cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2f9g8h
title: CCDC 2243416: Experimental Crystal Structure Determination

description: Related Article: Yuhang Wang, Peng Ma, Ning Ma, Jianhui Wang|2023|Org.Lett.|25|3527|doi:10.1021/acs.orglett.3c01091
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7929648
title: IBSU-1432 dataset on videoendoscopy frame quality classification for laryngoscopy (NBI modality)

description: <strong>How to cite</strong> Nogal, P., Buchwald, M., Staśkiewicz, M., Kupiński, S., Pukacki, J., Mazurek, C., ... & Wierzbicka, M. (2022). Endoluminal larynx anatomy model–towards facilitating deep learning and defining standards for medical images evaluation with artificial intelligence algorithms. <em>Polish Journal of Otolaryngology</em>, <em>76</em>(5), 37-45. https://doi.org/10.5604/01.3001.0015.9501 Paderno, A., Piazza, C., Del Bon, F., Lancini, D., Tanagli, S., Deganello, A., … Moccia, S. (2021). Deep Learning for Automatic Segmentation of Oral and Oropharyngeal Cancer Using Narrow Band Imaging: Preliminary Experience in a Clinical Perspective. <em>Frontiers in Oncology</em>, <em>11</em>(March), 1–12. https://doi.org/10.3389/fonc.2021.626602 Moccia, S., Vanone, G. O., Momi, E. De, Laborai, A., Guastini, L., Peretti, G., & Mattos, L. S. (2018). Learning-based classification of informative laryngoscopic frames. <em>Computer Methods and Programs in Biomedicine</em>, <em>158</em>, 21–30. https://doi.org/10.1016/j.cmpb.2018.01.030 <strong>Description</strong> The presented dataset consists of 1432 laryngeal endoscopy frames of different acquisition quality. The four classes were distinguished (after Moccia et al., 2018): Informative frames (436), Blurred (383), Saliva/specular reflections (321), and Underexposed frames (292). (In total, 1432 = 436 I + 383 B + 321 S + 292 U.) <strong>Acknowledgements</strong> Alberto Paderno, MD PhD – Brescia data part Sara Moccia, PhD – IBSU-720 frames dataset from Zenodo: https://zenodo.org/record/1162784#.Ycrmfi1Q1qt Małgorzata Wierzbicka, MD PhD – Poznan data part Piotr Nogal, MD – Poznan data part Joanna Jackowska, MD PhD – Poznan data part Hanna Klimza, MD PhD – Poznan data part
DOI: 10.5281/zenodo.7929647
title: IBSU-1432 dataset on videoendoscopy frame quality classification for laryngoscopy (NBI modality)

description: <strong>How to cite</strong> Nogal, P., Buchwald, M., Staśkiewicz, M., Kupiński, S., Pukacki, J., Mazurek, C., ... & Wierzbicka, M. (2022). Endoluminal larynx anatomy model–towards facilitating deep learning and defining standards for medical images evaluation with artificial intelligence algorithms. <em>Polish Journal of Otolaryngology</em>, <em>76</em>(5), 37-45. https://doi.org/10.5604/01.3001.0015.9501 Paderno, A., Piazza, C., Del Bon, F., Lancini, D., Tanagli, S., Deganello, A., … Moccia, S. (2021). Deep Learning for Automatic Segmentation of Oral and Oropharyngeal Cancer Using Narrow Band Imaging: Preliminary Experience in a Clinical Perspective. <em>Frontiers in Oncology</em>, <em>11</em>(March), 1–12. https://doi.org/10.3389/fonc.2021.626602 Moccia, S., Vanone, G. O., Momi, E. De, Laborai, A., Guastini, L., Peretti, G., & Mattos, L. S. (2018). Learning-based classification of informative laryngoscopic frames. <em>Computer Methods and Programs in Biomedicine</em>, <em>158</em>, 21–30. https://doi.org/10.1016/j.cmpb.2018.01.030 <strong>Description</strong> The presented dataset consists of 1432 laryngeal endoscopy frames of different acquisition quality. The four classes were distinguished (after Moccia et al., 2018): Informative frames (436), Blurred (383), Saliva/specular reflections (321), and Underexposed frames (292). (In total, 1432 = 436 I + 383 B + 321 S + 292 U.) <strong>Acknowledgements</strong> Alberto Paderno, MD PhD – Brescia data part Sara Moccia, PhD – IBSU-720 frames dataset from Zenodo: https://zenodo.org/record/1162784#.Ycrmfi1Q1qt Małgorzata Wierzbicka, MD PhD – Poznan data part Piotr Nogal, MD – Poznan data part Joanna Jackowska, MD PhD – Poznan data part Hanna Klimza, MD PhD – Poznan data part
DOI: 10.6084/m9.figshare.23198942
title: Datos para revisión sistemática Metaversidad

