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3,630 results for “Forming”
Symbol Representation of the Three Gluon Form Factor in N=4 Planar Super Yang-Mills Theory
<p>Datasets describing the symbol of the three-gluon form factor in N=4 planar super Yang-Mills theory, generated using the amplitude bootstrap approach. The file "EZ_symb_new_norm" contains the symbol form of this quantity at 1 through 5 loops of precision, while the file "EZ6_symb_new_norm" contains the symbol at 6 loops. The file "EZ_symb_quad_new_norm" contains the symbol at 1 through 6 loops in compressed "quad" form, where the final-entry conditions described in (https://arxiv.org/pdf/2204.11901) are used to dramatically reduce the total number of terms in the symbol. The file "EZ7_symb_quad_new_norm" contains the symbol at 7 loops in the "quad" form. </p> <p>The tag “new_norm” refers to the fact that in the symbols given here, the letters a,b,c are defined by a = sqrt(u/(v*w)), b = sqrt(v/(w*u)), c = sqrt(w/(u*v)), as in arXiv:2405.06107, in order to make all coefficients integers. In contrast, in arXiv:2204.11901, the letters a,b,c were defined by a = u/(v*w), b = v/(w*u), c = w/(u*v).</p> <p>In addition to the funding sources listed, MW was supported by research grant 00025445 from Villum Fonden.</p>
Viewing behavior and vertical eye-level light for non-image-forming effects
<p>When considering non-image-forming (NIF) light effects on people, knowing the light vertically at eye-level is necessary. However, people are dynamic in their behavior and constantly change their viewing direction. This means that light measured vertically towards a constant direction might differ from the actual light that reaches people’s eyes. If the difference is large, viewing behavior might need to be included in lighting design measurements and simulations predicting the potential of the light to induce NIF light effects. This dataset was collected during an experiment on the difference between the actual dynamic eye-level light of office workers while seated at a desk (dynamic condition) and light measured statically towards a computer screen (static condition). The dataset was collected to test the hypothesis: "There is a significant and relevant difference between simultaneously measured static and dynamic light conditions in an office environment occupied by one user." It includes measured and simulated light quantities (illuminance, alpha-opic quantities according to CIE S026 and light-driven alertness according to the non-visual direct response model) together with participants' measured face orientation (horizontal and vertical) in an office environment with a single user.</p>
Correlator data for determination of the I=1 pion-pion scattering amplitude and timelike pion form factor from Nf=2+1 lattice QCD
<p>Bootstrap samples of all correlation functions involved in the analysis of pion-pion scattering data and the timelike pion form factor described in "The I =1 pion-pion scattering amplitude and timelike pion form factor from N f = 2 + 1 lattice QCD". Additionally, an analysis file is provided for each ensemble which stored the analysis choices made in that work. These data are intended for use with the Jupyter notebook located in https://github.com/ebatz/jupan, which provides an interface. This notebook performs the entire analysis chain discussed in the above paper. </p>
Promiscuity cliffs (PCs), promiscuity cliff pathways (PCPs), and promiscuity hubs (PHs) formed by inhibitors of human kinases
<p>The PC, PCP, and PH data structures have been introduced for the analysis of compound promiscuity [1-3]. A comprehensive collection of PCs, PCPs, and PHs formed by kinase inhibitors covering more than 80% of the human kinome is made available. See readme.txt for more information regarding the provided files.</p> <p>References:</p> <ol> <li>Dimova, D.; Gilberg, E.; Bajorath, J. Identification and Analysis of Promiscuity Cliffs Formed by Bioactive Compounds and Experimental Implications. RSC Adv. 2017, 7, 58–66.</li> <li>Miljković, F.; Bajorath, J. Computational Analysis of Kinase Inhibitors Identifies Promiscuity Cliffs across the Human Kinome. ACS Omega 2018, 3, 17295–17308.</li> <li>Miljković, F; Vogt, M; Bajorath, J. Systematic Computational Identification of Promiscuity Cliff Pathways Formed by Inhibitors of the Human Kinome. J. Comput. Aided Mol. Des. 2019, in press, doi: doi.org/10.1007/s10822-019-00198-9</li> </ol>
The terrestrial carnivorous plant Utricularia reniformis sheds light on environmental and life-form genome plasticity: Annotation, Gene Ontology and raw data
