Find research datasets worth reusing

Science ready spectra and their best-fitting models described in the research paper ``Internal dynamics and stellar content of nine ultra-diffuse galaxies in the Coma cluster prove their evolutionary link with dwarf early-type galaxies'' by Chilingarian et al.

Science ready spectra of nine ultra-diffuse galaxies in the Coma cluster collected with the Binospec multi-object spectrograph and their best-fitting PEGASE.HR templates obtained using the NBursts full spectrum fitting code. These spectra were presented in the paper ``Internal dynamics and stellar content of nine ultra-diffuse galaxies in the Coma cluster prove their evolutionary link with dwarf early-type galaxies'' by Chilingarian et al. accepted for publication in the Astrophysical Journal on Sep/3/2019 (arXiv:1901.05489). Each spectrum is presented as a binary FITS table, which contains a spectrum (wavelength, flux, uncertainties), best-fitting template, best-fitting parameters (radial velocity, age, metallicity), and a pixel mask used in the fitting procedure. For six galaxies there are two files provided: (i) one-dimensional optimally extracted integrated spectrum and (ii) two dimensional spectrum for spatially resolved radial velocity information. For the remaining three galaxies, only spatially resolved spectra are provided.

Results of the DYNAMO (Dynamic MEC Orchestration of Cellular Networks) experiment in the Fed4FIRE+ testbeds

The main objective of the DYNAMO Fed4FIRE+ experiment was to perform Network Function Virtualization (NFV) Management and Network Orchestration (MANO) of a cellular network on top of cloud infrastructures, exploring one of the key enabling technologies for 5G systems and beyond.  DYNAMO used cloud and radio access facilities at the IRIS testbed and cloud facilities at the University of Vigo (UVIGO) to deploy an end-to-end (E2E) cellular network and perform elastic changes on it if needed. The geographic distance in between facilitated the setup of a realistic Multi-Access Edge Computing (MEC) use case, where the virtual Evolved Packet Core (vEPC) was deployed at UVIGO (Spain) and the access network, i.e., the User Equipment (UE), the e-Node-B (eNB) and edge cloud, were implemented on IRIS testbed (Ireland).   While the initial deployment of the E2E cellular network may be considered as static, DYNAMO showcases the elasticity that an E2E cellular network may need in runtime. Hence, we presented a use case consisting of a latency sensitive E2E cellular network (network slice), where the endpoint of the UE connection was initially located in the core (UVIGO) but then migrated to the edge (IRIS), in case the UE's latency ranges were unacceptable.   In this regard, the UE reported the experienced latency to Open Network Automation Platform (ONAP), which is responsible to trigger specific policy-driven control actions if a predefined Service-Level Agreement (SLA) is violated. This datased includes the reports provided by the UE to ONAP.   As a result, the endpoint of the data plane of the UE is automatically moved to the access network (IRIS) thus reducing significantly the latency for the UE.  For the access part of the network, we implemented one srsLTE e-Node-B (eNB), one srsLTE User Equipment (UE) and a Devstack (Edge Cloud) in virtual machines on IRIS testbed. In addition, we also implemented an SDN switch controlled by an ONOS SDN controller. For the core part of the network, we considered a disaggregated vEPC from Open Air Interface (OAI) on a Devstack (Core Cloud) at UVIGO.   DYNAMO has succeeded in the integration of a broad set of network elements and technologies between the two different domains (UVIGO and IRIS testbed) and fulfilled all initial objectives: (i) establishing communication between ONAP and IRIS testbed to deploy generic VNFs on core and edge clouds, (ii), deployment of an E2E cellular network with UE and eNB in IRIS and the vEPC at UVIGO, (iii), sending telemetry of the UE to ONAP and (iv) designing and testing closed-loop control actions in ONAP to migrate the data plane of the UE to the edge in case of unsatisfactorily SLA.  DYNAMO paves the way to a broad set of future 5G experiments that will require resource orchestration, such as the deployment of network slices or the automatic scheduling of services in the limited resources of Edge Clouds. This repository contains the information sent from the UE to ONAP, in order to decide if the latency between the UE and the PGW is OK or if an action has to be considered to reduce such latency.