description: Datos para revisión sistemática de literatura (hasta diciembre 2022) para los términos: "metaversity", "metauniversity", "university", "higher education", "metaverse", "metaverses", "immersive experience", "extended reality", "web 3.0", "digital twin". Bases de datos WoS, Scopus y Scielo
DOI: 10.5281/zenodo.7971705
title: Generative Machine Learning for Detector Response Modeling with a Conditional Normalizing Flow

description: The samples are datasets used for testing in the scenarios: baseline (corr0.hdf5), correlation of 0.5 (corr50.hdf5), correlation of 1.0 (corr100.hdf5), and asymmetric detector responses (asymmetric.hdf5). Each file contains the conditional variables, generated and simulated detector responses, and generated and simulated reconstruction-level variables.
DOI: 10.5281/zenodo.7971704
title: Generative Machine Learning for Detector Response Modeling with a Conditional Normalizing Flow

description: The samples are datasets used for testing in the scenarios: baseline (corr0.hdf5), correlation of 0.5 (corr50.hdf5), correlation of 1.0 (corr100.hdf5), and asymmetric detector responses (asymmetric.hdf5). Each file contains the conditional variables, generated and simulated detector responses, and generated and simulated reconstruction-level variables.
DOI: 10.5519/qd.qqmw83zo
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (64 records)
DOI: 10.5281/zenodo.7971878
title: Data of Gerromorpha occurrence in central Amazonia

description: Data of occurrence of 17 species of Gerromorpha in 33 streams in central Amazonia, and environmental descriptors. The data was used in maximum likelihood models to determine the occurrence of species.
DOI: 10.5281/zenodo.7971877
title: Data of Gerromorpha occurrence in central Amazonia

description: Data of occurrence of 17 species of Gerromorpha in 33 streams in central Amazonia, and environmental descriptors. The data was used in maximum likelihood models to determine the occurrence of species.
DOI: 10.21227/6f22-py65
title: Cyber-Physical Dataset for UAVs Under Normal Operations and Cyber-Attacks

description: Unmanned aerial vehicles (UAVs) are being used for various applications, but the associated cyber risks are also increasing. Machine learning techniques have been successfully adopted to develop intrusion detection systems (IDSs). However, none of the existing works published the cyber or physical datasets that have been used to develop the IDS, which hinders further research in this field. Hence, we developed a testbed that includes a UAV, controller, and data collection tools, to launch cyber-attacks (de-authentication denial-of-service (DoS) and replay attacks) on the UAV and collect cyber and physical data under normal and attack conditions, and we make this dataset publicly available.
DOI: 10.6084/m9.figshare.23199161
title: Global Noncoding microRNA Profiling in Mice Infected with Partial Human Mouth Microbes (PAHMM) Using an Ecological Time-Sequential Polybacterial Periodontal Infection (ETSPPI) Model Reveals Sex-Specific Differential microRNA Expression

