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Lactobacillus johnsonii N6.2 total lipid and fractionated lipids profiling by qualitative lipidomic LC-MS/MS analysis
<p>Table presents both MS-1 (precursor mass-matched) and MS-2 (precursor mass- and spectral-matched) annotations. The values in the table represent the peak area. The column labels, RT: retention time; m/z: mass-to-charge ratio; SL (simple lipids), GL (glycolipids), and PL (phospholipids) represent lipid fractions and TL: total lipids. Table is provided as an xlsx file.</p>
Vertical hydrography profiles from CTD rosette downcasts during PolarFront cruise 2022-05
<p>Hydrography data from CTD (SBE911plus, Seabird Inc.) profiles. Rosette equipped with the following sensors:</p> <ul> <li>Conductivity</li> <li>Temperature</li> <li>Pressure</li> <li>Fluorometer</li> <li>Turbidity</li> <li>PAR</li> <li>Oxygen</li> </ul> <p>Update December 2024</p> <p>The salinity and temperature sensors were calibrated against another CTD from a moored instrument by Ragnheid Skogseth at UNIS, the University Centre in Svalbard. A relatively large drift in temperature was observed. To convert temperature (T) and salinity (S) to calibrated values apply the following equations to e.g. data from stnrxxxx_bin.cnv</p> <p>T_new = T_old + 0.12<br>S_new = 1.0115 * S_old – 0.5343</p> <p>The following is quoted verbatim from chapter 1 in the cruise report (Basedow, 2022):</p> <blockquote> <p>Hydrographic data were collected by a variety of sensors mounted on vertical profiling platforms, towed platforms and autonomous gliders. Combined, these platforms provided detailed information at stations, high-resolution measurements across the polar front, and longer-term measurements by the gliders. During the cruise, hydrographic measurements were taken at stations using the main rosette equipped with 12 5-L Niskin bottles, CTD-F, PAR and other sensors (Table 1.1) and using a smaller rosette frame equipped with CTD-F, LOPC, LISST and WBAT (Table 1.2, Fig. 1.1). Both platforms were deployed vertically until 5-10 m above the bottom for the main platform and down to 300 m for the platform with the LOPC, this rosette sampling three profiles at selected stations.</p> <p>In total 14 vertical profiles were sampled by the rosette with the water bottles (Table 1.1) at our 6 main stations (PF1 to PF6). Water samples for biological analyses were taken from selected depths and a bottom water samples was collected at each station for calibration of the conductivity sensor ashore. Water samples for chlorophyll a will be used to calibrate the fluorescence sensor. CTD data from this rosette were processed using the SBEDataProcessing-Win32 software. Only the values from the CTD downcast were used to avoid turbulence caused by the rosette on the upcast. The data were converted<br>to physical units, filtered for outliers and bin-averaged over 1 m bins. </p> </blockquote> <p><strong>References</strong></p> <p>Sünnje Basedow, Nicolas Gosset, Torkel Granaas, Eva Leu (2022). Hydrography. In: Malin Daase (ed.) (2022). PolarFront May 2022 Cruise Report. Zenodo. https://doi.org/10.5281/zenodo.7128746</p>
EPSAPG: A Pipeline Combining MMseqs2 and PSI-BLAST to Quickly Generate Extensive Protein Sequence Alignment Profiles
<p>This repository contains all data, queries, and search results used in the analysis of</p> <ul> <li>Arab, Issar. “<strong>EPSAPG: A Pipeline Combining MMseqs2 and PSI-BLAST to Quickly Generate</strong><br><strong>Extensive Protein Sequence Alignment Profiles</strong>.” IEEE/ACM 10th International Conference on<br>Big Data Computing, Applications and Technologies (BDCAT ’23), December 4–7, 2023,<br>Taormina, Messina, Italy. <a href="https://doi.org/10.1145/3632366.3632384">doi.org/10.1145/3632366.3632384</a></li> </ul>
The pan-epigenome of the symbiotic nitrogen fixing bacterium Sinorhizobium meliloti unravels unexpected variability of DNA-methylation profiles in closely related strains
<p>Supplementary Dataset S1. Genome coverage data and assignment of contigs to <em>S. meliloti</em> 1021 genome replicons. MS Excel file format (.xlsx file)</p> <p>Supplementary Dataset S2. Folder containing summary pangenome statistics, core and accessory orthologs, alignments and R script. Zip archive</p> <p>Supplementary Dataset S3. Number motifs and methylated motifs identified and their ratio. Data on number of motifs (RAW), number of methylated motifs (METH), fraction of methylated motifs (RATIO) related to functional features (CDSid, tIG and US sequences) and to replicons (CHR, chromosome; PA, pSymA; PB, pSymB and other) are reported. Red color in columns from “other” indicate missing data (i.e., absence of replicons other than chromosome, pSymA, pSymB). .xlsx file</p>
Effects of maternal calcium propionate supplementation on offspring productivity and meat metabolomic profile in sheep
<p>data set from meat metabolome from lambs</p>
Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy
<p>Quantifying neuron morphology and distribution at the whole brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single cell labeling and whole brain imaging to study human brains. We propose Adaptive Cell Tomography (ACTomography), a low-cost, high-throughput, high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and 1 donated fresh postmortem brain. We collected 3-D images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor-field of neuron morphology to characterize anatomical modularity of a human brain.</p>
Scalar flux profiles in the unstable atmospheric surface layer under the influence of large eddies: Implications for eddy covariance flux measurements and the non-closure problem
<p>This dataset contains the data used in the submitted manuscript of Liu, Liu, Huang, Desai, Zhang, Ghannam, and Katul 2023. Please refer to the manuscript for the detailed description of the dataset.</p>
Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity
<p>Raw data for Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity </p>
Data used in "Multi-omic profiling reveals the endogenous and neoplastic responses to immunotherapies in cutaneous T cell lymphoma"
<p>Data generated from the clinical trials, CITN-10 (NCT02243579) and CITN-13 (NCT03063632), analyzing the in vivo responses to anti-PD-1 monotherapy or anti-PD-1 interferon-gamma combination therapy in patients with advanced mycosis fungoides and sezary syndrome. Data include mass cytometry files of PBMCs, Olink serum targeted proteomics, Nanostring targeted bulk transcriptomics of tumor biopsies, CODEX imaging of tumor biopsies, and TCR sequencing from peripheral blood and tumor biopsies. Please direct correspondences to DRG or EWN.</p>
Fig. 6 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 6. Predicted cis-acting elements in the TdGASA genes promoter regions. The 2-kb sequences upstream of the 19 TdGASA genes were analyzed with the PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html) and New PLACE (https://www.dna.affrc.go.jp/PLACE/?action=new place) databases. The cis-acting elements were classified into three major classes: hormone-related cis-elements, development-related cis-elements, and stress-related cis-elements.