Physiographic and climatic controls on groundwater dynamics

Data set to reproduce results from Haaf et al., 2019 (submitted) containing: <ul> <li>46 index values of 340 daily groundwater level time series from Bavaria.</li> <li>Geologic, topographic, boundary and climatic controls used as potential predictors</li> </ul>

Molecular dynamics simulations of the interaction of the quadruple mutant human CYP2J2 (R111A + R117A + R382A + R446A) with arachidonic acid (POSES 1-3)

Description of files in this dataset: MD_quadmut_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the quadruple R111A + R117A+R382A+R446A) mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage

Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R117A) with arachidonic acid (POSES 5-6)

Description of files in this dataset: MD_mutR117A_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with DHA (POSES 1-4)

Description of files in this dataset: MD_wt_CYP2J2_DHA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of docosahexaenoic acid (DHA) in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 4 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 3 and 4)

Description of files in this dataset: MD_wt_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 4 times, hence there are 4 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

Homology modelling, molecular docking and molecular dynamics simulations of wild type and mutant human CYP2J2 with three polyunsaturated fatty acids

This is the "parent" repository for the Data Note : "Molecular dynamics simulations of the interaction of wild type and mutant human CYP2J2 with polyunsaturated fatty acids" by Abelak, Bishop-Bailey and Nobeli. It contains a document (Abelak_etal_Methods.pdf) describing the methods used to produce the data here and the data in all repositories supplementing it. It also contains a shell script (create_sim4_repeats.sh) that is typical of those used to set up the molecular dynamics simulations in the repositories supplementing this one. Finally, it contains the results of the homology modelling and docking simulations that formed the starting points for the molecular dynamics simulations in this study. Description of files in this dataset: C2J2_min3_mod_noH.pdb : Homology model of the wild type CYP2J2 built from an alignment of templates with PDB ids: 1SUO, 2P85, 3EBS and 1Z10. docking_wild_type_C2J2.zip : Nine docked poses of arachidonic acid docked to the homology model of the wild type CYP2J2. Details of how this data was produced is available in the Abelak_etal_Methods.docx document.

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 1 and 2)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 5 and 6)

Molecular dynamics simulations of the interaction of the double mutant human CYP2J2 (R117A and R111A) with arachidonic acid (POSES 1-3)

Description of files in this dataset: MD_mutR111A_R117A_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the double R111A + R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage

Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R117A) with arachidonic acid (POSES 1-4)

Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R111A) with arachidonic acid (POSES 4-6)

Description of files in this dataset: MD_mutR111A_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R111A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

Molecular dynamics simulations of the interaction of wild type human CYP2J2 with EPA (POSES 1-4)

Description of files in this dataset: MD_wt_CYP2J2_EPA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of eicosapentaenoic acid (EPA) in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 4 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage 005.md : Production stage 006.analysis : Basic energy graphs 007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)

Molecular dynamics simulations of the interaction of the quadruple mutant human CYP2J2 (R111A + R117A + R382A + R446A) with arachidonic acid (POSES 4-6)

Description of files in this dataset: MD_quadmut_CYP2J2_AA_StateX_repeatY.zip : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the quadruple (R111A + R117A+R382A+R446A) mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose).   Each directory contains the following sub-directories: 001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands 002.min : Minimisation stage 003.heat : Heating stage 004.equil: Equilibration stage

Experimental datasets of networks of nonlinear oscillators: Structure and dynamics during the path to synchronization