description: Periodontitis (PD) is a polymicrobial dysbiotic immuno-inflammatory disease. It is more prevalent in males and has poorly understood pathogenic molecular mechanisms. Our primary objective was to characterize alterations in sex-specific microRNA (miRNA, miR) after periodontal bacterial infection. Using partial human mouth microbes (PAHMM) (<em>Streptococcus gordonii</em>, <em>Fusobacterium nucleatum</em>, <em>Porphyromonas gingivalis</em>, <em>Treponema denticola,</em> and <em>Tannerella forsythia</em>) in an ecological time-sequential polybacterial periodontal infection (ETSPPI) mouse model, we evaluated differential mandibular miRNA profiles by using high-throughput Nanostring nCounter® miRNA expression panels. All PAHMM mice showed bacterial colonization (100%) in the gingival surface, an increase in alveolar bone resorption (<em>p</em> &lt; 0.0001), and the induction of a specific immunoglobin G antibody immune response (<em>p</em> &lt; 0.001). Sex-specific differences in distal organ bacterial dissemination were observed in the heart (82% male vs. 28% female) and lungs (2% male vs. 68% female). Moreover, sex-specific differential expression (DE) of miRNA was identified in PAHMM mice. Out of 378 differentially expressed miRNAs, we identified seven miRNAs (miR-9, miR-148a, miR-669a, miR-199a-3p, miR-1274a, miR-377, and miR-690) in both sexes that may be implicated in the pathogenesis of periodontitis. A strong relationship was found between male-specific miR-377 upregulation and bacterial dissemination to the heart. This study demonstrates sex-specific differences in bacterial dissemination and in miRNA differential expression. A novel PAHMM mouse and ETSPPI model that replicates human pathobiology can be used to identify miRNA biomarkers in periodontitis.
DOI: 10.6084/m9.figshare.23199161.v1
title: Global Noncoding microRNA Profiling in Mice Infected with Partial Human Mouth Microbes (PAHMM) Using an Ecological Time-Sequential Polybacterial Periodontal Infection (ETSPPI) Model Reveals Sex-Specific Differential microRNA Expression

description: Periodontitis (PD) is a polymicrobial dysbiotic immuno-inflammatory disease. It is more prevalent in males and has poorly understood pathogenic molecular mechanisms. Our primary objective was to characterize alterations in sex-specific microRNA (miRNA, miR) after periodontal bacterial infection. Using partial human mouth microbes (PAHMM) (<em>Streptococcus gordonii</em>, <em>Fusobacterium nucleatum</em>, <em>Porphyromonas gingivalis</em>, <em>Treponema denticola,</em> and <em>Tannerella forsythia</em>) in an ecological time-sequential polybacterial periodontal infection (ETSPPI) mouse model, we evaluated differential mandibular miRNA profiles by using high-throughput Nanostring nCounter® miRNA expression panels. All PAHMM mice showed bacterial colonization (100%) in the gingival surface, an increase in alveolar bone resorption (<em>p</em> &lt; 0.0001), and the induction of a specific immunoglobin G antibody immune response (<em>p</em> &lt; 0.001). Sex-specific differences in distal organ bacterial dissemination were observed in the heart (82% male vs. 28% female) and lungs (2% male vs. 68% female). Moreover, sex-specific differential expression (DE) of miRNA was identified in PAHMM mice. Out of 378 differentially expressed miRNAs, we identified seven miRNAs (miR-9, miR-148a, miR-669a, miR-199a-3p, miR-1274a, miR-377, and miR-690) in both sexes that may be implicated in the pathogenesis of periodontitis. A strong relationship was found between male-specific miR-377 upregulation and bacterial dissemination to the heart. This study demonstrates sex-specific differences in bacterial dissemination and in miRNA differential expression. A novel PAHMM mouse and ETSPPI model that replicates human pathobiology can be used to identify miRNA biomarkers in periodontitis.
DOI: 10.6084/m9.figshare.22770443
title: Data Field Probiotic Trials

description: Raw Sequencences, Processed Sequences, and Metadata for two years of field trials of amphibian skin probiotic treatments.
DOI: 10.6084/m9.figshare.22770443.v1
title: Data Field Probiotic Trials

description: Raw Sequencences, Processed Sequences, and Metadata for two years of field trials of amphibian skin probiotic treatments.
DOI: 10.6084/m9.figshare.22770443.v2
title: Data Field Probiotic Trials

description: Raw Sequencences, Processed Sequences, and Metadata for two years of field trials of amphibian skin probiotic treatments.
DOI: 10.5281/zenodo.7922486
title: GPUHarbor: Testing GPU Memory Consistency At Large (Experience Paper): Artifact

description: Artifact for the ISSTA 2023 paper "GPUHarbor: Testing GPU Memory Consistency At Large (Experience Paper)"
DOI: 10.5281/zenodo.7922485
title: GPUHarbor: Testing GPU Memory Consistency At Large (Experience Paper): Artifact

description: Artifact for the ISSTA 2023 paper "GPUHarbor: Testing GPU Memory Consistency At Large (Experience Paper)"
DOI: 10.5519/qd.446jui9w
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.7970590
title: Annotated sequences extracted from bacterial genomes

