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19,342 results for “sequence”
Fluorescent (C)LSM image sequences of Dictyostelium discoideum (Ax2 - LifeAct mRFP) for cell track and cell contour analysis
<p>This data set is designed for cell contour and cell track analysis. Hence image sequences of moving Dictyostelium discoideum cells are recorded. For the purpose to facilitate the detection of the cell contour we take fluorescent images of the cortical protein actin to obtain a high contrast between background and cell body. In each image sequences several cells are recorded. This allows for an analysis of all cells at once or to crop single cell tracks.</p>
Co- and Post-seismic Crustal Deformation Associated with the 2016 Kumamoto Earthquake Sequence Revealed by PALSAR-2 Pixel Tracking and InSAR
<p>This archive includes the dataset for the co- and post-seismic displacements associated with the 2016 Kumamoto earthquake in Japan detected by ALOS-2/PALSAR-2 data. All files are formatted as the MATLAB format. ALOS-2/PALSAR-2 level 1.1 data in this study were provided from the PIXEL (PALSAR Interferometry Consortium to Study our Evolving Land Surface) under a cooperative research contract with the Earthquake Research Institute, University of Tokyo. The ownership of ALOS-2/PALSAR-2 level 1.1 data belongs to JAXA.</p> <p> </p> <p>coseismic_datav1.mat contains the original PALSAR-2 pixel tracking data and 3D displacement components. You can display 3D displacement field using "display_3Ddisp.m".</p> <p>coseismc_flocv1.mat contains the isolated displacement discontinuities in the observation data.</p> <p>postseismic_asc_v1.mat contains the PALSAR-2 original InSAR data in the ascending orbit.</p> <p>postseismic_dsc_v1.mat contains the PALSAT-2 original InSAR data in the descending orbit.</p> <p>script_acrossp_p.m generates the profiles of post-seismic displacement profile across the profile.</p> <p>script_alongp_c.m generates the profiles of co-seismic displacement along the fault.</p> <p>script_alongp_p.m generates the profiles of post-seismic displacement along the fault.</p> <p>script_quasi_def.m generates the quasi-eastwest and the quasi-vertical displacement fields.</p> <p>script_ts.m generates the time-series of line-of-sight change using the sequence of InSAR data.</p> <p>-</p> <p>display_3Ddisp.m displays 3D displacement fields using "coseismic_datav1.m".</p> <p>coseis_Fdisp.mat contains data for along-fault displacement. (Lon, Lat, vertical, stv_vertical, horizontal_alongfault, stv_horizontal_alongfault, and topography)</p> <p>display_coseis_alongdisp.m generates figures for the along-fault displacement distribution using "coseis_Fdisp.mat".</p>
VFTS meeting: animation of main-sequence model evolution
<p>This animation shows the evolution of our binary and single stellar models from 2Myr to 100Myr. We populate 3763 binaries, whose primary mass is in the range of 3Msun to 100Msun, following a Salpeter IMF with an exponent of -2.37. The mass ratio is uniformly distributed from 0.1 to 1. The orbital period logP is uniformly distributed from the minimum value at which the two stars would contact initially to 3.5. Both components rotate at half of their critical velocities initially. </p> <p>Considering a binary fraction of 70%, we populate 1612 single stars with vi=0.5. In addition, we also populate 537 slowly-rotating single stars with vi=0.2 to reproduce the observed blue MS in young star clusters. The number is chosen such that the ratio between the slow and fast rotators is 1/3, which is the same as the ratio of observed blue and red MS stars. </p> <p>Gravity darkening and observational errors are included. Filled circles correspond to single stellar models, while open symbols correspond to binaries with different companions. Single stellar tracks with vi=0.5 are plotted with solid grey lines. The black dotted line represents the ZAMS line of vi=0.2 single stellar models. In the legend, the number in each group outside the parenthesis corresponds to the number of stars whose color and magnitude are in the figure range. While the number in the parenthesis corresponds to the number of stars above the orange dashed line, which is 1.75 mag below the turn-off magnitude. </p>
Dataset of 'Using Sequence-to-Sequence Learning for Repairing C Vulnerabilities'
<p>This is the dataset we collected for the 'Using Sequence-to-Sequence Learning for Repairing C Vulnerabilities' paper. See the description in the paper for how the dataset was collected. Please cite 'Using Sequence-to-Sequence Learning for Repairing C Vulnerabilities' if you use the dataset.</p> <p> </p> <p>src-all.txt and tgt-all.txt contain the tokenized function pairs and are ready to used as training data. Each line in both txt file corresponds to a function before and after a commit that was classified as a bug fix commit.</p> <p> </p> <p>The two tar files contain the raw data that was used to generate both txt files. Both containing the commits that were collected during the respective year.</p>
