to assign records to a consensus species name, while detecting and correcting geographical inconsistencies. Its main objective is to automate a process that can integrate information about nomenclature, taxon concepts and geographical information to reconcile taxon names from different sources. Here, we present the WF.ACTIAS workflow in the context of the analysis of diversity in two sister families of moths – the Saturniidae and Sphingidae. Species boundaries in these insects have been thoroughly and comprehensively revisited through the integration of DNA barcodes and we are tackling the reconciliation of taxon names in ca. 282 000 records of which more than 77 000 have DNA barcodes. The outcome of this data integration is essential to study patterns of biodiversity and distributions and sets the ground to extend this process to other groups of organisms
WF.ACTIAS: A workflow for a better integration of biodiversity data from diverse sources
No full textOur knowledge of global biodiversity remains incomplete and beset by knowledge shortfalls affecting both the census of species (i.e. the Linnean shortfall) and our understanding of their distributions (i.e. the Wallacean shortfall; Hortal et al. 2015). While alarming rates of species extinction have been reported in most groups of organisms, our capacity to assess extinction threats is limited by these shortfalls and it has become imperative to optimize our use of existing information for the analyses of biodiversity data. There are two major challenges when integrating biodiversity data from heterogeneous sources to ultimately analyzing them:
The frequent disparity in taxon names used to refer to the same organisms;
Geographical inconsistencies on specimen information.
The first refers to disagreements about the taxon concepts attached to names alongside the different interpretations and applications (e.g. gender agreement in taxonomic names) of the existing nomenclatural rules that ensure universality and stability of scientific names. The development of new methods for species delineation, and in particular with the growing integration of genetic data in the practice of taxonomy (e.g. DNA barcoding; Ratnasingham and Hebert 2013), has increased our ability to discriminate closely related species. This enhances the resolution level at which biodiversity is documented, described and analyzed(Goldstein and DeSalle 2011). One frequent outcome is the redefinition of species boundaries; either through merging (synonymy) or splitting of previously recognized species. In understudied groups such as insects, the resulting inflation of names, sometimes provisional, further defies the reconciliation of names used by different sources.
The second challenge refers to the completeness and accuracy of geographical information. Specimen records in biodiversity databases often lack GPS coordinates. Consequently we need to accurately infer the latitude and longitude from place names. Other frequent inaccuracies include erroneous georeferencing, imprecision and/or error in the location of a record (Soberón and Peterson 2004).
Integration of data on the basis of taxon names and their geographic information is a major challenge that either results in excluding a significant number of records, or in merging incompatible records, leading to erroneous outcomes. Therefore, we have developed WF.ACTIAS, a computational workflow that gathers data from several sources and provides the user with tools to make objective and reproducible decisions to assign records to a consensus species name, while detecting and correcting geographical inconsistencies. Its main objective is to automate a process that can integrate information about nomenclature, taxon concepts and geographical information to reconcile taxon names from different sources. Here, we present the WF.ACTIAS workflow in the context of the analysis of diversity in two sister families of moths – the Saturniidae and Sphingidae. Species boundaries in these insects have been thoroughly and comprehensively revisited through the integration of DNA barcodes and we are tackling the reconciliation of taxon names in ca. 282 000 records of which more than 77 000 have DNA barcodes. The outcome of this data integration is essential to study patterns of biodiversity and distributions and sets the ground to extend this process to other groups of organisms
A DNA-based registry for all animal species: the barcode index number (BIN) system.
No full textBecause many animal species are undescribed, and because the identification of known species is often difficult, interim taxonomic nomenclature has often been used in biodiversity analysis. By assigning individuals to presumptive species, called operational taxonomic units (OTUs), these systems speed investigations into the patterning of biodiversity and enable studies that would otherwise be impossible. Although OTUs have conventionally been separated through their morphological divergence, DNA-based delineations are not only feasible, but have important advantages. OTU designation can be automated, data can be readily archived, and results can be easily compared among investigations. This study exploits these attributes to develop a persistent, species-level taxonomic registry for the animal kingdom based on the analysis of patterns of nucleotide variation in the barcode region of the cytochrome c oxidase I (COI) gene. It begins by examining the correspondence between groups of specimens identified to a species through prior taxonomic work and those inferred from the analysis of COI sequence variation using one new (RESL) and four established (ABGD, CROP, GMYC, jMOTU) algorithms. It subsequently describes the implementation, and structural attributes of the Barcode Index Number (BIN) system. Aside from a pragmatic role in biodiversity assessments, BINs will aid revisionary taxonomy by flagging possible cases of synonymy, and by collating geographical information, descriptive metadata, and images for specimens that are likely to belong to the same species, even if it is undescribed. More than 274,000 BIN web pages are now available, creating a biodiversity resource that is positioned for rapid growth
High Responsivity and Response Speed Single‐Layer Mixed‐Cation Lead Mixed‐Halide Perovskite Photodetectors Based on Nanogap Electrodes Manufactured on Large‐Area Rigid and Flexible Substrates
No full textAdv. Funct. Mater. 2019, 29, 1901371 In the initially published version of this article, the name of Akmaral Seitkhan was omitted from the final authors list. The correct author list is as follows: Dimitra G. Georgiadou,* Yen-Hung Lin, Jongchul Lim, Sinclair Ratnasingham, Akmaral Seitkhan, Martyn A. McLachlan, Henry J. Snaith, and Thomas D. Anthopoulos* The respective updated author affiliations are as follows: Dr. D. G. Georgiadou, Prof. T. D. Anthopoulos Department of Physics and Centre for Plastic Electronics Blackett Laboratory Imperial College London Exhibition Road, London SW7 2BW, UK E-mail: [email protected]; [email protected] Dr. D. G. Georgiadou, S. Ratnasingham, Dr. M. A. McLachlan Department of Materials and Centre for Plastic Electronics Imperial College London Prince Consort Road, London SW7 2BP, UK Dr. Y.-H. Lin, Dr. J. Lim, Prof. H. J. Snaith Department of Physics University of Oxford Clarendon Laboratory Parks Road, Oxford OX1 3PU, UK A. Seitkhan, Prof. T. D. Anthopoulos Division of Physical Sciences and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal 23955–6900, Saudi Arabia The authors apologize for any inconvenience this error may have caused.</p
Bringing Genomics to Diversity: Barcode of Life Database System & Multiplex Barcode Research and Visualization Environment
No full textDescription of the software development project funded by CANARIE.</p
Bringing Genomics to Diversity: Barcode of Life Database System & Multiplex Barcode Research and Visualization Environment
No full textDescription of the software development project funded by CANARIE
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