The analysis of the interplay between structural and functional networks require experiments where both the specific structure of the connections between nodes and the time series of the underlying dynamical units are known at the same time.  However, real datasets typically contain only one of the two ways (structural or functional) a network can be observed. Here, we provide experimental recordings of the dynamics of 28 nonlinear electronic circuits coupled in 20 different network configurations. For each network, we modify the coupling strength between circuits, going from an incoherent state of the system to a complete synchronization scenario. Time series containing 30000 points are recorded using a data-acquisition card capturing the analogic output of each circuit. The experiment is repeated three times for each network structure allowing to track the path to the synchronized state both at the level of the nodes (with its direct neighbors) and at the whole network. These datasets can be useful to test new metrics to evaluate the coordination between dynamical systems and to investigate to what extent the coupling strength is related to the correlation between functional and structural networks. We provide the times series of N=28 Rössler electronic oscillators for 20 different network configurations (compressed file with tag R1 to R20). For each network structure, we recorded the times series for 101 different coupling strengths between oscillators. Each one of the 101 corresponding files is labeled as ST_X_Y.dat where X is a value between X=0 and X=100 that corresponds, respectively, to the minimum and maximum coupling strength. The value of Y corresponds to the repetition number, which can be 1, 2 of 3 (i.e., we repeated the same experiment three times). Data files contain the second variable of the 28 nodes arranged in columns with a length of 30000 points. In a second file named Structure.zip, all the network structures are given, each file having a name Net_R.dat, where R=1, 2… 20. The degree of each node (i.e., number of output connections) is the same for all network configurations, where the specific neighbors of each node are re-arranged randomly.

opencc-by-4.0Nov 2019View details →

Example dataset for openPMD-conform molecular dynamics data (MD domain extension)

This dataset results from the molecular dynamics (MD) simulation of the photon-sample interaction. The photons are propagated through the SASE1 beamline and the SPB-SFX instrument at European XFEL, with an initial energy of 5 keV. The sample is the two-nitrogenase iron protein (2nip) with 4348 atoms. The simulation is performed with a demo version of XMDYN. The datasets were rewritten from the original XMDYN output into an hdf5 format that complies with the openPMD metadata standard for particle and mesh data and the proposed domain extension of this standard for MD data. The dataset "pure_2nip_pmi_out.opmd.h5" conforms the  openPMD metadata MD domain extension strictly, while the dataset "pure_2nip_pmi_out.opmd.ff.h5" stores form factor results additionally for SingFEL diffraction simulation. This dataset is part of the Deliverable D5.1 in Workpackage 5 (Virtual Neutron and X-ray Laboratory) of the Photon and Neutron Open Science Cloud (PaNOSC). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 823852.

