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  • 1.
    Abalde, Samuel
    Swedish Museum of Natural History, Department of Zoology.
    MATEdb: a new phylogenomic-driven database for Metazoa2022Other (Other (popular science, discussion, etc.))
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  • 2.
    de Jong, Yde
    et al.
    University of Amsterdam.
    Kouwenberg, Juiana
    Boumans, Louis
    Hussey, Charles
    Hyam, Roger
    Nicolson, Nicola
    Kirk, Paul
    Paton, Alan
    Michel, Ellinor
    Guiry, Michael D,
    Boegh, Phillip S.
    Aerenlund Pedersen, Henrik
    Enghoff, Henrik
    von Raab-Straube, Eckhard
    Güntsch, Anton
    Geoffroy, Marc
    Müller, Andreas
    Kohlbecker, Andreas
    Berendsohn, Walter
    Appeltans, Ward
    Arvantidis, Christos
    Vanhoorne, Bart
    Declerck, Joram
    Vandepitte, Leen
    Hernandez, Francisco
    Nash, Róisín
    Costello, Mark John
    Ouvrard, David
    Bezard-Falgas, Pascale
    Bourgoin, Thierry
    Wetzel, Florian Tobias
    Glöckler, Falko
    Korb, Günther
    Ring, Caroline
    Hagedorn, Gregor
    Häuser, Christoph
    Aktaç, Nihat
    Asan, Ahmet
    Ardelean, Adorian
    Vieira Borges, Paulo Alexandre
    Dhora, Dhimiter
    Khachatryan, Hasmik
    Malicky, Michael
    Ibrahimov, Shaig
    Tuzikov, Alexander
    De Wever, Aike
    Moncheva, Snejana
    Spassov, Nikolai
    Chobot, Karel
    Popov, Alexei
    Borsíc, Igor
    Sfenthourakis, Spyros
    Köljalg, Urmas
    Uotila, Pertti
    Olivier, Gargominy
    Dauvin, Jean-Claude
    Tarkhnishvili, David
    Chaladze, Giorgi
    Tuerkay, Michael
    Legakis, Anastasios
    Peregovits, LáslZó
    Gudmundsson, Gudmundur
    Ólafsson, Erling
    Lysaght, Liam
    Galil, Bella Sarah
    Raimondo, Francesco M.
    Domina, Gianniantonio
    Stoch, Fabio
    Minelli, Alessandro
    Spungis, Voldemars
    Budrys, Eduardas
    Olenin, Sergei
    Turpel, Armand
    Walisch, Tania
    Krpach, Vladimir
    Gambin, Marie Therese
    Ungureano, Laurentia
    Karaman, Gordan
    Kleukers, Roy M. J. C.
    Stur, Elisabeth
    Aagaard, Kaare
    Valland, Nils
    Loennechen Moen, Tori
    Bogdanowicz, Wieslaw
    Tykarski, Piotr
    Wieslawski, Jan Marcin
    Kedra, Monika
    de frias Martins, ntonio M.
    Domingos Abreu, António
    Silva, Ricardo
    Medvedev, Sergei
    Ryss, Alexander
    Simic, Smilijka
    Marhold, Karel
    Stloukal, Eduard
    Tome, Davorin
    Ramos, Marian A.
    Valdés, Benito
    Pina, Francisco
    Kullander, Sven
    Swedish Museum of Natural History, Department of Zoology.
    Anders, Telenius
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Gonseth, Yves
    Tschudin, Pascal
    Sergeyeva, Oleksandra
    Vladymyrov, Volodymyr
    Bogdanovych Rizun, Volodymyr
    Raper, Chris
    Lear, Dan
    Stoev, Pavel
    Penev, Lyubomir
    Casino Rubio, Ana
    Backeljau, Thierry
    Saarenmaa, Hannu
    Ullenberg, Sandrine
    PESI - a taxonomic backbone for Europe2015In: Biodiversity Data Journal, ISSN 1314-2836, E-ISSN 1314-2828, Vol. 3, p. 1-51, article id e5848Article in journal (Refereed)
    Abstract [en]

    Reliable taxonomy underpins communication in all of biology, not least nature conservation and sustainable use of ecosystem resources. The flexibility of taxonomic interpretations, however, presents a serious challenge for end-users of taxonomic concepts. Users need standardised and continuously harmonised taxonomic reference systems, as well as high-quality and complete taxonomic data sets, but these are generally lacking for non-specialists. The solution is in dynamic, expertly curated web-based taxonomic tools.

    The Pan-European Species-directories Infrastructure (PESI) worked to solve this key issue by providing a taxonomic e-infrastructure for Europe. It strengthened the relevant social (expertise) and information (standards, data and technical) capacities of five major community networks on taxonomic indexing in Europe, which is essential for proper biodiversity assessment and monitoring activities. The key objectives of PESI were: 1) standardisation in taxonomic reference systems, 2) enhancement of the quality and completeness of taxonomic data sets and 3) creation of integrated access to taxonomic information.

    This paper describes the results of PESI and its future prospects, including the involvement in major European biodiversity informatics initiatives and programs.