YaCoS: a Complete Infrastructure to the Design and Exploration of Code Optimization Sequences
<p>The growing popularity of machine learning frameworks and algorithms has greatly contributed to the design and exploration of good code optimization sequences. Yet, in spite of this progress, mainstream compilers still provide users with only a handful of fixed optimization sequences. Finding optimization sequences that are good in general is challenging because the universe of possible sequences is potentially infinite. This paper describes a infrastructure that provides developers with the means to explore this space. Said infrastructure, henceforth called YaCoS, consists of benchmarks,search algorithms, metrics to estimate the distance between programs, and compilation strategies. YaCoS’s features let users build learning models that predict, for unknown pro-grams, optimization sequences that are likely to yield good results for them. In this paper, as a case study, we have used YaCoS to find good optimization sequences for LLVM, using code size as the objective function. Such study lets us evaluate three feature sets: two variations of the feature vectors proposed by Namolaru at al in 2010, plus the optimization statistics produced by LLVM. Our results show that YaCoSis able to find sequences that improve onto clang -Oz by3.75% on average. Our experiments do not indicate a dominant feature set out of the three approaches that we have investigated—it is possible to find programs in which one of them is strictly better than the others.</p>
Supplementary datasets for: Large-scale genome sequencing reveals the driving forces of viruses in microalgal evolution
<p>Microalgae are integral primary producers for global ecosystems whose genomes can be mined for ecological insights, but representative genome sequences are lacking for many phyla. We cultured and sequenced 107 microalgae species from 11 different phyla indigenous to varied geographies and climates. This genome collection was used to resolve genomic differences between saltwater and freshwater microalgae. Freshwater species showed domain-centric ontology enrichment for nuclear and nuclear membrane functions, while saltwater species were enriched in organellar and cellular membrane functions. Marine species contained significantly more viral families in their genomes (<span>p-value = 8 x 10(-4))</span>. Viral sequences were identified from Chlorovirus, Coccolithovirus, Pandoravirus, Marseillevirus, Tupanvirus, and others integrated into algal genomes. Algal, viral-origin sequences were found to be expressed and to code for a wide variety of functions. Our results clarify the poorly characterized occurrences of viral elements in algal genomes and define a unified adaptive strategy for algal halotolerance.</p>
Data from: Evolutionary and phylogenetic insights from a nuclear genome sequence of the extinct, giant subfossil koala lemur Megaladapis edwardsi
<p><span>No endemic Madagascar animal with body mass >10 kg survived a relatively recent wave of extinction on the island. From morphological and isotopic analyses of skeletal 'subfossil' remains we can reconstruct some of the biology and behavioral ecology of giant lemurs (primates; up to ~160 kg), elephant birds (up to ~860 kg), and other extraordinary Malagasy megafauna that survived well into the past millennium. Yet much about the evolutionary biology of these now extinct species remains unknown, along with persistent phylogenetic uncertainty in some cases. Thankfully, despite the challenges of DNA preservation in tropical and sub-tropical environments, technical advances have enabled the recovery of ancient DNA from some Malagasy subfossil specimens. Here we present a nuclear genome sequence (~2X coverage) for one of the largest extinct lemurs, the koala lemur <i>Megaladapis edwardsi </i>(~85kg). To support the testing of key phylogenetic and evolutionary hypotheses we also generated new high-coverage complete nuclear genomes for two extant lemur species, <i>Eulemur rufifrons</i> and <i>Lepilemur mustelinus</i>, and we aligned these sequences with previously published genomes for three other extant lemur species and 47 non-lemur vertebrates. Our phylogenetic results confirm that <i>Megaladapis</i> is most closely related to the extant Lemuridae (typified in our analysis by <i>E. rufifrons</i>) to the exclusion of <i>L. mustelinus</i>, which contradicts morphology-based phylogenies. Our evolutionary analyses identified significant convergent evolution between <i>M. edwardsi</i> and extant folivorous primates (colobine monkeys) and ungulate herbivores (horses) in genes encoding protein products that function in the biodegradation of plant toxins and nutrient absorption. These results suggest that koala lemurs were highly adapted to a leaf-based diet, which may also explain their convergent craniodental morphology with the small-bodied folivore <i>Lepilemur</i>.</span></p>