description: Three files containing sequences extracted from 1,049,210 bacterial genomes available from GenBank (release 252). Protein coding sequences were annotated with IDTAXA (PMID: 34541527) using taxon-specific KEGG groups (Bacteria_Protein_subset.fas.gz). These annotations were transferred to their corresponding (nucleotide) coding sequences (Bacteria_Nucleotide_subset.fas.gz). Intergenic regions were extracted from each genome and annotated by FindNonCoding (PMID: 34636849) for their overlap with any of 25 common bacterial non-coding RNAs in Rfam (v14). Intergenic regions were required to be at least 100 nucleotides long and contain no ambiguities (Bacteria_Intergenic_subset.fas.gz). Each subset contains only distinct sequences randomly ordered. <strong><em>Headers</em></strong> Sequence headers contain the assembly accession followed by the annotation and separated by a "|" character. For example: <strong>Bacteria_Intergenic_subset.fas.gz</strong> &gt;GCA_022121725.1|RF00000<br> ATGTTACCTTCTTGAGTGATACGGGATGAA[...] <strong>Bacteria_Protein_subset.fas.gz</strong> &gt;GCA_014764685.1|K02049<br> MPRDLIRISGLEKTYADGSVHALSNIDLSIKD[...] <strong>Bacteria_Nucleotide_subset.fas.gz</strong> &gt;GCA_015948525.1|K02197<br> GTGAACCTGCGACGTAAAAACCGGCTAYG[...] <strong><em>Annotations</em></strong> Protein and protein coding sequences are labeled with their KEGG group, starting with "K". Intergenic sequences are named by any overlapping Rfam families, starting with a "RF", and separated by commas when multiple are predicted. "RF00000" is a placeholder for the absence of any predicted RF families.
DOI: 10.5281/zenodo.7970589
title: Annotated sequences extracted from bacterial genomes

description: Three files containing sequences extracted from 1,049,210 bacterial genomes available from GenBank (release 252). Protein coding sequences were annotated with IDTAXA (PMID: 34541527) using taxon-specific KEGG groups (Bacteria_Protein_subset.fas.gz). These annotations were transferred to their corresponding (nucleotide) coding sequences (Bacteria_Nucleotide_subset.fas.gz). Intergenic regions were extracted from each genome and annotated by FindNonCoding (PMID: 34636849) for their overlap with any of 25 common bacterial non-coding RNAs in Rfam (v14). Intergenic regions were required to be at least 100 nucleotides long and contain no ambiguities (Bacteria_Intergenic_subset.fas.gz). Each subset contains only distinct sequences randomly ordered. <strong><em>Headers</em></strong> Sequence headers contain the assembly accession followed by the annotation and separated by a "|" character. For example: <strong>Bacteria_Intergenic_subset.fas.gz</strong> &gt;GCA_022121725.1|RF00000<br> ATGTTACCTTCTTGAGTGATACGGGATGAA[...] <strong>Bacteria_Protein_subset.fas.gz</strong> &gt;GCA_014764685.1|K02049<br> MPRDLIRISGLEKTYADGSVHALSNIDLSIKD[...] <strong>Bacteria_Nucleotide_subset.fas.gz</strong> &gt;GCA_015948525.1|K02197<br> GTGAACCTGCGACGTAAAAACCGGCTAYG[...] <strong><em>Annotations</em></strong> Protein and protein coding sequences are labeled with their KEGG group, starting with "K". Intergenic sequences are named by any overlapping Rfam families, starting with a "RF", and separated by commas when multiple are predicted. "RF00000" is a placeholder for the absence of any predicted RF families.
DOI: 10.7281/t1/ijo1fu/ihvui7
title: 00_Readme.RagenACC.docx

description: Readme file describing variables
DOI: 10.7281/t1/ijo1fu/xjcrmp
title: Data.RagenACC.zip

description: Data from years 2399-2499 of control simulation
DOI: 10.5281/zenodo.7971928
title: SciExpeM - 10.5281/zenodo.7971928

description: Hu, Erjiang; Pan, Lun; Gao, Zhenhua; Lu, Xin; Meng, Xin; Huang, Zuohua - International Journal Of Hydrogen Energy, 2016, (41), 13261-13280
DOI: 10.5281/zenodo.7971927
title: SciExpeM - 10.5281/zenodo.7971928