<p><strong>Description:</strong> In this work, we deeply sequenced (genome and transcriptome of different organs), assembled, and analyzed the 311-Mbp genome of the terrestrial carnivorous plant <em>U. reniformis</em> (Lentibulariaceae). This project presents great importance to the understanding of genomic, evolutive and functional aspects of<em> U. reniformis</em>, which may, with the next-generation sequencing and computational biology approaches shed light to a better understanding not only for the biology and evolution of <em>Utricularia</em> genus, but also for other genera and lineages of the Lentibulariaceae family. Here we present all the raw data generated, including annotation and gene ontology files.</p> <p><strong>External Information</strong></p> <p><a href="https://genomevolution.org/coge/GenomeInfo.pl?gid=54799">Genome Browser</a> avaliable at CoGe Portal (https://genomevolution.org/coge/GenomeInfo.pl?gid=54799)</p> <p><a href="http://https://www.ncbi.nlm.nih.gov/bioproject/290588">GenBank </a><a href="http://https://www.ncbi.nlm.nih.gov/bioproject/290588">Bioproject</a> (https://www.ncbi.nlm.nih.gov/bioproject/290588) for raw genomic and transcriptomic reads</p> <p><a href="https://bv.fapesp.br/en/auxilios/84264/genomics-and-transcriptomics-of-utricularia-reniformis-lentibulariaceae-an-evolutive-and-function/">FAPESP grant website</a> contaning the project abstract and other information.</p> <p><strong>Papers published related to <em>Utricularia reniformis</em> genome</strong></p> <pre><strong>[1]</strong> Silva SR, Diaz YC, Penha HA, Pinheiro DG, Fernandes CC, Miranda VF, MichaelTP, Varani AM. <strong>The Chloroplast Genome of Utricularia reniformis Sheds Light on the Evolution of the ndh Gene Complex of Terrestrial Carnivorous Plants from the Lentibulariaceae Family</strong>. PLoS One. 2016 Oct 20;11(10):e0165176. doi:<strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/27764252">10.1371/journal.pone.0165176</a></strong>. </pre> <pre><strong>[2] </strong>Silva SR, Alvarenga DO, Aranguren Y, Penha HA, Fernandes CC, Pinheiro DG, Oliveira MT, Michael TP, Miranda VFO, Varani AM. <strong>The mitochondrial genome of the terrestrial carnivorous plant Utricularia reniformis (Lentibulariaceae): Structure, comparative analysis and evolutionary landmarks.</strong> PLoS One. 2017 Jul19;12(7):e0180484. doi: <strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/28723946">10.1371/journal.pone.0180484</a></strong>.</pre> <pre><strong>[3] </strong>Silva SR, Moraes AP, Penha HA, Julião MHM, Domingues DS, Michael TP, Miranda VFO, Varani AM. <strong>The Terrestrial Carnivorous Plant Utricularia reniformis Sheds Light on Environmental and Life-Form Genome Plasticity.</strong> Int J Mol Sci. 2019 Dec 18;21(1). pii: E3. doi: <strong><a href="https://www.ncbi.nlm.nih.gov/pubmed/31861318">10.3390/ijms21010003</a></strong>.</pre> <p><strong>Acknowledgements</strong></p> <p>This work was supported by Sao Paulo Research Foundation FAPESP, Grant ID: [1325164-6]</p> <p> </p> <p><strong>---------------------------------------------------------</strong><br> <strong>FILES DESCRIPTION</strong><br> <strong>---------------------------------------------------------</strong><br> <br> ----------------<br> <strong>ANNOT-vFinal.sql: </strong>MySQL database containing all integrated annotation information of Urenif and Ugibba<br> ----------------<br> <strong>TABLE fields description</strong><br> gene_name gene name generated by EVidence Modeler + PASA<br> length gene lenght<br> status duplicate_gene_classifier status (0:singleton, 1:dispersed, 2:proximal, 3: tandem, 4:WGD)<br> product gene product <br> GOterms Blast2GO/OmicsBox GOterms<br> GO_mapping Blast2GO/OmicsBox GOterms derived from direct mapping (UniProt)<br> GO_annotation Blast2GO/OmicsBox annotated GOterms<br> GO_interpro Blast2GO/OmicsBox derived from InterProScan<br> EC Blast2GO/OmicsBox EC number<br> EC_name Blast2GO/OmicsBox enzyme name<br> NOG_annot EggNOG annotation description<br> NOG_EC EggNOG EC number<br> NOG_GO EggNOG GOterms<br> NOG_class EggNOG COG/KOG classfication<br> KEGG_Pathway EggNOG KEGG pathyways<br> KEGG_ko EggNOG KEGG ko<br> CAZy EggNOG CAZy enzymes<br> TAIR_gene Closest A. thaliana gene name (homologous) TAIR database lasted version<br> TAIR_annot Closest A. thaliana gene product (homologous) TAIR database lasted version <br> ortho MCL clustering among Vvinifera, Athaliana, and Slycopersicum (S:singleton, C: clustered, Y: shared)<br> ortho_two MCL clustering among Urenif and Ugibba (S:singleton, C: clustered, Y: shared)<br> -<br> -<br> ----------------<br> <strong>CEGs.zip </strong> 336 shared and concatenated CEGs from Urenif, U. gibba, Genlisea nigrocaulis, G. hispidula, G. aurea, G. pygmaea, and G. repens.