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Spectroscopic data of the compounds published in "The Effect of Selenium-Based Ligands on Tungsten Acetylene Complexes"
<p>Here, the uploaded data are associated with the manuscript "The Effect of Selenium-Based Ligands on Tungsten Acetylene Complexes" published in Inorg. Chem. under the following doi/10.1021/acs.inorgchem.4c01636<br>The .dpt files represent IR spectra of the compounds published in the manuscript. The .scv files represent NMR spectra of the compounds and reactions published in the manuscript.<br>The labeling of the compounds and reactions follows the one in the published manuscript.</p>
Figure 7 in Internet-based data platforms re-define the distributions of some large crabronid wasps in Arkansas (Hymenoptera: Crabronidae)
Figure 7. Map of the known geographic distributions for Sphecius speciosus (circle), Stictia carolina (triangle), Stizus brevipennis (square) in Arkansas.
Figure 8 in Internet-based data platforms re-define the distributions of some large crabronid wasps in Arkansas (Hymenoptera: Crabronidae)
Figure 8. Number of county records for three species of wasps in the University of Arthropod Arthropod Museum (UAAM), and three internet-based data platforms.
Mediterranean risk assessment data based on the concurrency between climate change, fisheries, stocks, and biodiversity
<p>Data associated to the paper "Detecting Ecosystem Risk Hotspots: A Mediterranean Case Study" by G. Coro, L. Pavirani, A. Ellenbroek.</p>
Data for fitting Burnt Area Simulator for Europe (BASE v1.0)
<p>Data set is a large R (v4.4.0) data.table (v1.15.4) saved with saveRDS (so open with readRDS). Data is monthly for years 2001-2014 with a spatial resolution of ~9km across the EU plus associated and candidated countries. It was used to fit BASE v1.0 - which is statistical model (GLM) of burnt area occurrence that considers cropland an non-cropland vegetation separately. </p>
Fig. 3 in Quantitative Biogeographic Characterization Of Hungary Based On The Distribution Data Of Land Snails (Mollusca,Gastropoda): A Case Of Nestedness Of Species Ranges With Extensive Overlap Of Biotic Elements
Fig. 3. Distribution maps of four biotic elements found by PRABCLUS: (a) highland species, (b) general species, (c) localizes species distributed in the northern and (d) south–eastern parts of Hungary. The different shadings indicate the areas where>70%,>30%, and>0% of the species of an ele-
Fig. 1 in Quantitative Biogeographic Characterization Of Hungary Based On The Distribution Data Of Land Snails (Mollusca,Gastropoda): A Case Of Nestedness Of Species Ranges With Extensive Overlap Of Biotic Elements
Fig. 1. Biogeographic classification of Hungary based on distribution data of land snails according to the (a) hierarchical clustering of the (b) spatial units (ca. 50 km × 50 km). For clustering, the Sørensen–index and Ward–Orlóci fusion method was used. Shades of grey indicate main partitions of the cluster hierarchy, circled numbers 1–6 indicate lower level partitions mentioned in the text, numbers 1–49 identify spatial units (a) in the cluster foot and (b) in the map. Capital letters correspond to IndVal species groups listed in the text and in Appendix, lines associated to letters refer to
Fig. 2 in Quantitative Biogeographic Characterization Of Hungary Based On The Distribution Data Of Land Snails (Mollusca,Gastropoda): A Case Of Nestedness Of Species Ranges With Extensive Overlap Of Biotic Elements
Fig. 2. First two dimensions of the metric multidimensional scaling of the range data of the Hungarian land snail species. 1–4: biotic elements found by PRABCLUS; N: noise component.