description: Hu, Erjiang; Pan, Lun; Gao, Zhenhua; Lu, Xin; Meng, Xin; Huang, Zuohua - International Journal Of Hydrogen Energy, 2016, (41), 13261-13280
DOI: 10.3886/e190581
title: Data and Code for: Policies for Electrifying the Light-Duty Vehicle Fleet in the United States

description: This folder provides data and code associated with the manuscript for "Policies for Electrifying the Light-Duty Vehicle Fleet in the United States".
DOI: 10.3886/e190581v1
title: Data and Code for: Policies for Electrifying the Light-Duty Vehicle Fleet in the United States

description: This folder provides data and code associated with the manuscript for "Policies for Electrifying the Light-Duty Vehicle Fleet in the United States".
DOI: 10.5281/zenodo.1419826
title: Data for: Resolving the avian tree of life from top to bottom: The promise and potential boundaries of the phylogenomic era

description: This data package includes multiple sequence alignments, information about base compositional variation, and phylogenetic analyses that support Figures 7 and 8 in Braun et al. (2019). There is a README in SuppInfo_Braun_et_al_chapter_Kraus_volume.tar.gz that provides a detailed description of the files in this data package. Braun, E.L., Cracraft, J., Houde, P. (2019). Resolving the Avian Tree of Life from Top to Bottom: The Promise and Potential Boundaries of the Phylogenomic Era. In: Kraus, R. (eds) Avian Genomics in Ecology and Evolution. Springer, Cham. https://doi.org/10.1007/978-3-030-16477-5_6
DOI: 10.5281/zenodo.1419827
title: Data for: Resolving the avian tree of life from top to bottom: The promise and potential boundaries of the phylogenomic era

description: This data package includes multiple sequence alignments, information about base compositional variation, and phylogenetic analyses that support Figures 7 and 8 in Braun et al. (2019). There is a README in SuppInfo_Braun_et_al_chapter_Kraus_volume.tar.gz that provides a detailed description of the files in this data package. Braun, E.L., Cracraft, J., Houde, P. (2019). Resolving the Avian Tree of Life from Top to Bottom: The Promise and Potential Boundaries of the Phylogenomic Era. In: Kraus, R. (eds) Avian Genomics in Ecology and Evolution. Springer, Cham. https://doi.org/10.1007/978-3-030-16477-5_6
DOI: 10.7281/t1/4f90kq/n2itin
title: 3. InVivoStudy.zip

description: Raw data, fluoroscopic movies, software, and figures for in vivo pig study.
DOI: 10.7281/t1/4f90kq/s5o88j
title: 4. Simulation.zip

description: COMSOL simulation files, data, CAD models, software, and figures associated with the acrylic phantom simulation.
DOI: 10.7281/t1/4f90kq/ykhxea
title: 1. readme.txt

description: Readme file for the data and software.
DOI: 10.7281/t1/4f90kq/neqb5w
title: 2. FemoralPhantomStudy.zip

description: Data, CAD models, software, and figures for femoral artery phantom case study.
DOI: 10.5281/zenodo.7965767
title: Early Medieval Pottery Marks from Moravia (Czechia)

