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Fig. 7. A in Survey of the allelopathic potential of Mediterranean macroalgae: production of long-chain polyunsaturated aldehydes (PUAs)
Fig. 7. A: Map indicating the position of the sampling site (Piscinetta del Passetto). B, C: details of the phytobenthic community in July 2017. In Fig. 6B arrowhead indicates Cystoseira compressa, curved arrow Dictyopteris polypodioides, and straight arrow Ulva cf. rigida, three of the species used for extraction of PUAs.
Fig. 6 in Survey of the allelopathic potential of Mediterranean macroalgae: production of long-chain polyunsaturated aldehydes (PUAs)
Fig. 6. Aldehydes production (nmol g 1) by Ulva cf. rigida at the different sampling times (data are mean ± st. dev. of 3 replicates).
Purification of High Molecular Weight DNA for Long-Read Sequencing Using a High-Salt Gel Electroelution Trap
<p><strong>Figure 3. Yield and purity of HMW DNA obtained from difficult samples using the method proposed in this study</strong>.</p> <p>(A) The proposed method extracts more HMW DNA from a complex soil sample than a commercial column purification kit. Shown is a negative image of an ethidium bromide-stained agarose gel. Lane 1: 1/10 aliquot of ~90 ng of HMW DNA isolated using the E.Z.N.A. soil DNA extraction kit from a soil sample containing ~1,5 μg of total DNA (HMW DNA yield around 6%). Lane 2: ~100 ng of CTAB-extracted DNA from the same soil sample. ~10 μg of this crude DNA preparation was used as input for HMW DNA purification using the proposed method. Lane 3: 1/100 aliquot of ~3 μg of HMW DNA isolated using the proposed method from ~10 μg of the CTAB-extracted DNA (HMW DNA yield around 30%).</p> <p>(B) The proposed method yields high-purity HMW DNA from a complex plant sample, as determined by agarose gel electrophoresis. Lane 1: molecular weight marker (GeneRuler DNA ladder, Thermo Fisher Scientific). Lane 2: crude nucleic acid preparation extracted with SDS/Proteinase K from <em>Zingeria trichopoda</em> leaves, which served as an input for HMW DNA purification using the proposed method. Lane 3: purified HMW DNA. Note the absence of low-molecular-weight nucleic acids and heavy covalent complexes in the purified sample.</p> <p>(C) Same as (B) except that crude, CTAB-extracted DNA from a complex soil sample was used as an input for HMW DNA purification. Note the absence of a continuous smear of fragmented DNA as well as heavy covalent complexes in the purified sample (lane 3). Molecular weight marker sizes are indicated in base pairs to the left of each panel.</p>
Tradeoffs in alignment and assembly-based methods for structural variant detection with long-read sequencing data
<p>Source data for the paper "Tradeoffs in alignment and assembly-based methods for structural variant detection with long-read sequencing data"</p>
isoMiGA: Long-read isoforms discovered in human microglia
<p>https://github.com/RajLabMSSM/isoMiGA </p> <p>Novel isoform discovery from long-read RNA-seq of 30 human microglia samples with PacBio CCS.</p> <p><strong>Isoform sets used</strong></p> <p>isomiga_full: all isoforms discovered from hybrid assembly of long-read and short-read data</p> <p>isomiga_novel: just the novel isoforms</p> <p>isomiga_gencode: the novel isoforms combined with all isoforms in GENCODE v38.</p> <p>Not included: GENCODE v38 - available at https://www.gencodegenes.org/human/release_38.html</p> <p><strong>Isoform coordinates (GTF)</strong></p> <p>All files bgzipped and tabixed for easy random access by IGV. {file}.gtf.gz is the Isoform list, {file}.gtf.gz.tbi is the tabix index.</p> <p><strong>Isoform sequences (FASTA)</strong></p> <p>All files gzipped. </p> <p> </p>
Fig. 3 in Transcriptional response of giant reed (Arundo donax L.) low ecotype to long-term salt stress by unigene-based RNAseq
Fig. 3. Distribution of transcription factors responsive to salt stress. Data are sorted by number of G34-S3 vs G34-CK DEGs.