opencc-zeroAug 2024View details →

EOL Dynamic Hierarchy Trunk (trunk): EOL Dynamic Hierarchy Trunk January 2021

This is the trunk for the EOL reference hierarchy. It determines the relationships among the higher taxa and adds a few taxa that are not covered by other resources. The EOL DH trunk is maintained in [TTT](http://ttt.biodinfo.org/) developed by Colin (Congtian Lin) and Jiangning Wang from Biodiversity Informatics Group of the Institute of Zoology, Chinese Academy of Sciences. ##References Adl, S. M., et al. 2019. Revisions to the classification, nomenclature, and diversity of eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. https://doi.org/10.1111/jeu.12691 Aguiar, A.P., Deans, A.R., Engel, M.S., Forshage, M., Huber, J.T., Jennings, J.T., Johnson, N.F., Lelej, A.S., Longino, J.T., Lohrmann, V., Mikó, I., Ohl, M., Rasmussen, C., Taeger, A., Yu, D.S.K., 2013. Order Hymenoptera . In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). 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Higher-level phylogeny of paraneopteran insects inferred from mitochondrial genome sequences. Scientific Reports 5. https://doi.org/10.1038/srep08527 Lozano-Fernandez, J., Tanner, A.R., Giacomelli, M., Carton, R., Vinther, J., Edgecombe, G.D., Pisani, D., 2019. Increasing species sampling in chelicerate genomic-scale datasets provides support for monophyly of Acari and Arachnida. Nature Communications 10, 2295. https://doi.org/10.1038/s41467-019-10244-7 Malm, T., Nyman, T., 2015. Phylogeny of the symphytan grade of Hymenoptera: new pieces into the old jigsaw(fly) puzzle. Cladistics 31, 1–17. https://doi.org/10.1111/cla.12069 Marlétaz, Ferdinand, Katja T. C. A. Peijnenburg, Taichiro Goto, Noriyuki Satoh, and Daniel S. Rokhsar. 2019. A New Spiralian Phylogeny Places the Enigmatic Arrow Worms among Gnathiferans. Current Biology 29(2):312-318.e3. https://doi.org/10.1016/j.cub.2018.11.042. Nakano, T., Ramlah, Z., Hikida, T., 2012. Phylogenetic position of gastrostomobdellid leeches (Hirudinida, Arhynchobdellida, Erpobdelliformes) and a new family for the genus Orobdella. Zoologica Scripta 41, 177–185. https://doi.org/10.1111/j.1463-6409.2011.00506.x Naylor, G.J.P., Caira, J.N., Jensen, K.R.E., Rosana, K.M., Straube, N., Lakner, C., 2012. Elasmobranch Phylogeny: A Mitochondrial Estimate Based on 595 Species. In J.C. Carrier, J.A. Musick and M.R. Heithaus (editors), The Biology of Sharks and Their Relatives. 31-56. CRC Press, Taylor & Francis Group. Nesbitt, S.J., 2011. The Early Evolution of Archosaurs: Relationships and the Origin of Major Clades. Bulletin of the American Museum of Natural History, 2011(352):1-292. https://doi.org/10.1206/352.1 Nesnidal, Maximilian P., Martin Helmkampf, Achim Meyer, Alexander Witek, Iris Bruchhaus, Ingo Ebersberger, Thomas Hankeln, Bernhard Lieb, Torsten H. Struck, and Bernhard Hausdorf. 2013. New Phylogenomic Data Support the Monophyly of Lophophorata and an Ectoproct-Phoronid Clade and Indicate That Polyzoa and Kryptrochozoa Are Caused by Systematic Bias. BMC Evolutionary Biology 13(1): 253. https://doi.org/10.1186/1471-2148-13-253. Oaks, J.R., 2011. A Time-Calibrated Species Tree of Crocodylia Reveals a Recent Radiation of the True Crocodiles. Evolution 65, 3285–3297. https://doi.org/10.1111/j.1558-5646.2011.01373.x Okamura, B., Gruhl, A., Reft, A.J., 2015. Cnidarian Origins of the Myxozoa, in: Okamura, B., Gruhl, A., Bartholomew, J.L. (Eds.), Myxozoan Evolution, Ecology and Development. Springer International Publishing, Cham, pp. 45–68. https://doi.org/10.1007/978-3-319-14753-6_3 Pyron, R.A., Burbrink, F.T., Wiens, J.J., 2013. A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes. BMC Evolutionary Biology 13, 93. https://doi.org/10.1186/1471-2148-13-93 Robertson, J.A., Ślipiński, A., Moulton, M., Shockley, F.W., Giorgi, A., Lord, N.P., Mckenna, D.D., Tomaszewska, W., Forrester, J., Miller, K.B., Whiting, M.F., Mchugh, J.V., 2015. Phylogeny and classification of Cucujoidea and the recognition of a new superfamily Coccinelloidea (Coleoptera: Cucujiformia): Systematics of Cucujoidea and Coccinelloidea. Systematic Entomology 40, 745–778. https://doi.org/10.1111/syen.12138 Rouse, Greg W., Nerida G. Wilson, Jose I. Carvajal, and Robert C. Vrijenhoek. 