  • 3.
    Glöckler, Falko
    et al.
    Museum für Naturkunde.
    Macklin, James
    Agriculture and Agri-Food Canada.
    Ronquist, Fredrik
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Hoffmann, Jana
    Museum für Naturkunde.
    DINA: Open Source and Open Services - A modern approach for natural history collection management systems and research2019In: Biodiversity Information Science and Standards, p. e38059-Article in journal (Refereed)
  • 4. Horton, Tammy
    et al.
    Gofas, Serge
    Kroh, Andreas
    Poore, Gary
    Read, Geoffrey
    Rosenberg, Gary
    Stöhr, Sabine
    Swedish Museum of Natural History, Department of Zoology.
    Bailly, Nicolas
    Boury-Esnault, Nicole
    Brandao, Simone
    Costello, Mark
    DeCock, Wim
    Dekeyzer, Stefanie
    Hernandez, Francisco
    Mees, Jan
    Paulay, Gustav
    Vandepitte, Leen
    Vanhoorne, Bart
    Vranken, Stefanie
    Improving nomenclatural consistency: a decade of experience in the World Register of Marine Species2017In: European journal of taxonomy, E-ISSN 2118-9773, Vol. 389, p. 1-24Article in journal (Refereed)
  • 5. Lundén, Daniel
    et al.
    Öhman, Joey
    KTH Royal Institute of Technology.
    Kudlicka, Jan
    BI Norwegian Business School.
    Senderov, Viktor
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Ronquist, Fredrik
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Broman, David
    KTH Royal Institute of Technology.
    Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference2022In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 13240, p. 29-56Article in journal (Refereed)
  • 6.
    Malm, Tobias
    et al.
    Swedish Museum of Natural History, Department of Zoology.
    Rota, Jadranka
    Department of Biology, Lund University, Lund, Sweden.
    Chazot, Nicolas
    Department of Biology, Lund University, Lund, Sweden.
    Peña, Carlos
    HipLead, San Francisco, CA, United States of America.
    Wahlberg, Niklas
    Department of Biology, Lund University, Lund, Sweden.
    A simple method for data partitioning based on relative evolutionary rates2018In: PeerJ, E-ISSN 2167-8359, p. 1-21, article id 6:e5498Article in journal (Refereed)
    Abstract [en]

    Background. Multiple studies have demonstrated that partitioning of molecular datasets is important in model-based phylogenetic analyses. Commonly, partitioning is done a priori based on some known properties of sequence evolution, e.g. differences in rate of evolution among codon positions of a protein-coding gene. Here we propose a new method for data partitioning based on relative evolutionary rates of the sites in the alignment of the dataset being analysed. The rates are inferred using the previously published Tree Independent Generation of Evolutionary Rates (TIGER), and the partitioning is conducted using our novel python script RatePartitions. We conducted simulations to assess the performance of our new method, and we applied it to eight published multi-locus phylogenetic datasets, representing different taxonomic ranks within the insect order Lepidoptera (butterflies and moths) and one phylogenomic dataset, which included ultra-conserved elements as well as introns.

    Methods. We used TIGER-rates to generate relative evolutionary rates for all sites in the alignments. Then, using RatePartitions, we partitioned the data into partitions based on their relative evolutionary rate. RatePartitions applies a simple formula that ensures a distribution of sites into partitions following the distribution of rates of the characters from the full dataset. This ensures that the invariable sites are placed in a partition with slowly evolving sites, avoiding the pitfalls of previously used methods, such as kmeans. Different partitioning strategies were evaluated using BIC scores as calculated by PartitionFinder.

    Results. Simulations did not highlight any misbehaviour of our partitioning approach, even under difficult parameter conditions or missing data. In all eight phylogenetic datasets, partitioning using TIGER-rates and RatePartitions was significantly better as measured by the BIC scores than other partitioning strategies, such as the commonly used partitioning by gene and codon position. We compared the resulting topologies and node support for these eight datasets as well as for the phylogenomic dataset.

    Discussion. We developed a new method of partitioning phylogenetic datasets without using any prior knowledge (e.g. DNA sequence evolution). This method is entirely based on the properties of the data being analysed and can be applied to DNA sequences (protein-coding, introns, ultra-conserved elements), protein sequences, as well as morphological characters. A likely explanation for why our method performs better than other tested partitioning strategies is that it accounts for the heterogeneity in the data to a much greater extent than when data are simply subdivided based on prior knowledge.