Fig. 2 in Transcriptional response of giant reed (Arundo donax L.) low ecotype to long-term salt stress by unigene-based RNAseq
Fig. 2. GO enrichment analysis for the DEGs in A. donax (G34-S3 vs G34-CK) The X-axis indicates the numbers related to the total number of GO terms, and the Y-axis indicates the subcategories. BP, biological processes; CC, cellular components; MF, molecular functions.
Fig. 1 in Transcriptional response of giant reed (Arundo donax L.) low ecotype to long-term salt stress by unigene-based RNAseq
Fig. 1. Volcano plot showing the DEGs of G34-S3 vs G34-CK comparison. The up-regulated genes with statistically significance are represented by blue dots, the green dots represent the down-regulated genes and the red dots are DEGs with -log10padj <1.3, adopting log2FoldChange threshold of 0.58 (1.5 fold change). The X-axis is the gene expression change, and the Y-axis is the pvalue adjusted after normalization. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Quast outputs for "When do longer reads matter? A benchmark of long read de novo assembly tools for eukaryotic genomes"
<p>Quast outputs for "When do longer reads matter? A benchmark of long read de novo assembly tools for eukaryotic genomes"</p>
Probing the long-lived photo-generated charge carriers in transition metal dichalcogenides by time-resolved microwave photoconductivity
<p>Raw data of time resolved microwave conductivity measurements. </p>
Simulations from four process-based ecosystem models describing primary productivity in a tallgrass prairie long-term irrigation experiment
<p class="MsoNormal"><span>To demonstrate current capabilities in modeling herbaceous ecosystems, we selected four different process-based models that vary in their representation of community change from no community representation to vegetation demographic models. These models were used to simulate a long-term irrigation experiment at a US tallgrass prairie (Konza Prairie Biological Station) following a standardized simulation protocol. Specifically, we were interested in how model output under a monotonic increase in water availability matched up to experimental findings of (1) herbaceous plant community change and (2) aboveground net primary productivity before and after the plant community change. The results of this simulation are included here.</span></p>
Dataset and Software for An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms
<p><strong>What is the nature of flow in the mantle?</strong><br> <strong>How fast do waves travel anywhere on Earth?</strong><br> <strong>Where can radial anisotropy be robustly detected?</strong><br> <strong>Can we reconcile a broad spectrum of seismic data? What are the benefits?</strong></p> <p>We use normal-mode splitting functions in addition to surface-wave phase anomalies, body-wave travel times and long-period waveforms to construct a three-dimensional model of anisotropic shear-wave velocity in the Earth's mantle. This is the <strong>first tomographic study</strong> to exploit the sensitivity of mode-splitting data to constrain radial anisotropy in the Earth's mantle jointly with several other types of data. Our modeling approach inverts for mantle velocity and anisotropy as well as transition-zone discontinuity topographies, and incorporates new crustal corrections for the splitting functions that are consistent with the nonlinear corrections we employ for the waveforms. Our preferred anisotropic model, S362ANI+M, is an update to the earlier model S362ANI, which did not include normal-mode splitting functions in its derivation.</p> <p><strong>Feedback/Questions?</strong> Please contact Raj Moulik (<a href="https://rajmoulik.com">rajmoulik.com</a>) at <a href="mailto:moulik@caa.columbia.edu?subject=Query%20from%20Zenodo">moulik@caa.columbia.edu</a> </p> <p><strong>Reference:</strong></p> <p><em>Please cite the following work if you use this data or software.</em></p> <ul> <li>Moulik, P. & Ekström, G., 2014. An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms, <em>Geophys. J. Int.</em>, <strong>199</strong>(3), 1713-1738, doi: <a href="http://dx.doi.org/10.1093/gji/ggu356">10.1093/gji/ggu356</a>. <em><a href="https://rajmoulik.com/Publications/MoulikEkstrom_GJI2014.pdf">pdf</a></em></li> </ul> <p><em>You can also cite the dataset and software from this Zenodo page (Optional).