<br> ----------------</p> <p><strong>ProcessRepeats_mod</strong> Modified version of RepeatMasker, ProcessRepeats script for detection of plant evolutionary lineages<br> ----------------</p> <p><strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> <em>Utricularia gibba</em> files<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong><br> <strong>Ugibba</strong><strong>-no-masked.fa </strong> Ugibba genome excluding organellar genomes (provided by Lan et al., 2017)<br> <strong>Ugibba-softmasked.fa</strong> Ugibba genome RepeatMasker softmasked and excluding organellar genomes (provided by Lan et al., 2017)<br> <strong>Ug.collinearity </strong> MCScanX collinearity file<br> <strong>Ug-duplicates.txt</strong> MCScanX duplicate_gene_classifier short report<br> <strong>Ug.gene_type </strong> MCScanX duplicate_gene_classifier full report<br> <strong>Ug.tandem </strong> Ugibba tandem genes generated by MCScanX tool<br> <strong>Ugibba_annot.annot </strong> Blast2GO/OmicsBox annotation file (eudicotyledons filtered and Viridiplantae GOSlim) <strong>Ugibba_annot-</strong><strong>noclean</strong><strong>.</strong><strong>annot</strong><strong> </strong> Blast2GO/OmicsBox annotation file (not filtered)<br> <strong>Ugibba</strong><strong>.cDNA</strong> Ugibba cDNAs fasta file<br> <strong>Ugibba</strong><strong>.CDS </strong> Ugibba CDSs fasta file<br> <strong>Ugibba</strong><strong>-EVM.all-no-TEs-PASA-ANNOTATED.gff3</strong> Ugibba GFF3 file fully annotated (including gene products and GO terms)</p> <p><strong>Ugibba</strong><strong>-EVM.all-no-TEs-PASA.gff3</strong> Ugibba GFF3 file fully annotated (genes only)<br> <strong>Ugibba_export.txt</strong> Blast2GO/OmicsBox full exported table<br> <strong>Ugibba_fasta.fasta</strong> Blast2GO/OmicsBox Ugibba fasta proteins containg annotation (product and GO terms)<br> <strong>ugibba_frozen_cleaned-validated.box</strong> Full Blast2GO/OmicsBox file</p> <p><strong>ugibba_frozen.box</strong> Full Blast2GO/OmicsBox file (containing TEs genes annotation)</p> <p><strong>ugibba_nogs_emapper_annotations.box</strong> Full Blast2GO/OmicsBox EggNOG file (containing TEs genes annotation)</p> <p><strong>Ugibba_GAF.txt</strong> GAF file<br> <strong>Ugibba</strong><strong>.gene</strong> Ugibba gene fasta file<br> <strong>Ugibba_GOstat.txt </strong> GOstat file<br> <strong>Ugibba</strong><strong>-PASA-assemblies.fasta </strong> Ugibba PASA assemblies<br> <strong>Ugibba</strong><strong>-PASA.stats </strong> Ugibba annotation STATS<br> <strong>Ugibba</strong><strong>.</strong><strong>prot</strong><strong> </strong> Ugibba protein fasta file<br> <strong>Ugibba</strong><strong>-RepeatMasker.gff </strong> Ugibba RepeatMasker gff file<br> <strong>Ugibba</strong><strong>-RepeatMasker.gff3 </strong> Ugibba RepeatMasker gff3 file<br> <strong>Ugibba</strong><strong>-RepeatMasker.tbl </strong> Ugibba RepeatMasker results<br> <strong>Ugibba</strong><strong>-RepeatMasker-v2.gff3</strong> Ugibba RepeatMasker gff3 second version file<br> <strong>Ugibba</strong><strong>-RNAseq-assembled.fasta </strong> Ugibba RNAseq assembled transcriptome (Trinity)<br> <strong>Ugibba_TEs_DANTE_2019.fa </strong> Ugibba TEs library, detected by REPET and annotated by PASTEC and DANTE<br> <strong>Ugibba_WEGO.txt </strong> WEGO file</p> <p><strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> <em>Utricularia reniformis</em> files<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong><br> <strong>Urenif</strong><strong>-no-masked.fa </strong> Urenif genome excluding organellar genomes<br> <strong>Urenif</strong><strong>-</strong><strong>softmasked</strong><strong>.fa</strong> Urenif genome RepeatMasker softmasked and excluding organellar genomes<br> <strong>Ur.collinearity </strong> MCScanX collinearity file<br> <strong>Ur-duplicates.txt </strong> MCScanX duplicate_gene_classifier short report<br> <strong>Ur.gene_type</strong> MCScanX duplicate_gene_classifier full report<br> <strong>Ur.tandem</strong> Urenif tandem genes generated by MCScanX tool<br> <strong>Urenif_annot.annot</strong> Blast2GO/OmicsBox annotation file (eudicotyledons filtered and Viridiplantae GOSlim)<br> <strong>Urenif_annot-</strong><strong>noclean</strong><strong>.</strong><strong>annot</strong> Blast2GO/OmicsBox annotation file (not filtered)<br> <strong>Urenif</strong><strong>.cDNA</strong> Urenif cDNAs fasta file<br> <strong>Urenif</strong><strong>.CDS </strong> Urenif cDNAs fasta file<br> <strong>Urenif</strong><strong>-EVM.all-no-TEs-PASA-ANNOTATED.gff3</strong> Urenif GFF3 file fully annotated (including gene products and GO terms)</p> <p><strong>Urenif</strong><strong>-EVM.all-no-TEs-PASA.gff3</strong> Urenif GFF3 file fully annotated (genes only)<br> <strong>Urenif_export.txt</strong> Blast2GO/OmicsBox full exported table<br> <strong>Urenif_fasta.fasta</strong> Blast2GO/OmicsBox Urenif fasta proteins containg annotation (product and GO terms)<br> <strong>urenif_frozen_cleaned-validated.box</strong> Full Blast2GO/OmicsBox file</p> <p><strong>urenif_frozen.box</strong> Full Blast2GO/OmicsBox file (containing TEs genes annotation)</p> <p><strong>urenif_nogs_emapper_annotations.box</strong> Full Blast2GO/OmicsBox EggNOG file (containing TEs genes annotation)<br> <strong>Urenif_GAF.txt </strong> GAF file<br> <strong>Urenif</strong><strong>.gene</strong> Urenif gene fasta file<br> <strong>Urenif_GOStat.txt </strong> GOstat file<br> <strong>Urenif</strong><strong>-PASA-assemblies.fasta</strong> Urenif PASA assemblies<br> <strong>Urenif</strong><strong>-PASA.stats </strong> Urenif annotation STATS<br> <strong>Urenif</strong><strong>.