2016. New Deep-Sea Species of Xenoturbella and the Position of Xenacoelomorpha. Nature 530(7588):94–97. https://doi.org/10.1038/nature16545. Ruhfel, B.R., Gitzendanner, M.A., Soltis, P.S., Soltis, D.E., Burleigh, J.G., 2014. From algae to angiosperms–inferring the phylogeny of green plants (Viridiplantae) from 360 plastid genomes. BMC Evolutionary Biology 14, 23. https://doi.org/10.1186/1471-2148-14-23 Schiffer, Philipp H., Helen E. Robertson, and Maximilian J. Telford. 2018. Orthonectids Are Highly Degenerate Annelid Worms. Current Biology 28(12):1970-1974.e3. https://doi.org/10.1016/j.cub.2018.04.088. The Angiosperm Phylogeny Group, 2016. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20. https://doi.org/10.1111/boj.12385 Van Nieukerken, E.J., Kaila, L., Kitching, I.J., Kristensen, N.P., Lees, D.C., Minet, J., Mitter, C., Mutanen, M., Regier, J.C., Simonsen, T.J., Wahlberg, N., Yen, S.-H., Zahiri, R., Adamski, D., Baixeras, J., Bartsch, D., Bengtsson, B.Å., Brown, J.W., Bucheli, S.R., Davis, D.R., Prins, J.D., Prins, W.D., Epstein, M.E., Gentili-Poole, P., Gielis, C., Hättenschwiler, P., Hausmann, A., Holloway, J.D., Kallies, A., Karsholt, O., Kawahara, A.Y., Koster, S.J.C., Kozlov, M.V., Lafontaine, J.D., Lamas, G., Landry, J.-F., Lee, S., Nuss, M., Park, K.-T., Penz, C., Rota, J., Schintlmeister, A., Schmidt, B.C., Sohn, J.-C., Solis, M.A., Tarmann, G.M., Warren, A.D., Weller, S., Yakovlev, R.V., Zolotuhin, V.V., Zwick, A., 2011. Order Lepidoptera Linnaeus, 1758. In: Zhang, Z.-Q. (Ed.) Animal biodiversity: An outline of higher-level classification and survey of taxonomic richness. Zootaxa 3148, 212. https://doi.org/10.11646/zootaxa.3148.1.41 Vea, I.M., Grimaldi, D.A., 2015. Diverse New Scale Insects (Hemiptera: Coccoidea) in Amber from the Cretaceous and Eocene with a Phylogenetic Framework for Fossil Coccoidea. novi 2015, 1–15. https://doi.org/10.1206/3823.1 Vélez-Zuazo, X., Agnarsson, I., 2011. Shark tales: A molecular species-level phylogeny of sharks (Selachimorpha, Chondrichthyes). Molecular Phylogenetics and Evolution 58, 207–217. https://doi.org/10.1016/j.ympev.2010.11.018 Weigert, A., Bleidorn, C., 2016. Current status of annelid phylogeny. Org Divers Evol 16, 345–362. https://doi.org/10.1007/s13127-016-0265-7 Weirauch, C., Schuh, R.T., 2011. Systematics and Evolution of Heteroptera: 25 Years of Progress. Annu. Rev. Entomol. 56, 487–510. https://doi.org/10.1146/annurev-ento-120709-144833 Wiegmann, B.M., Trautwein, M.D., Winkler, I.S., Barr, N.B., Kim, J.-W., Lambkin, C., Bertone, M.A., Cassel, B.K., Bayless, K.M., Heimberg, A.M., Wheeler, B.M., Peterson, K.J., Pape, T., Sinclair, B.J., Skevington, J.H., Blagoderov, V., Caravas, J., Kutty, S.N., Schmidt-Ott, U., Kampmeier, G.E., Thompson, F.C., Grimaldi, D.A., Beckenbach, A.T., Courtney, G.W., Friedrich, M., Meier, R., Yeates, D.K., 2011. Episodic radiations in the fly tree of life. Proceedings of the National Academy of Sciences 108, 5690–5695. https://doi.org/10.1073/pnas.1012675108 Winterton, S.L., Hardy, N.B., Wiegmann, B.M., 2010. On wings of lace: phylogeny and Bayesian divergence time estimates of Neuropterida (Insecta) based on morphological and molecular data. Systematic Entomology 35, 349–378. https://doi.org/10.1111/j.1365-3113.2010.00521.x Yuri, T., Kimball, R.T., Harshman, J., Bowie, R.C.K., Braun, M.J., Chojnowski, J.L., Han, K.-L., Hackett, S.J., Huddleston, C.J., Moore, W.S., Reddy, S., Sheldon, F.H., Steadman, D.W., Witt, C.C., Braun, E.L., 2013. Parsimony and Model-Based Analyses of Indels in Avian Nuclear Genes Reveal Congruent and Incongruent Phylogenetic Signals. Biology 2, 419–444. https://doi.org/10.3390/biology2010419 Zverkov, Oleg A., Kirill V. Mikhailov, Sergey V. Isaev, Leonid Y. Rusin, Olga V. Popova, Maria D. Logacheva, Alexey A. Penin, et al. 2019. Dicyemida and Orthonectida: Two Stories of Body Plan Simplification. Frontiers in Genetics 10. https://doi.org/10.3389/fgene.2019.00443.The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](https://eol.org/docs/eol-dynamic-hierarchy)