Supplementary Simulation Data for "A contact-based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold-switch"
<p>Additional simulation data for "A contact-based analysis of local energetic frustration dynamics identifies key residues enabling RfaH fold-switch"</p> <p><strong>Content:</strong></p> <p>'clusters_foldswitch': Contains representative structures in PDB format of the refolding landscape of RfaH using all-atom structure-based models. The QA and QB values indicated in each filename correspond to the fraction of native contacts contain in the representative structure in comparison to the total number of contacts in the structure of the autoinhibited ⍺-folded (A) and active β-folded (B) states of the C-terminal domain of RfaH.</p> <p>'input_one_fs': Contains a trajectory of RfaH refolding from the ⍺-folded to the β-folded state, with each frame contained into a separate PDB file, totalling 400 PDB files. These files can be used with the frustration-based windowing method scripts and Colab notebook made available at https://github.com/pb3lab/RfaH-frustration</p> <p>'input_many_fs': Contains several trajectory of RfaH reversible refolding between the ⍺-folded and β-folded states, with each frame contained into a separate PDB file, totalling 11,999 PDB files. These files can be used with the frustration-based windowing method scripts and Colab notebook made available at https://github.com/pb3lab/RfaH-frustration</p> <p>'output_one_fs': Contains output results from the analysis of local energetic frustration dynamics of the 400 frames contained in 'input_one_fs' using the windowing method available in the Colab notebook at https://github.com/pb3lab/RfaH-frustration.</p> <p>'output_many_fs': Contains output results from the analysis of local energetic frustration dynamics of the 11,999 frames contained in 'input_many_fs' using the windowing method available in the Python script at https://github.com/pb3lab/RfaH-frustration.</p>
Electronic Structure Data for "Design of Covalent Organic Frameworks through on-the-fly Batch-based Bayesian Optimization"
<p>This is a dataset of 1736 potential building blocks for the construction of covalent organic frameworks (COF). Electronic structures were calculated with the GFN1-xTB tight binding DFT approach as implemented in the xTB package (v6.2.3). The dataset contains all necessary inputs and outputs from these calculations. Structures were optimised with xTB's internal normal coordinate rational function optimizer (ANCopt) at the default geometry convergence criterion.</p> <p>The dataset contains calculations for two major parameters determining the suitability of the resulting COFs as an organic semiconductor, specifically, the approximate energy alignment of the homo level and the reorganization free energy.</p>
Data from: Sequence-based detection of emerging antigenically novel influenza A viruses
<p>The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe NIAViD, an unsupervised machine learning tool, adept at identifying these transitions, using HA1 sequence and associated physicochemical properties. NIAViD, performed with 88.9% (95% CI, 56.5%–98.0%) and 72.7% (95% CI,43.4%– 90.3%) sensitivity in training and validation respectively, outperforming the uncalibrated null model – 33.3% (95% CI,12.1%–64.6%) and does not require the need for potentially biased, time-consuming and costly laboratory assays. The pivotal role of Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modeling of hemagglutinin inhibition titers. Our approach holds immense promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.</p>
Figure 4 in Interannual Variability of Water Exchange Anomalies Between the Northern, Middle and Southern Caspian Based on Satellite Altimetry Data
Figure 4. Temporal variability of anomalies of surface geostrophic velocities (m/s) directed normal to 133 (a) and 209 (b) tracks. Positive values correspond to the southeast direction of currents, negative values correspond to the northwest direction.
Figure 1 in Interannual Variability of Water Exchange Anomalies Between the Northern, Middle and Southern Caspian Based on Satellite Altimetry Data
Figure 1. The Caspian Sea. Main parts of the Caspian Sea: (1) – the Northern Caspian (2) - the Middle Caspian; (3) – the Southern Caspian; (4) – the Kara-Bogaz-Gol Bay. Isobaths are shown in meters. The coastline corresponds to year 1934, when the sea level was -26.46 m relative to the World Ocean level (Lebedev, 2018).
Data study "The Impact of Augmented Reality on Biodiversity Learning in a Pedagogical Scenario Based on Analogical Reasoning: An Experimental Study"
<p>This data was collected in 2023 as part of a study on the impact of location-based AR on biodiversity education. </p>
Рис. 7. Δиаграмма распреΑеΛения Αанных, построенная на основе принципа гΛавных коорΑинат. Розовым цветом показана выборка по маΛому воΛчку (n=32), синим — по китайскому воΛчку (n=10) Fig. 7. Data distribution diagram based on the principal coordinates. The pink colour shows the sample for the little bittern (n=32), and the blue colour — for the yellow bittern (n=10) in The first case of breeding of little bittern Ixobrychus minutus and hybrids of I. minutus with I. sinensis in the Russian Far East
Рис. 7. Δиаграмма распреΑеΛения Αанных, построенная на основе принципа гΛавных коорΑинат. Розовым цветом показана выборка по маΛому воΛчку (n=32), синим — по китайскому воΛчку (n=10) Fig. 7. Data distribution diagram based on the principal coordinates. The pink colour shows the sample for the little bittern (n=32), and the blue colour — for the yellow bittern (n=10)
Fig. 3. Phylogenetic trees from reported 18S in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig. 3. Phylogenetic trees from reported 18S rRNA genes of insects according to NJ. A. Based on sequences of full-length. B. Based on second conserved region.
Fig. 4 in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig. 4. Phylogenetic trees based on partial sequences from reported cox1 genes of insects according to NJ.
Fig.1 in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig.1. PCR result of 18S rRNA of Lymantria dispar. Separated bands (from left to right). 18S1, 18S2, 18S rRNA, DL2000 marker.
Data set for "Bidirectional microwave-optical transduction based on integration of high-overtone bulk acoustic resonators and photonic circuits"
<p>The repository contains raw data, processing scripts, simulation and GDS files for the manuscript "Bidirectional microwave-optical transduction based on integration of high-overtone bulk acoustic resonators and photonic circuits". For detailed usage instructions, please take a look at the README.txt file. </p>
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019) in Variability of the gene cyt b in the Korean field mouse Apodemus peninsulae Thomas, 1906 - a reservoir host of AMRV in the Khasansky District of Primorsky Krai
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019)
ScienceDex guides
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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.