CusVarDB: A tool for building customized sample-specific variant protein database from Next-generation sequencing datasets
<p>CusVarDB is a windows based tool for creating a variant protein database from Next-generation sequencing datasets. The program supports variant calling for Genome, RNA-Seq and exome datasets.</p> <p>This repository will provide the resultant variant peptides identified in our study and its corresponding information. The detailed information of the table is given below.</p> <p>Supplementary Table 1. This table contains the resultant variant peptides along with its wild-type peptides from BT474, MDMAB157, MFM223, and HCC38 datasets. Along with mutant peptides, this section also provides additional information such as peptide-spectrum match (PSM), Protein accession, cross-correlation value from the search (Xcorr), and retention time (RT).</p> <p>Supplementary Table 2. This table provides the complete details of the resultant peptides. Here the mutant and corresponding wild-type peptides are mentioned in different sheets. For a given mutant peptide its wild-type peptide and corresponding information can be mapped using the VLOOKUP function in Excel by keeping column A (Sl.No) as lookup parameter.</p> <p>Supplementary Table 3. This table briefs about the variants which are already reported in other cancers.</p>
Multiple sequence alignment for the native Norwegian vascular plant phylogeny
<p>Methods: We produced a multi-locus Maximum Likelihood (ML) phylogeny using a combination of newly produced DNA sequences from herbarium specimens and sequences available from public repositories. We combined the phylogeny with species occurrence data to estimate phylogenetic diversity and phylogenetic endemism across Norway, using a spatial randomization to judge statistical significance. We used multiple-model inference to identify environmental variables that contributed the most to the patterns of phylogenetic diversity. Finally, we estimated phylogenetic turnover and used this to identify Norwegian plant assemblages in terms of composition and evolutionary history.<br> <br> Results: Our ML phylogeny contained 87% of all currently described native Norwegian vascular plants. Assemblages were phylogenetically overdispersed in warmer and wetter regions of Norway, as well as in regions with a longer post-glacial history. In cold and dry regions, plant assemblages were phylogenetically clustered, and characterised by neo-endemism, while the mild and wet regions were characterised by both paleo- and neo-endemism. Phylogenetic diversity was positively correlated with summer temperature and habitat heterogeneity, and peaked in the southeast of Norway.<br> <br> Main conclusions: Both contemporary ecological factors (climate and habitat heterogeneity), and post-glacial history seem to have shaped the phylogenetic structure of the flora of Norway. The flora in the far north of Norway appear to be a result of recent diversification while the coastal regions are assemblages of deeper lineages. Our results suggest that there is an evolutionary signal in the distribution of the Norwegian vascular flora.</p>
Single-cell repertoire and transcriptome sequencing reveals clonally expanded and transcriptionally distinct lymphocytes in aged CNS
<p>Single-cell repertoire and transcriptome sequencing reveals clonally expanded and transcriptionally distinct lymphocytes in aged CNS. Gene expression and immune receptor repertoire sequencing was performing for both B and T cells. This dataset contains the VDJ sequencing information for the four samples. Each B cell and T cell library was sequenced across four lanes. </p> <p> </p> <p>Files with _WT_ in their name correspond to the young (4-6 week B6 mice) </p> <p>Files with _12_ in their name before the BDJ or VDJ text correspond to the 12-month-old cohort.</p> <p>Files with _18_ in their name before the BDJ or VDJ text correspond to the 18-month-old cohort in which four brains were pooled.</p> <p>Files with 4_18_ in their name before the BDJ or VDJ text correspond to the 18-month-old mouse that was processed and sequenced alone. </p> <p> </p> <p>The L001 - L004 in the file names indicates the sequencing lane. Samples with BDJ correspond to the B cell repertoire library (B cell VDJ). Samples with TDJ correspond to the T cell repertoire library (T cell VDJ). </p>
A codon model for associating phenotypic traits with altered selective patterns of sequence evolution
<p>Detecting the signature of selection in coding sequences and associating it with shifts in phenotypic states can unveil genes underlying complex traits. Of the various signatures of selection exhibited at the molecular level, changes in the pattern of selection at protein coding genes have been of main interest. To this end, phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. Many of these methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that phenotypic transitions have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the primate SEMG2 gene in polygynandrous species compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from a free-living to an endosymbiotic lifestyle.</p>