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  • 7.
    Norén, Michael
    Swedish Museum of Natural History, Department of Zoology. FishBase.
    The enigmatic Betadevario ramachandrani (Teleostei: Cyprinidae: Danioninae): phylogenetic position resolved by mitogenome analysis, with remarks on the prevalence of chimeric mitogenomes in GenBank2018In: Cogent Biology, ISSN 2331-2025, Vol. 4, no 1, p. 1-8Article in journal (Refereed)
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  • 8. Pochon, Zoé
    et al.
    Bergfeldt, Nora
    Kırdök, Emrah
    Vicente, Mário
    Naidoo, Thijessen
    van der Valk, Tom
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Altınışık, N. Ezgi
    Krzewińska, Maja
    Dalén, Love
    Götherström, Anders
    Mirabello, Claudio
    Unneberg, Per
    Oskolkov, Nikolay
    aMeta: an accurate and memory-efficient ancient metagenomic profiling workflow2023In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 24, no 1, article id 242Article in journal (Refereed)
  • 9. Prager, Maria
    et al.
    Lundin, Daniel
    Ronquist, Fredrik
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Andersson, Anders F.
    ASV portal: an interface to DNA-based biodiversity data in the Living Atlas2023In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 24, no 1, article id 6Article in journal (Refereed)
  • 10. Prager, Maria
    et al.
    Lundin, Daniel
    Ronquist, Fredrik
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Andersson, Anders F.
    The ASV Portal Allows for Efficient Handling of DNA Derived Data in the Living Atlas2023In: Biodiversity Information Science and Standards, 2023, article id e110488Conference paper (Refereed)
  • 11.
    Ronquist, Fredrik
    et al.
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Skyttner, Markus
    Swedish Museum of Natural History, Department of Bioinformatics and Genetics.
    Kõljalg, Urmas
    Röppert, Dominik
    Penev, Lyubomir
    Stoev, Pavel
    Peer, Israel
    Stein, Martin
    Calabuig, Isabel
    Agosti, Donat
    Kempa, Matus
    EU-BON Deliverable 1.3. Systems for mobilizing and managing collection-based data (specimen + DNA-data) fully integrated2016Report (Other academic)
    Abstract [en]

    Introduction. A large portion of the biodiversity data in natural history collections is still not available digitally. Increasingly, innovative high-throughput methods are being applied to digitize this backlog in bulk, generating large amounts of data. In parallel, natural history museums are becoming increasingly involved in the generation of large amounts of molecular biodiversity data using new massively parallel sequencing platforms. Against this backdrop, the goal of EU BON Task 1.4 has been to support data mobilization efforts targeting collection-based and molecular data, mainly through the development and integration of innovative open-source tools and services.

    Progress towards objectives. The activities have involved work within the context of three major projects: i) DINA, an open-source, modular, web-based collection management system for natural history specimen data. ii) JACQ an open-access system for botanical (herbarium) data. iii) PlutoF, a web platform for working with traditional and molecular biodiversity research data. The task has also involved work on a number of other EU BON partner systems and services, as well as integration across internal EU BON and external biodiversity informatics resources. Finally, these systems have been used for targeted data mobilization efforts.

    Achievements and current status. Within DINA, the focus has been on supporting the engineering of sophisticated biodiversity information systems through the exploration of tools supporting distributed development and a modular plug-and-play design based on services-oriented architectures. This has involved the testing and adoption of tools like Apiary for the design of Application Programming Interfaces (APIs) and Docker for systems integration and deployment tasks. A Python library for data migration to DINA was also developed and tested. Within JACQ, a number of tools were developed to facilitate deployment and data migration to the system, and the AnnoSys tool for annotation of data has been integrated. Within PlutoF, EU BON efforts focused on the development of a citizen-science module and improved functionality for the mobilization of collection (living) specimen data. A number of innovative tools were developed by Pensoft to help mobilize biodiversity data published in the scientific literature, including semantic mark-up of species conservation papers, direct import of data from a range of biodiversity platforms into manuscripts, and a mechanism for providing stable links from publications to global biodiversity repositories. Plazi implemented an automated workflow mining published scientific papers for taxonomic data, currently mobilizing 25 % of all published new names as they become available. GlueCad developed apps allowing citizen scientists reporting spontaneous observations or systematic inventory data to select target taxa and preferred data mobilization platform. IBSAS and UCPH have focused on national data mobilization efforts targeting Slovakia and Denmark, respectively.

    Future developments. Although the development is clearly towards increased integration of biodiversity informatics tools into larger and more sophisticated systems, it is clear that there is no one size that fits all. Nevertheless, the increasingly widespread adoption of community standards, open-source development practises and service-oriented architectures are pushing the capability of current systems forward and facilitating tighter integration across systems. This trend is supported by the appearance of sophisticated tools enabling the design and deployment of complex modular systems. The adoption of the Docker approach is one example of how the biodiversity informatics community may benefit from this.

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  • 12.
    Wahlberg, Emma
    Swedish Museum of Natural History, Department of Zoology.
    FACEPAI: a script for fast and consistent environmental DNA processing and identification2019In: BMC Ecology, E-ISSN 1472-6785, Vol. 19, p. 51-Article in journal (Refereed)
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  • 13.
    Wahlberg, Emma
    Swedish Museum of Natural History, Department of Zoology.
    Kartläggning av tvåvingar med miljö-DNA – mer än bara en fluga2019In: Fauna och flora : populär tidskrift för biologi, ISSN 0014-8903, Vol. 114, no 4, p. 20-26Article in journal (Other (popular science, discussion, etc.))
1 - 13 of 13
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