</strong><strong>prot</strong><strong> </strong> Urenif protein fasta file<br> <strong>Urenif</strong><strong>-RepeatMasker.gff </strong> Urenif RepeatMasker gff file<br> <strong>Urenif</strong><strong>-RepeatMasker.gff3 </strong> Urenif RepeatMasker gff3 file<br> <strong>Urenif</strong><strong>-RepeatMasker.tbl </strong> Urenif RepeatMasker results<br> <strong>Urenif</strong><strong>-RepeatMasker-v2.gff3 </strong> Urenif RepeatMasker gff3 second version file<br> <strong>Urenif</strong><strong>-RNAseq-assembled.fasta </strong> Urenif RNAseq assembled transcriptome (Trinity)<br> <strong>Urenif_TEs_DANTE_2019.fa </strong> Urenif TEs library, detected by REPET and annotated by PASTEC and DANTE<br> <strong>Urenif_WEGO.txt </strong> WEGO file<br> <strong>----------------------------------------------------------------------------------------------------------------------------------------------<br> ----------------------------------------------------------------------------------------------------------------------------------------------</strong></p>
EOL Dynamic Hierarchy, digest form, January 2019: Dynamic hierarchy digest January 2019
__Digest__ of the EOL dynamic hierarchy prepared by querying the online traits database. Unlike the full DH files, this file provides only the bare minimum information for each taxon: page id, parent page id, canonical name.<p></p>Zip file containing a README and a three-column CSV (pages.csv) with header row
NMNH Botany Plant Habit Data: NMNH Plant Growth Form Data
<p>Plant growth form data from specimen labels in the collections of the Smithsonian National Museum of Natural History Botany Department, revised draft.</p> <p> </p> <p>Excel version, revised March 2018. Recoded measurement types and values to FLOPO uris whenever possible.</p>
Cellularity & Growth Form: Old Version
<p>Cellularity & growth form data derived from the following sources: </p> <p>Abdullin, S.R., Bagmet, V.B., Nikulin, A.Y., Nikulin, V.Y., Gorpenchenko, T.Y., Grishin, S.Y., Allaguvatova, R.Z. and Gontcharov, A.A., 2022. Emended description of the genus Eremochloris (Trebouxiophyceae, Chlorophyta), with Eremochloris kamchatica sp. nov. from Kamchatka, Russia. Phycologia, 61(2), pp.175-183. <a href="<p></p>https://doi.org/10.1080/00318884.2021.2024710"></a></p><p></p><a href="<p></p>https://doi.org/10.1080/00318884.2021.2024710">https://doi.org/10.1080/00318884.2021.2024710</a><p></p> <p>Adl, S.M., Bass, D., Lane, C.E., Lukeš, J., Schoch, C.L., Smirnov, A., Agatha, S., Berney, C., Brown, M.W., Burki, F., Cárdenas, P., Čepička, I., Chistyakova, L., Campo, J. del, Dunthorn, M., Edvardsen, B., Eglit, Y., Guillou, L., Hampl, V., Heiss, A.A., Hoppenrath, M., James, T.Y., Karnkowska, A., Karpov, S., Kim, E., Kolisko, M., Kudryavtsev, A., Lahr, D.J.G., Lara, E., Gall, L.L., Lynn, D.H., Mann, D.G., Massana, R., Mitchell, E.A.D., Morrow, C., Park, J.S., Pawlowski, J.W., Powell, M.J., Richter, D.J., Rueckert, S., Shadwick, L., Shimano, S., Spiegel, F.W., Torruella, G., Youssef, N., Zlatogursky, V., Zhang, Q., 2019. Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. <a href="<p></p>https://doi.org/10.1111/jeu.12691"></a></p><p></p><a href="<p></p>https://doi.org/10.1111/jeu.12691">https://doi.org/10.1111/jeu.12691</a><p></p> <p>Alberghina, J.S., Vigna, M.S., Confalonieri, V.A., 2006. Phylogenetic position of the Oedogoniales within the green algae (Chlorophyta) and the evolution of the absolute orientation of the flagellar apparatus. Plant Syst. Evol. 261, 151–163. <a href="<p></p>https://doi.org/10.1007/s00606-006-0449-2"></a></p><p></p><a href="<p></p>https://doi.org/10.1007/s00606-006-0449-2">https://doi.org/10.1007/s00606-006-0449-2</a><p></p> <p>Amaral, R., Fawley, K.P., Němcová, Y., Ševčíková, T., Lukešová, A., Fawley, M.W., Santos, L.M. and Eliáš, M., 2020. Toward Modern Classification of Eustigmatophytes, Including the Description of Neomonodaceae Fam. Nov. and Three New Genera. Journal of Phycology, 56(3), pp.630-648. <a href="<p></p>https://doi.org/10.1111/jpy.12980"></a></p><p></p><a href="<p></p>https://doi.org/10.1111/jpy.12980">https://doi.org/10.1111/jpy.12980</a><p></p> <p>Andersen, R.A., 1987. Synurophyceae classis nov., a new class of algae. American journal of botany, 74(3), pp.337-353. <a href="<p></p>https://doi.org/10.2307/2443810"></a></p><p></p><a href="<p></p>https://doi.org/10.2307/2443810">https://doi.org/10.2307/2443810</a><p></p> <p>Antonio, M., Schulze-Makuch, D., 2012. Toward a New Understanding of Multicellularity. Hypotheses in the Life Sciences 2, 4–14. <a href="<p></p>http://www.hy-ls.org/index.php/hyls/article/view/89/0"></a></p><p></p><a href="<p></p>http://www.hy-ls.org/index.php/hyls/article/view/89/0">http://www.hy-ls.org/index.php/hyls/article/view/89/0</a><p></p> <p>Arneson, R.D., 1973. Pseudotetracystis, a new chlorosarcinean alga. Journal of Phycology, 9(1), pp.10-14. <a href="<p></p>https://doi.org/10.1111/j.1529-8817.1973.tb04056.x"></a></p><p></p><a href="<p></p>https://doi.org/10.1111/j.1529-8817.1973.tb04056.x">https://doi.org/10.1111/j.1529-8817.1973.tb04056.x</a><p></p> <p>Aslam, Z., Shin, W., Kim, M.K., Im, W.T. and Lee, S.T., 2007. Marinichlorella kaistiae gen. et sp. nov.