</em></p> <ul> <li> <p>Moulik, P. & Ekström, G., 2014. Dataset and Software for An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms. In Geophys. J. Int. (v1.0, Vol. 199, pp. 1713–1738). Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.8357379">10.5281/zenodo.8357379</a></p> </li> </ul> <p><strong>Data Products:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANIplusM_Figures.tar.gz"><strong>S362ANIplusM_Figures.tar.gz</strong></a> - contains all figures from the paper in .png format</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM_MapViewsCrossSections.pdf"><strong>S362ANI+M_MapViewsCrossSections.pdf</strong></a> - Some cross sections and map views at various depths in the mantle</li> <li><strong><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM">S362ANI+M</a> - </strong>Coefficients of the spline basis functions for each parameter. Refer c<sub>ij</sub> in equation 11. This is our preferred global model of shear-wave velocity. In this model, radial anisotropy is confined to the uppermost mantle (that is, since the anisotropy is parameterized with only the four uppermost splines, it becomes very small below a depth of 250 km, and vanishes at 410 km). This is an updated version of S362ANI (Kustowski et al., 2008) which did not include normal modes in its derivation. Please note the stronger isotropic shear velocity anomalies in the transition zone.</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/STW105"><strong>STW105</strong></a> - reference model used in S362ANI+M. Described in Kustowski et al. (2008)</li> <li><strong><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/setup.cfg">setup.cfg</a> - </strong>Some configuration metadata relevant to this model for reproducibility.</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/epix.tar.gz"><strong>epix.tar.gz</strong></a> - Perturbations in horizontally (vsh) and vertically polarized shear velocity (vsv), Voigt-average isotropic velocity (vs), ansotropy (as) and topography of the internal boundaries. This is calculated from the spline coefficients at every 1 by 1 degree cell-centered pixel and at every ~25 km depth region from Moho to the core-mantle boundary and stored in extended pixel format (.epix) ASCII files. </li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM.BOX25km_PIX1X1.avni.nc4"><strong>S362ANI+M.BOX25km_PIX1X1.avni.nc4</strong></a> - The perturbations in a standard AVNI format that utilizes the NETCDF4 container format. This file can be read in Python using either xarray or AVNI libraries. For example, to plot vs perturbations at 24.4-50 km depth range <ul> <li><em>import xarray as xr</em></li> <li><em>ds = xr.open_dataset('S362ANI+M.BOX25km_PIX1X1.avni.nc4')</em></li> <li><em>ds.vs[0].plot()</em></li> </ul> </li> <li><strong>Fortran Code</strong> <ul> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/readme"><strong>readme</strong></a> - contains a description of all files in the folder below</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/PROGRAMS.tar.gz"><strong>PROGRAMS.tar.gz</strong></a> - tools for obtaining model values at specific locations and some GMT plotting tools</li> </ul> </li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/GRD.tar.gz"><strong>GRD.tar.gz</strong></a> - longitude-latitide-velocity files with vsh, vsv, and Voigt average in km/s evaluated on a grid of points at many depths in the mantle</li> </ul>
D-LONG
<p>d-LONG</p>
Supplementary dataset for paper Long-period directivity pulses of strong ground motion during the 2023 Mw7.8 Kahramanmaraş earthquake
<p>Supplementary dataset for paper Long-period directivity pulses of strong ground motion during the 2023 Mw7.8 Kahramanmaraş earthquake by František Čejka, Jiří Zahradník, Fatih Turhan, Efthimios Sokos, and František Gallovič</p>
Modified LRphase and Simulated Dataset for "LRphase: an efficient algorithm for assigning haplotypic identity to long reads"