Fig. 8 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 8. Expression of TdGASA1, TdGASA4, TdGASA14, and TdGASA19 genes confers stress tolerance to yeast cells. Wild-type transformed with empty vector (EV) or with four TdGASA genes were grown for 4 days under normal growth conditions (30 ◦ C) or under heat (37 ◦ C or 42 ◦ C), ionic (LiCl 100 mM), salt stress (NaCl 2 M), osmotic stress (Mannitol 2 M), and oxidative stress (H2O2 10 mM) in rich solid media a containing galactose as carbon source. The growth assays depicted are reflective of three independent replicates (A). (B) Cell growth (OD600) of wild-type transformed with empty vector (EV) or with four TdGASA genes under different stress conditions. Error bars represent calculated standard error of the mean (SEM) of three independent replicates. Different letters on bars represent the significant values according to Duncan's test (p <0.05).
Fig. 7 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 7. Expression pattern of durum wheat GASA genes. (A) Heatmap of the expression pattern of TdGASA genes in roots, stems, leaves, and seeds. (B) Heatmap showing the expression pattern of TdGASA genes T. durum plants subjected to 150 mM NaCl, 15% PEG-6000, 50 μM GA3 and 50 μM ABA. The data represent means of three independent experiments. Color code is presented above the heatmap. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 1. Locations of the 19 TdGASA genes on durum wheat chromosomes. The scale on the left represented the length of the chromosomes. Mb = million base pair. The pairs of duplicated genes are underlined with same color. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 5. Analysis of 19 TdGASA genes structures. (A) An unrooted phylogenetic tree constructed based on TdGASA genes sequences. (B) Exon-intron structure analysis, blue boxes represent untranslated regions, yellow boxes and black lines were exon and intron positions, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 2. Predicted three-dimensional structures of TdGASA proteins. Models were generated by using Phyr2 server. The secondary structure elements: α-helices (blue), β-sheets (yellow), and coils (cyan) are indicated for the predicted 3D structures of TdGASA proteins. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 4. Analysis of Triticum durum TdGASA proteins structures. (A) An unrooted phylogenetic tree generated using TdGASA protein sequences. (B) Motif identification using MEME. (C) TdGASA protein structure (D) Multiple sequence alignments of GASA domain. (E) Logo of the TdGASA conserved-domain.
Fig. 3 in Genome-wide characterization and expression profiling of GASA gene family in Triticum turgidum ssp. durum (desf.) husn. (Durum wheat) unveils its involvement in environmental stress responses
Fig. 3. Phylogenetic tree analysis of B. distachyon, O. sativa, S. bicolor, A. thaliana, T. aestivum, T. turgidum, and H. vulgare GASA proteins. Maximum likelihood method with 1000 bootstrap replicates was used to compute the distances of GASA proteins by using the MEGA11 software. The four subgroups of GASAs are presented with different colors. Black triangles denote B distachyon (Bd) proteins, yellow triangles denote the O. sativa (Os) proteins, blue triangles denote the S. bicolor (Sb), red triangles are for A. thaliana (At) proteins, black circles refer to T. turgidum (TdGASA) proteins, blue diamond's indicate T. aestivum (Ta) proteins, and yellow diamonds are for H. vulgare (Hv) proteins. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Guaiane-rich phytochemical profile of Centaurea kotschyi subsp. persica (Boiss.) Wagenitz and identification of hypoglycaemic metabolites
Fig. 2. LC-MS profile of the CH2Cl2 extract obtained from Centaurea kotschyi subsp. persica aerial parts.
Fig. 1 in Guaiane-rich phytochemical profile of Centaurea kotschyi subsp. persica (Boiss.) Wagenitz and identification of hypoglycaemic metabolites
Fig. 1. Chemical structures of specialized metabolites isolated from Centaurea kotschyi subsp. persica.
Fig. 5 in Guaiane-rich phytochemical profile of Centaurea kotschyi subsp. persica (Boiss.) Wagenitz and identification of hypoglycaemic metabolites
Fig. 5. COSY (red bold), key HMBC (black arrows) and NOESY (blue arrow) correlations detected for compound 15. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
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.