Single-cell immune repertoire sequencing of two convalescent COVID-19 patients
<p>Single-cell immune repertoire sequencing of two convalescent COVID-19 patients using 10x genomics 5' immune profiling. Resulting output files are from the count and vdj functions from 10x genomic's cellranger v3.1.0. </p>
Homology analysis of HCV sequences obtained from a dialysis unit of northeast India
<p>This is a homology analysis (by DNASTAR MegaAlign Version 5.00) of 29 HCV Sequences (5'UTR-Core region sequencing) obtained from a dialysis unit of a tertiary care teaching hospital in northeast India. It is a part of a manuscript titled- "Circulation of an atypical hepatitis C virus (HCV) strain in a dialysis unit in northeast India". </p>
Supplementary table with homology analysis of twenty nine HCV sequences ((5'UTR-Core region) )
<p>It is a supplementary data table with homology analysis of 29 HCV sequences ((5’UTR-Core region) obtained from a dialysis unit of a tertiary care teaching hospital of Northeast India (Assam). It is a part (supplementary data) of the manuscript titled - "Circulation of an atypical hepatitis C virus (HCV) strain in a dialysis unit in northeast India" </p>
Multiple drainage reversal episodes and glacial refugia in a Patagonian fish revealed by sequenced microsatellites
<p>The rise of the southern Andes and the Quaternary glacial cycles influenced the landscape of Patagonia, affecting the phylogeographic and biogeographic patterns of its flora and fauna. Here we examine the phylogeography of the freshwater fish, Percichthys trucha, using 53 sequenced microsatellite DNA markers. Fish (N=835) were collected from 16 river systems (46 locations) spanning the species range on both sides of the Andes. Eleven watersheds drain to the Pacific, five of which are trans-Andean (headwaters east of Andes). The remaining five drainages empty into the Atlantic. Three analytical approaches (neighbour-joining tree, hierarchical AMOVAs, STRUCTURE) revealed evidence of historic drainage reversals: Fish from four of the five trans-Andean systems (Puelo, Futalaufquen/Yelcho, Baker, Pascua) exhibited greater genetic similarity with Atlantic draining systems than with Pacific systems with headwaters west of Andes. Present-day drainage (Pacific vs. Atlantic) explained only 5% of total genetic variance, while ancestral drainage explained nearly 27% of total variance. Thus, the phylogeographic structure of Percichthys trucha is consistent with episodes of drainage reversal in multiple systems and suggests a major role for deglaciation in the genetic and indeed the geographic distribution of P. trucha in Patagonia. The study emphasizes the significant role of historical processes in the current pattern of genetic diversity and differentiation in a fish from a southern temperate region.</p>
Influence of Quaternary environmental changes on mole populations inferred from mitochondrial sequences and evolutionary rate estimation
<p><span><span><span><span><span><span><span><span><span><span><span>Quaternary environmental changes fundamentally influenced genetic diversity of the temperate-zone terrestrial animals, including those on the Japanese Archipelago. The genetic diversity of present-day populations are taxon and region specific, but its determinants are poorly understood. Here, we analyzed cytochrome <i>b</i> gene (<i>Cytb</i>) sequences (1,140 bp) of mitochondrial DNA (mtDNA) to elucidate factors determining the genetic variation in three species of large moles: <i>Mogera imaizumii</i> and <i>Mogera wogura</i> occur in Northern and Southern mainland Japan (Honshu, Shikoku, and Kyushu), and <i>Mogera robusta </i>occurs on the nearby Asian continent<i>.</i> Network construction with the <i>Cytb</i> sequences revealed 10 star-shaped clusters with apparent geographic affinity. Mismatch distribution analysis showed that modes of pairwise nucleotide differences (t values) were grouped into five classes in terms of the level, implying the occurrence of five stages for the rapid expansion. It is conceivable that a severe cold periods and a subsequent warm periods during the late Quaternary are responsible for the population expansion events. The first and third oldest events include island-derived haplotypes, indicative of involvement of land bridge formation between remote islands, hence suggesting association of the ends of the penultimate (PGM, ca. 130,000 years ago) and last (LGM, ca. 15,000 years ago) glacial maxima, respectively. Since the third one is followed by the fourth one, it is plausible that the termination of Younger Dryas and subsequent abrupt warming at ca. 11,500 years ago facilitated the fourth expansion event. The second is most likely corresponding to the early marine isotope stage (MIS) 3 (ca. 53,000 years ago) when the glaciation and subsequent warming period are predicted to have influenced biodiversity. Utilization of the critical times of 130,000, 53,000, 15,000, and 11,500, years ago as calibration points yielded evolutionary rates of 0.03, 0.045, 0.10 and 0.10 substitutions/site/million years, respectively, showing the time-dependent manner whose pattern is similar to that seen in small rodents reported in our previous studies. The age of the fifth expansion event was calculated to be 5,800 years ago with the rate of 0.10 substitutions/site/million years ago, during the mid-Holocene, suggestive of influence of humans or other unspecified reason, such as the Jomon marine transgression. </span></span></span></span></span></span></span></span></span></span></span></p>