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EOL Dynamic Hierarchy Trunk (trunk): Dynamic Hierarchy Trunk 25 April 2017

This is the trunk for the EOL reference hierarchy. It determines the relationships among the higher taxa and adds a few taxa that are not covered by other resources. The EOL DH trunk is maintained in [TTT](http://ttt.biodinfo.org/) developed by Colin (Congtian Lin) and Jiangning Wang from Biodiversity Informatics Group of the Institute of Zoology, Chinese Academy of Sciences. ##References Adl, S. M., et al. 2019. Revisions to the classification, nomenclature, and diversity of eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. https://doi.org/10.1111/jeu.12691 Aguiar, A.P., Deans, A.R., Engel, M.S., Forshage, M., Huber, J.T., Jennings, J.T., Johnson, N.F., Lelej, A.S., Longino, J.T., Lohrmann, V., Mikó, I., Ohl, M., Rasmussen, C., Taeger, A., Yu, D.S.K., 2013. Order Hymenoptera . In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). 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Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346, 1320–1331. https://doi.org/10.1126/science.1253451 Kathirithamby, J., Engel, M.S., 2014. A Revised Key to the Living and Fossil Families of Strepsiptera, with the Description of a New Family, Cretostylopidae. Journal of the Kansas Entomological Society 87, 385–388. https://doi.org/10.2317/JKES140407.1 Kjer, K.M., Simon, C., Yavorskaya, M., Beutel, R.G., 2016. Progress, pitfalls and parallel universes: a history of insect phylogenetics. Journal of The Royal Society Interface 13, 20160363. https://doi.org/10.1098/rsif.2016.0363 Klopfstein, S., Vilhelmsen, L., Heraty, J.M., Sharkey, M., Ronquist, F., 2013. The Hymenopteran Tree of Life: Evidence from Protein-Coding Genes and Objectively Aligned Ribosomal Data. PLoS ONE 8, e69344. https://doi.org/10.1371/journal.pone.0069344 Kocot, Kevin M., Torsten H. Struck, Julia Merkel, Damien S. Waits, Christiane Todt, Pamela M. Brannock, David A. Weese, et al. 2016. Phylogenomics of Lophotrochozoa with Consideration of Systematic Error. Systematic Biology, syw079. https://doi.org/10.1093/sysbio/syw079. Laumer, Christopher E., Rosa Fernández, Sarah Lemer, David Combosch, Kevin M. Kocot, Ana Riesgo, Sónia C. S. Andrade, Wolfgang Sterrer, Martin V. Sørensen, and Gonzalo Giribet. 2019. Revisiting Metazoan Phylogeny with Genomic Sampling of All Phyla. Proceedings of the Royal Society B: Biological Sciences 286 (1906): 20190831. https://doi.org/10.1098/rspb.2019.0831. Laumer, Christopher E., Nicolas Bekkouche, Alexandra Kerbl, Freya Goetz, Ricardo C. Neves, Martin V. Sørensen, Reinhardt M. Kristensen, et al. 2015. Spiralian Phylogeny Informs the Evolution of Microscopic Lineages. Current Biology 25(15): 2000–2006. https://doi.org/10.1016/j.cub.2015.06.068. Leschen, R.A.B., Beutel, R.G., 2014. Morphology and Systematics: Phytophaga. Walter de Gruyter. Li, H., Shao, R., Song, N., Song, F., Jiang, P., Li, Z., Cai, W., 2015. Higher-level phylogeny of paraneopteran insects inferred from mitochondrial genome sequences. Scientific Reports 5. https://doi.org/10.1038/srep08527 Lozano-Fernandez, J., Tanner, A.R., Giacomelli, M., Carton, R., Vinther, J., Edgecombe, G.D., Pisani, D., 2019. Increasing species sampling in chelicerate genomic-scale datasets provides support for monophyly of Acari and Arachnida. Nature Communications 10, 2295. https://doi.org/10.1038/s41467-019-10244-7 Malm, T., Nyman, T., 2015. Phylogeny of the symphytan grade of Hymenoptera: new pieces into the old jigsaw(fly) puzzle. Cladistics 31, 1–17. https://doi.org/10.1111/cla.12069 Marlétaz, Ferdinand, Katja T. C. A. Peijnenburg, Taichiro Goto, Noriyuki Satoh, and Daniel S. Rokhsar. 