(Trebouxiophyceae, Chlorophyta) based on polyphasic taxonomy. Journal of Phycology, 43(3), pp.576-584. <a href="<p></p>https://doi.org/10.1111/j.1529-8817.2007.00345.x"></a></p><p></p><a href="<p></p>https://doi.org/10.1111/j.1529-8817.2007.00345.x">https://doi.org/10.1111/j.1529-8817.2007.00345.x</a><p></p> <p>Badewitz, H. (2004). The genus Microcorycia Cockerell, 1911 (Testacealobosia, Rhizopoda, Protozoa). A critical monograph of the genus including a first description of a new species: Microcorycia scutella n. sp. Lauterbornia 50: 111-146. </p> <p>Bakker, M.E., De Jong, Y.S. and Lokhorst, G.M., 1997. The flagellar apparatus ultrastructure in Leptosira erumpens (Deason & Bold) lukesová and its contribution to the understanding of phylogenese relationships within the microthamniales (chlorophyta). Archiv für Protistenkunde, 148(1-2), pp.17-31. <a href="<p></p>https://doi.org/10.1016/S0003-9365(97)80033-4"></a></p><p></p><a href="<p></p>https://doi.org/10.1016/S0003-9365(97)80033-4">https://doi.org/10.1016/S0003-9365(97)80033-4</a><p></p> <p>Barcytė, D., Hodač, L. and Nedbalová, L., 2017. Lunachloris lukesovae gen. et sp. nov.(Trebouxiophyceae, Chlorophyta), a novel coccoid green alga isolated from soil in South Bohemia, Czech Republic. European Journal of Phycology, 52(3), pp.281-291. <a href="<p></p>https://doi.org/10.1080/09670262.2017.1283541"></a></p><p></p><a href="<p></p>https://doi.org/10.1080/09670262.2017.1283541">https://doi.org/10.1080/09670262.2017.1283541</a><p></p> <p>Barsanti, L., Frassanito, A.M., Passarelli, V., Evangelista, V., Etebari, M., Paccagnini, E., Lupetti, P., Lenzi, P., Verni, F. and Gualtieri, P., 2013. Tetraflagellochloris mauritanica gen. et sp. nov.(Chlorophyceae), a new flagellated alga from the mauritanian desert: morphology, ultrastructure, and phylogenetic framing. Journal of Phycology, 49(1), pp.178-193. <a href="<p></p>https://doi.org/10.1111/j.1529-8817.2012.01232.x"></a></p><p></p><a href="<p></p>https://doi.org/10.1111/j.1529-8817.2012.01232.x">https://doi.org/10.1111/j.1529-8817.2012.01232.x</a><p></p> <p>Bass, D., Chao, E.E.-Y., Nikolaev, S., Yabuki, A., Ishida, K., Berney, C., Pakzad, U., Wylezich, C., Cavalier-Smith, T., 2009. Phylogeny of Novel Naked Filose and Reticulose Cercozoa: Granofilosea cl. n. and Proteomyxidea Revised. Protist 160, 75–109. <a href="<p></p>https://doi.org/10.1016/j.protis.2008.07.002"></a></p><p></p><a href="<p></p>https://doi.org/10.1016/j.protis.2008.07.002">https://doi.org/10.1016/j.protis.2008.07.002</a><p></p> <p>Becker, B., Marin, B., 2009. Streptophyte algae and the origin of embryophytes. Annals of Botany 103, 999–1004. <a href="<p></p>https://doi.org/10.1093/aob/mcp044"></a></p><p></p><a href="<p></p>https://doi.org/10.1093/aob/mcp044">https://doi.org/10.1093/aob/mcp044</a><p></p> <p>Bernard, Catherine, Alastair G. B. Simpson & David J. Patterson (2000) Some free-living flagellates (protista) from anoxic habitats Ophelia 52(2):113-142. <a href="<p></p>https://doi.org/10.1080/00785236.1999.10409422"></a></p><p></p><a href="<p></p>https://doi.org/10.1080/00785236.1999.10409422">https://doi.org/10.1080/00785236.1999.10409422</a><p></p> <p>Berney, C., Geisen, S., Van Wichelen, J., Nitsche, F., Vanormelingen, P., Bonkowski, M. and Bass, D., 2015. Expansion of the __reticulosphere__: diversity of novel branching and network-forming amoebae helps to define Variosea (Amoebozoa). Protist, 166(2):271-295. <a href="<p></p>https://doi.org/10.1016/j.protis.2015.04.001"></a></p><p></p><a href="<p></p>https://doi.org/10.1016/j.protis.2015.04.001">https://doi.org/10.1016/j.protis.2015.04.001</a><p></p> <p>Biard, T., 2022. Diversity and ecology of Radiolaria in modern oceans. 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Cellularity & Growth Form Data Version April 2023