<p><strong>A modified version of LRphase was used to simulate reads for a single hypothetical human genome with maternal and paternal phasing information. Briefly, haplotype-specific reference sequences were generated with `bcftools consensus` <a href="https://paperpile.com/c/VO12CC/SIk9">(Li 2011)</a> based on the rescued GIAB VCF and hg38 human reference sequence. Each haplotype-specific fasta was fed separately into pbsim2 <a href="https://paperpile.com/c/VO12CC/NMmE">(Ono, Asai, and Hamada 2021)</a> as the reference from which simulated reads were randomly drawn, up to 1X coverage. Parameters controlling the read length distribution, sequencing, and base calling error rates were set to emulate typical performance of the MinIon sequencing platform with flow cell version R10.4.1 (https://nanoporetech.com/products/minion). These are as follows: `--depth 1 –hmm_model R103.model --difference-ratio '23:31:46' --length-mean 25000 --length-min 100 --length-max 1000000 –length-sd 20000 --accuracy-mean 0.98 --accuracy-min 0.01 --accuracy-max 1.00`. Simulated reads were aligned to the hg38 reference genome with minimap2 <a href="https://paperpile.com/c/VO12CC/Y2HP">(Li 2018)</a> and correct phasing and alignment coordinates were encoded in the read names. Finally, samtools <a href="https://paperpile.com/c/VO12CC/YLss">(Li et al. 2009)</a> was used to remove duplicated and supplementary reads, and concatenate, sort, and index reads into a single combined bam file. Of 258,539 total reads, 246,210 were mappable, and 178,504 overlapped at least one heterozygous variant in HG001.</strong></p>
The 3-week-long transport history and deep tropical origin of the 2021 extreme heat wave in the Pacific Northwest
<p>This archive includes the data used for the manuscript "The 3-week-long transport history and deep tropical origin of the 2021 extreme heat wave in the Pacific Northwest" submitted to Geophysical Research Letter.<br> </p>
Parc Cwm Long Cairn
Parc Cwm Long Cairn [https://coflein.gov.uk/en/site/93072](https://coflein.gov.uk/en/site/93072) *AHRC (UK) AH/L007916/1* Source: Objaverse 1.0 / Sketchfab
FIGURES 31–42. FIGURES 31–36 in Five new species of Acanthobothrium (Cestoda: Onchoproteocephalidea) from the long-tailed butterfly ray, Gymnura cf. poecilura (Elasmobranchii: Gymnuridae) from the Persian Gulf and Gulf of Oman
FIGURES 31–42. FIGURES 31–36. Scanning electron micrographs of Acanthobothrium halehae n. sp. 31. Scolex. Note: Small numbers on scolex correspond to the figures showing higher magnification images of these surfaces, and white arrow tip show the marginal lappet. 32. Apical pad and hooks. 33. Surface of apical pad. 34. Proximal bothridial surface. 35. Distal bothridial surface. 36. Cephalic peduncle surface. FIGURES 37–42. Scanning electron micrographs of Acanthobothrium makranense n. sp. 37. Scolex. 38. Apical pad and hooks. 39. Surface of apical pad..40. Proximal bothridial surface. 41. Distal bothridial surface. 42. Cephalic peduncle surface. Scale bars: Fig 31=100 µm; Fig. 37=70 µm; Fig. 38=50 µm; Fig. 32=40 µm; Figs. 36, 42=2 µm; Figs. 33, 34, 35, 39, 40, 41=1 µm.
FIGURES 10–21. FIGURES 10–15 in Five new species of Acanthobothrium (Cestoda: Onchoproteocephalidea) from the long-tailed butterfly ray, Gymnura cf. poecilura (Elasmobranchii: Gymnuridae) from the Persian Gulf and Gulf of Oman
FIGURES 10–21. FIGURES 10–15. Scanning electron micrographs of Acanthobothrium omanense n. sp. 10. Scolex. Note: Small numbers on the scolex correspond to the figures showing higher magnification images of these surfaces, and white arrow tip show the marginal lappet. 11. Apical pad and hooks. 12. Surface of apical pad. 13. Proximal bothridial surface. 14. Distal bothridial surface. 15. Cephalic peduncle surface. FIGURES 16–21. Scanning electron micrographs of Acanthobothrium kurdistanense n. sp. 16. Scolex. 17. Apical pad and hooks. 18. Surface of apical pad. 19. Proximal bothridial surface. 20. Surface of anterior region of strobila. 21. Distal bothridial surface. Scale bars: Fig 16=100; Fig. 10=80 µm; Figs. 11, 17=40 µm; Figs 15, 20=2 μm; Figs. 12, 13, 14, 18, 19, 21=1 µm.
FIGURES 47–52 in Five new species of Acanthobothrium (Cestoda: Onchoproteocephalidea) from the long-tailed butterfly ray, Gymnura cf. poecilura (Elasmobranchii: Gymnuridae) from the Persian Gulf and Gulf of Oman
FIGURES 47–52. Scanning electron micrographs of Acanthobothrium persicum n. sp. 47. Scolex. Note: Small numbers on scolex correspond to the figures showing higher magnification images of these surfaces and white arrow tip show the marginal lappet. 48. Apical pad and hooks. 49. Surface of apical pad. 50. Proximal bothridial surface. 51. Distal bothridial surface. 52. Cephalic peduncle surface. Scale bars: Fig. 47=100 µm; Fig. 48=40 µm; Fig. 52=3 µm; Figs. 50=2 µm; Figs. 49, 51=1 µm.
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.