2019. A New Spiralian Phylogeny Places the Enigmatic Arrow Worms among Gnathiferans. Current Biology 29(2):312-318.e3. https://doi.org/10.1016/j.cub.2018.11.042. Nakano, T., Ramlah, Z., Hikida, T., 2012. Phylogenetic position of gastrostomobdellid leeches (Hirudinida, Arhynchobdellida, Erpobdelliformes) and a new family for the genus Orobdella. Zoologica Scripta 41, 177–185. https://doi.org/10.1111/j.1463-6409.2011.00506.x Naylor, G.J.P., Caira, J.N., Jensen, K.R.E., Rosana, K.M., Straube, N., Lakner, C., 2012. Elasmobranch Phylogeny: A Mitochondrial Estimate Based on 595 Species. In J.C. Carrier, J.A. Musick and M.R. Heithaus (editors), The Biology of Sharks and Their Relatives. 31-56. CRC Press, Taylor & Francis Group. Nesbitt, S.J., 2011. The Early Evolution of Archosaurs: Relationships and the Origin of Major Clades. Bulletin of the American Museum of Natural History, 2011(352):1-292. https://doi.org/10.1206/352.1 Nesnidal, Maximilian P., Martin Helmkampf, Achim Meyer, Alexander Witek, Iris Bruchhaus, Ingo Ebersberger, Thomas Hankeln, Bernhard Lieb, Torsten H. Struck, and Bernhard Hausdorf. 2013. New Phylogenomic Data Support the Monophyly of Lophophorata and an Ectoproct-Phoronid Clade and Indicate That Polyzoa and Kryptrochozoa Are Caused by Systematic Bias. BMC Evolutionary Biology 13(1): 253. https://doi.org/10.1186/1471-2148-13-253. Oaks, J.R., 2011. A Time-Calibrated Species Tree of Crocodylia Reveals a Recent Radiation of the True Crocodiles. Evolution 65, 3285–3297. https://doi.org/10.1111/j.1558-5646.2011.01373.x Okamura, B., Gruhl, A., Reft, A.J., 2015. Cnidarian Origins of the Myxozoa, in: Okamura, B., Gruhl, A., Bartholomew, J.L. (Eds.), Myxozoan Evolution, Ecology and Development. Springer International Publishing, Cham, pp. 45–68. https://doi.org/10.1007/978-3-319-14753-6_3 Pyron, R.A., Burbrink, F.T., Wiens, J.J., 2013. A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes. BMC Evolutionary Biology 13, 93. https://doi.org/10.1186/1471-2148-13-93 Robertson, J.A., Ślipiński, A., Moulton, M., Shockley, F.W., Giorgi, A., Lord, N.P., Mckenna, D.D., Tomaszewska, W., Forrester, J., Miller, K.B., Whiting, M.F., Mchugh, J.V., 2015. Phylogeny and classification of Cucujoidea and the recognition of a new superfamily Coccinelloidea (Coleoptera: Cucujiformia): Systematics of Cucujoidea and Coccinelloidea. Systematic Entomology 40, 745–778. https://doi.org/10.1111/syen.12138 Rouse, Greg W., Nerida G. Wilson, Jose I. Carvajal, and Robert C. Vrijenhoek. 2016. New Deep-Sea Species of Xenoturbella and the Position of Xenacoelomorpha. Nature 530(7588):94–97. https://doi.org/10.1038/nature16545. Ruhfel, B.R., Gitzendanner, M.A., Soltis, P.S., Soltis, D.E., Burleigh, J.G., 2014. From algae to angiosperms–inferring the phylogeny of green plants (Viridiplantae) from 360 plastid genomes. BMC Evolutionary Biology 14, 23. https://doi.org/10.1186/1471-2148-14-23 Schiffer, Philipp H., Helen E. Robertson, and Maximilian J. Telford. 2018. Orthonectids Are Highly Degenerate Annelid Worms. Current Biology 28(12):1970-1974.e3. https://doi.org/10.1016/j.cub.2018.04.088. The Angiosperm Phylogeny Group, 2016. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. 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The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](https://eol.org/docs/eol-dynamic-hierarchy)