<p>Cellularity & growth form data derived from the following sources: </p> <p>Abdullin, S.R., Bagmet, V.B., Nikulin, A.Y., Nikulin, V.Y., Gorpenchenko, T.Y., Grishin, S.Y., Allaguvatova, R.Z. and Gontcharov, A.A., 2022. Emended description of the genus Eremochloris (Trebouxiophyceae, Chlorophyta), with Eremochloris kamchatica sp. nov. from Kamchatka, Russia. 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The genus Microcorycia Cockerell, 1911 (Testacealobosia, Rhizopoda, Protozoa). A critical monograph of the genus including a first description of a new species: Microcorycia scutella n. sp. Lauterbornia 50: 111-146. </p> <p>Bakker, M.E., De Jong, Y.S. and Lokhorst, G.M., 1997. The flagellar apparatus ultrastructure in Leptosira erumpens (Deason & Bold) lukesová and its contribution to the understanding of phylogenese relationships within the microthamniales (chlorophyta). Archiv für Protistenkunde, 148(1-2), pp.17-31. <a href="https://doi.org/10.1016/S0003-9365(97)80033-4">https://doi.org/10.1016/S0003-9365(97)80033-4</a></p> <p>Barcytė, D., Hodač, L. and Nedbalová, L., 2017. Lunachloris lukesovae gen. et sp. nov.(Trebouxiophyceae, Chlorophyta), a novel coccoid green alga isolated from soil in South Bohemia, Czech Republic. 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Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service. </p> <p>Bovee, E.C., 1953. Oscillosignum nov. gen. proboscidium nov. sp., type form of its genus, family Mayorellidae, order Amoebida. Transactions of the American Microscopical Society, 72(4):328-332. <a href="https://doi.org/10.2307/3223477">https://doi.org/10.2307/3223477</a></p> <p>Bovee, E.C., 1985. The lobose amebas: III. Descriptions of nine new conopodous amebas of the genus Vexillifera Schaeffek, 1926, emd. Bovee 1951, 1970, with comments on the genus. Archiv für Protistenkunde, 129(1-4):101-118. <a href="https://doi.org/10.1016/S0003-9365(85)80013-0">https://doi.org/10.1016/S0003-9365(85)80013-0</a></p> <p>Brown, M.W., Silberman, J.D. (2013). The Non-dictyostelid Sorocarpic Amoebae. In: Romeralo, M., Baldauf, S., Escalante, R. (eds) Dictyostelids. 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Hiding in plain sight: Koshicola spirodelophila gen. et sp. nov.(Chaetopeltidales, Chlorophyceae), a novel green alga associated with the aquatic angiosperm Spirodela polyrhiza. American Journal of Botany, 103(5), pp.865-875. <a href="https://doi.org/10.3732/ajb.1500481">https://doi.org/10.3732/ajb.1500481</a></p> <p>Watanabe, S., Mitui, K., Nakayama, T. and Inouye, I., 2002. Phylogenetic analyses of the species of Chlorosarcinopsis and Neochlorosarcina (Chlorophyceae). Journal of Phycology, 38, pp.36-36. <a href="https://doi.org/10.1046/j.1529-8817.38.s1.103.x">https://doi.org/10.1046/j.1529-8817.38.s1.103.x</a></p> <p>Wetherbee, R. and Verbruggen, H., 2016. Kraftionema allantoideum, a new genus and family of Ulotrichales (Chlorophyta) adapted for survival in high intertidal pools. 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Plant Systematics and Evolution, 230(3), pp.161-171. <a href="https://doi.org/10.1007/s006060200002">https://doi.org/10.1007/s006060200002</a></p> <p>Wujek, D.E. The first occurrence of the coccoid green alga Borodinella polytetras. Miller in North America (Michigan). Great Lakes Bot. 59(3-4):94-98. <a href="http://hdl.handle.net/2027/spo.0497763.0058.107">http://hdl.handle.net/2027/spo.0497763.0058.107</a></p> <p>Wujek, D.E., 2016. The chlorococcalean Green Alga Hydrianum Rabenhorst from North America (Kansas and Michigan). Transactions of the Kansas Academy of Science, 119(1), pp.105-108. <a href="https://www.jstor.org/stable/24887848">https://www.jstor.org/stable/24887848</a></p> <p>Yoon H.S. et al. (2016) Rhodophyta. In: Archibald J. et al. (eds) Handbook of the Protists. Springer, Cham. <a href="https://doi.org/10.1007/978-3-319-32669-6_33-1">https://doi.org/10.1007/978-3-319-32669-6_33-1</a></p>
Research data for "Intermediates of Forming Transition Metal Dichalcogenides Heterostructures Revealed by Machine Learning Simulations"
<p>This dataset supports the paper "Intermediates of Forming Transition Metal Dichalcogenides Heterostructures Revealed by Machine Learning Simulations". </p> <p><strong>Included Files:</strong></p> <ul> <li><strong>ocp_active.zip</strong>: Modified version of ocp (https://github.com/Open-Catalyst-Project/ocp) tailored for active learning applications.</li> <li><strong>deployed.pth</strong>: Pre-trained model used in the experiments.</li> <li><strong>chemiscopy_run.py</strong>: Script integrating the chemiscopy and nequip modules, designed for dataset visualization.</li> <li><strong>new_energy.py</strong>: Modified version of the nequip module, featuring a repulsive potential function.</li> <li><strong>test_datasets.extxyz</strong> & <strong>train_datasets.extxyz</strong>: The test and training datasets in extxyz format.</li> </ul> <p>How to use the modified version of the nequip module:</p> <p>To train this version of the potential function, it is recommended to use nequip<=0.5.6 (on Linux). The NequIP training files need to be updated as follows:</p> <pre><code>model_builders: - new_energy.EnergyModel - StressForceOutput min_bond_len: 1.8</code></pre> <p>Then run:</p> <p><code>export PYTHONPATH=${PYTHONPATH}:$PWD</code><br><code>nequip-train config.yml # Train the potential function</code><br><code>nequip-deploy build --train-dir nequipresultsdir build.pth # Deploy the trained model</code></p>