description: Published archaeological dataset contains a database (MS Access .mdb database, and .csv exports as an alternative), as well as precise drawings of 636 pottery marks (i.e. embossed imprints on bottoms of ceramic vessels) from the following 9th century Moravian sites: Brno-Líšeň –⁠ Staré Zámky (87 pcs.) Břeclav –⁠ Pohansko (162 pcs.) Mikulčice (310 pcs.) Staré Město u Uherského Hradiště –⁠ U Víta (49 pcs.) Cemetery of Nechvalín (5 pcs.) Cemetery of Prušánky (23 pcs.) The dataset was originally created for the purpose of the author's dissertation (Hlavica 2020). It will be also referenced in the upcoming monograph (Hlavica in print). Records contained in the dataset can be used for the comparison with other similarly documented assemblages (for the method of documentation, see Hlavica 2016). The hierarchy of folders including precise drawings (.psd and .pdf formats) is: mark_type -&gt; inner_shape -&gt; outer_shape -&gt; match_variant
description: {"references": ["Hlavica, M. 2016: Zna\u010dky na dnech n\u00e1dob z Pohanska u B\u0159eclavi, Nechval\u00edna a Pru\u0161\u00e1nek a metoda jejich dokumentace. In: M\u011b\u0159\u00ednsk\u00fd, Z., Kl\u00e1p\u0161t\u011b, J. (eds.): Workshopy ke st\u0159edov\u011bk\u00e9 a novov\u011bk\u00e9 keramice: Pansk\u00e1 Lhota 2015. Brno: Masarykova Univerzita, 25\u201345.", "Hlavica, M. 2020: Zna\u010dky na dnech velkomoravsk\u00fdch keramick\u00fdch n\u00e1dob jako n\u00e1stroj pozn\u00e1n\u00ed ekonomicko-politick\u00e9 komplexity Velk\u00e9 Moravy. Dissertation. Masaryk University: Available at: https://is.muni.cz/th/xhz28/.", "Hlavica, M. in print: Fragmenty Velk\u00e9 Moravy. Hrn\u010d\u00ed\u0159sk\u00e9 zna\u010dky jako n\u00e1stroj v\u00fdzkumu spole\u010densk\u00e9 a politick\u00e9 komplexity Moravy 9. stolet\u00ed. Brno: Archeologick\u00fd \u00fastav AV \u010cR, Brno."]}
DOI: 10.5281/zenodo.7965768
title: Early Medieval Pottery Marks from Moravia (Czechia)

description: Published archaeological dataset contains a database (MS Access .mdb database, and .csv exports as an alternative), as well as precise drawings of 636 pottery marks (i.e. embossed imprints on bottoms of ceramic vessels) from the following 9th century Moravian sites: Brno-Líšeň –⁠ Staré Zámky (87 pcs.) Břeclav –⁠ Pohansko (162 pcs.) Mikulčice (310 pcs.) Staré Město u Uherského Hradiště –⁠ U Víta (49 pcs.) Cemetery of Nechvalín (5 pcs.) Cemetery of Prušánky (23 pcs.) The dataset was originally created for the purpose of the author's dissertation (Hlavica 2020). It will be also referenced in the upcoming monograph (Hlavica in print). Records contained in the dataset can be used for the comparison with other similarly documented assemblages (for the method of documentation, see Hlavica 2016). The hierarchy of folders including precise drawings (.psd and .pdf formats) is: mark_type -&gt; inner_shape -&gt; outer_shape -&gt; match_variant
description: {"references": ["Hlavica, M. 2016: Zna\u010dky na dnech n\u00e1dob z Pohanska u B\u0159eclavi, Nechval\u00edna a Pru\u0161\u00e1nek a metoda jejich dokumentace. In: M\u011b\u0159\u00ednsk\u00fd, Z., Kl\u00e1p\u0161t\u011b, J. (eds.): Workshopy ke st\u0159edov\u011bk\u00e9 a novov\u011bk\u00e9 keramice: Pansk\u00e1 Lhota 2015. Brno: Masarykova Univerzita, 25\u201345.", "Hlavica, M. 2020: Zna\u010dky na dnech velkomoravsk\u00fdch keramick\u00fdch n\u00e1dob jako n\u00e1stroj pozn\u00e1n\u00ed ekonomicko-politick\u00e9 komplexity Velk\u00e9 Moravy. Dissertation. Masaryk University: Available at: https://is.muni.cz/th/xhz28/.", "Hlavica, M. in print: Fragmenty Velk\u00e9 Moravy. Hrn\u010d\u00ed\u0159sk\u00e9 zna\u010dky jako n\u00e1stroj v\u00fdzkumu spole\u010densk\u00e9 a politick\u00e9 komplexity Moravy 9. stolet\u00ed. Brno: Archeologick\u00fd \u00fastav AV \u010cR, Brno."]}
DOI: 10.6084/m9.figshare.21737303.v4
title: Continuous odor profile monitoring to study olfactory navigation in small animals

description: Dataset for analysis and demo code for publication: "Continuous odor profile monitoring to study olfactory navigation in small animals" Chen et al. 2022
DOI: 10.5281/zenodo.7971922
title: compdist

description: This data package is associated with a manuscript describing the data for a test of the behavior of data compression distances for phylogenetic analyses. Mammal and bird protein data were used to examine the behavior of the distances. The information is: 1) sequence data files; 2) taxon lists; 3) locus lists; 4) distance output; 5) support values; 6) ML trees. The included README describes all of the files in this data package.