Coarse-grained molecular dynamics simulations of SARS-CoV-2 envelope protein E in the pentameric form
<p>The trajectories of coarse-grained (CG) molecular dynamics (MD) simulations of<br> 1) unmodified (FeigLab_NMR; FeigLab_PentamerNoPTM_POPC_Martini3b: 5 μs; 5 μs); <br> 2) palmitoylated (FeigLab_PentamerCYSP43; PentamerCYSP44_POPC_Martini3b: 5 μs; 5 μs); <br> SARS-CoV-2 E protein pentamer in a POPC bilayer.</p> <p>The trajectory of CG MD of system containing 2 pentamers in the membrane buckled in a single direction (BuckledMembrane_FeigLab_2xPentamerNoPTM_POPC_Martini3b: 1 μs).</p> <p>FeigLab_Pentamer: https://github.com/feiglab/sars-cov-2-proteins/blob/master/Membrane/E_protein.pdb<br> FeigLab_NMR_Pentamer is assembled based on the transmembrane domain determined by NMR (PDB ID: 7K3G) and FeigLab model for the rest.</p>
Classifying the generation and formation channels of dynamically-formed gravitational-wave events
<p>This dataset contains all the simulations of dynamically-formed binaries performed with the software <a href="https://github.com/Kkritos/Rapster">rapster</a>, together with trained machine-learning classification models from (Antonelli, Kritos et al, in prep.), see <a href="https://github.com/aantonelli94/TheBHClassifier">the public codes online</a>.</p> <p>All items starting with "mergers_*" are simulations of clusters and they follow the structure reported in the documentation of <a href="https://github.com/Kkritos/Rapster">rapster</a>. The simulations differ in the choice of the hyperparameters for the distribution of the cluster mass, half-mass radius and initial spin distribution for the binaries.</p> <p>All items starting from "RFClassifier_*" are machine-learning classification models that use a Random Forest Classifier and that are trained with the simulations above. The models ending with "*_gen" predict the generation of the black holes, those with "*_form" predict their formation channels. </p> <p> </p>
Data and Analyses for Defining Filler Particles: A Phonetic Account of the Terminology, Form, and Grammatical Classification of Filled Pauses.
<p>Aggregated data and analyses for the article Belz, Malte (2023): Defining Filler Particles: A Phonetic Account of the Terminology,<br> Form, and Grammatical Classification of "Filled Pauses". Languages. <a href="https://www.mdpi.com/journal/languages/special_issues/Pauses_in_Speech">https://www.mdpi.com/journal/languages/special_issues/Pauses_in_Speech</a></p>
Morphological cladogenesis and terminal dwarfing in extinct Late Miocene through Pliocene menardiform globorotalids: New complementary data to «Evolutionary prospection in the Neogene planktic foraminifer Globorotalia menardii and related forms from ODP Hole 925B (Céara Rise, western tropical Atlantic): evidence for gradual evolution superimposed by long distance dispersal ?, Swiss J. Palaeontology, 135:205-248»
<p>A complementary morphometric data set is provided to the study of Knappertsbusch (2016) about the shell evolution of menardiform globorotalids (Neogene planktic foraminifera) at ODP Hole 925B from Céara Rise in the the western tropical Atlantic. The new measurements confirm splitting of extinct <em>Globorotalia multicamerata</em> from the <em>G. menardii</em> stock via the intermediate form <em>G. limbata</em> between about 6 Ma to 5 Ma ago. After splitting both <em>G. limbata</em> and <em>G. multicamerata</em> show gradual divergence from <em>G. menardii</em> in several shell parameters illustrating morphological cladogenesis. Between 2.88 Ma and 2.59 Ma the same parameters show a concerted trend towards reduced values indicating pre-extinction dwarfing. A comparison with published literature data of Delta<sup>18</sup>O trends between species, that populated the mixed layer (<em>Globigerinoides sacculifer</em>) and the thermocline layer (<em>Neogloboquadrina dutertrei</em>) at this location during those times suggests, that both divergence and subsequent dwarfing trends were probably the results of changes in upper watermass stratification.</p> <p>The complementary data set is provided in six zipped archives APPENDIX A, B, C, D, E and F (zipped with free software 7-Zip 22.00 (x64), 2022-06-15 from 1999-2022 Igor Pawlow), together with a description of the data in file Report_925B_suppl_1.pdf.</p>
Data and Software for "Gullies on Mars could have formed by melting of water ice during periods of high obliquity"
<p>Code, movies and climate model outputs for "Gullies on Mars could have formed by melting of water ice during periods of high obliquity" by Dickson et al. Science, 2023.</p>
FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach.
<p>The products can be vizualized at <a href="https://martinschwartz0.users.earthengine.app/view/forms-height-biomass-volume-viewer">https://martinschwartz0.users.earthengine.app/view/forms-height-biomass-volume-viewer</a></p> <p>- FORMS-H: Canopy height map of France at 10 m resolution. The units are in centimeter (10^-2 m).</p> <p>- FORMS-B: Above-ground biomass density map of France at 30 m resolution. The units are in Mg ha-1</p> <p>- FORMS-V: Wood volume density map of France at 30 m resolution. The units are in m3 ha-1</p> <p>Please refer to the paper <a href="https://doi.org/10.5194/essd-15-4927-2023">https://doi.org/10.5194/essd-15-4927-2023</a> for further details.</p>
Dataset: Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges
<p>Direct numerical simulation (DNS) data for 2D forced homogeneous isotropic turbulence (FHIT) and 2D Rayleigh-Benard Convection (RBC). This data is used to discover subgrid-scale (SGS) closures for momentum and heat fluxes.</p> <p>Paper: "<strong>Learning Closed-Form Equations for Subgrid-Scale Closures From High-Fidelity Data: Promises and Challenges</strong>" <br> <a href="https://doi.org/10.1029/2023MS003874">https://doi.org/10.1029/2023MS003874</a></p>
EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 5: Aspects of ENCI I.: Hybridity, private/public, passive/active forms
<p>This document is Part 5 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship (ENCI) between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe.</p> <p>EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.</p>
DB4ISF: An incremental sheet forming database
<h2>DB4ISF</h2> <p>DB4ISF is an incremental sheet forming database consisting of 76 forming experiments executed by the Chair of Production Systems at Ruhr-Universität Bochum.</p> <p>The database consists of the following data:<br>• General process data (tool radii, sheet thickness, step depth, ...)<br>• CAD files (stl, sldprt including CAMWorks toolpaths)<br>• Toolpaths (surface points and normal vectors)<br>• Robot programs used for forming (KRL)<br>• Digitization (CDB)<br>• Deviation of every toolpath point in normal direction<br>• Precalculated surface representations for machine learning</p> <h2>Publication and reference</h2> <p>A publication that describes the methodical approach for building up the database and the experimental data inside it can be found here:<br>Möllensiep, Dennis; Schäfer, Jan; Pasch, Felix, Kuhlenkötter Bernd<em>.</em> Cluster analysis for systematic database extension to improve machine learning performance in double-sided incremental sheet forming. <em>International Journal of Advanced Manufacturing Technology</em> (2024). <a href="https://doi.org/10.1007/s00170-024-14014-8">https://doi.org/10.1007/s00170-024-14014-8.</a></p> <p>Please cite the corresponding publication too if you are using the database for your own research.</p> <h2>ML4ISF</h2> <p>ML4ISF is a Matlab Framework with a GUI for the application of machine learning in incremental sheet forming and fully compatible with the database. </p> <p>The framework offers the following features:<br>• Data management<br>• Toolpath import with various presets<br>• Calculation of surface representations utilized for machine learning<br>• Generation of training data tables for machine learning in python<br>• Prediction of the forming accuracy with several provided artificial networks<br>• Toolpath adjustments based on the prediction and smoothing of the path<br>• Generation of Kuka robot programs (other exporters could be implemented)<br>• Various plotting functions</p> <p>Prerequisites:<br>• Surface toolpath with the corresponding normal vectors<br>• STL file of the part</p> <p>The framework was developed for the application of double sided incremental forming (DSIF) utilizing two industrial robots where the supporting robot applies a defined support force. Other methods such as SPIF with NC-machines can be implemented with slight modifications.</p> <p>ML4ISF can be downloaded here: <a href="https://doi.org/10.5281/zenodo.10036335">https://doi.org/10.5281/zenodo.10036335</a>.</p> <h2>Contact</h2> <p>If you have any questions about the database, please contact:<br>Dennis Möllensiep<br><a href="../moelldnl/ml4isf/-/blob/master/moellensiep@lps.rub.de">moellensiep@lps.rub.de</a></p> <h2>License</h2> <p>This database is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit <a href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</a>.</p>
Model output, drivers and parameters for Ecosystem Recovery from Disturbance is Constrained by N Cycle Openness, Vegetation-Soil N Distribution, Form of N Losses, and the Balance Between Vegetation and Soil-Microbial Processes
Files used to generate the data for figures in: Rastetter, EB, Kling, GW, Shaver, GR, Crump, BC, Gough, L. Ecosystem Recovery from Disturbance Is Constrained by N Cycle Openness, Vegetation-Soil N Distribution, Form of N Losses, and the Balance between Vegetation and Soil-Microbial Processes. Ecosystems (2020). https://doi.org/10.1007/s10021-020-00542-3. This paper present a framework for assessing biogeochemical recovery of terrestrial ecosystems from disturbance. We identify three recovery phases. In Phase 1, nitrogen is redistributed from soil organic matter to vegetation, but the ecosystem continues to lose nitrogen because the recovering vegetation cannot take up nitrogen as fast as it is released from soil. In Phase 2, the ecosystem begins re-accumulating nitrogen and converges on a quasi-steady state in which vegetation and soil-microbial processes are in balance. In Phase 3, vegetation and soil-microbial processes remain in balance and the ecosystem slowly re-accumulates the remaining nitrogen.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.