An automatically generated high-resolution earthquake catalogue for the 2016-2017 Central Italy seismic sequence, including P and S phase arrival times
<p>Catalog of 440,697 earthquakes of the 2016-2017 Central Italy seismic sequence semi-automatically generated by Spallarossa et al. (2020). The catalogue covers one year of aftershocks following the first mainshock of the sequence (from 08242016 to 08312017).</p> <p>The catalog has been generated using the Complete Automatic Seismic Processor (CASP) procedure (Scafidi et al., 2019) to detect the events and an advanced picker engine (RSNI-Picker<sub>2</sub>; Scafidi et al., 2018; Spallarossa et al., 2014) to determine their phase arrival times. The final set of about 7 million P- and 10 million S-wave arrival times have been used to locate the events using a non-linear location algorithm (NonLinLoc; Lomax et al. 2000), with a 1D velocity model calibrated for the area (De Luca et al., 2009) and station corrections. For each event, also local magnitudes (M<sub>L</sub>) has been calculated as well as a locations quality.</p> <p>Earthquake locations quality has been classified by means of the procedure proposed by Michele et al., (2019) consisting of the combination of diverse uncertainty parameters provided by the NonLinLoc location code. Locations quality is provided in terms of a unique numeric normalized value, named quality factor, varying between qf=0 (best quality location) and qf=1 (worst quality location). Then locations have been assigned to a quality class depending on the qf parameter value according to the following scheme: A-class (0 < qf ≤ 0.25), B-class (0.25 < qf ≤ 0.50), C-class (0.50 < qf ≤ 0.75), and D-class (0.75 < qf < 1.00). The earthquake locations are distributed between the quality classes as A-30.6%, B-31.4%, C-18.6%, and D-19.4% (details in Spallarossa et al., 2020).</p> <p>We accompanied the catalogue with the 30 events with M>3.5 missed by our procedure (bring the total number of events to 440,727), including the first Amatrice mainshock (M<sub>W</sub>6.0; see Spallarossa et al., 2020). These 30 missing events recognisable by the ID starting with ISI), have been taken from INGV bulletin (<a href="http://terremoti.ingv.it">http://terremoti.ingv.it</a>; ISIDe Working Group., 2007), manually generated. These additional events report INGV locations and magnitude parameters while are missing related quality factors and quality class, being generated by a different procedure.</p> <p>We added to the larger events, the available moment magnitudes (M<sub>W</sub>) from Time Domain Moment Tensor catalogue (<a href="http://terremoti.ingv.it/tdmt">http://terremoti.ingv.it/tdmt</a>; Scognamiglio et al., 2006).</p> <p>The catalog is in csv format, semicolon separator, ordered by origin time and the header content is the following:</p> <ul> <li>Id-event – ID</li> <li>Latitude (°) expressed in decimal degrees - LAT</li> <li>Longitude (°) expressed in decimal degrees - LON</li> <li>Depth(km) hypocentral depth expressed in kilometres - DEP</li> <li>Year of origin time in the format yyyy - YR</li> <li>Month of origin time in the format mo - MON</li> <li>Day of origin time in the format dd - DY</li> <li>Hour of origin time in the format hh - HR</li> <li>Minute of origin time in the format mi - MIN</li> <li>Second of origin time in the format XX.XXX s - SEC</li> <li>Local Magnitude - ML</li> <li>Standard deviation of the Local Magnitude – STD</li> <li>Moment Magnitude – Mw (from TDMT)</li> <li>Horizontal Error (from NLL output) (km) expressed in kilometres - ERH</li> <li>Vertical Error (from NLL output) (km) expressed in kilometres - ERZ</li> <li>RMS (from NLL output) (s) expressed in seconds - RMS</li> <li>Number of Phases – NPHS</li> <li>Stations Azimuthal GAP (°) expressed in decimal degrees - GAP</li> <li>Quality factor - Qf</li> <li>Quality class - Qc</li> </ul> <p> </p> <p>De Luca G., M. Cattaneo, G. Monachesi and A, Amato (2009). Seismicity in the Umbria-Marche region from the integration of national and regional seismic networks. Tectonophysics, 476(1), 219-231. doi: 10.1016/j.tecto.2008.11.032.</p> <p>ISIDe Working Group. (2007). Italian Seismological Instrumental and Parametric Database (ISIDe). Istituto Nazionale di Geofisica e Vulcanologia (INGV); https://doi.org/10.13127/ISIDE.</p> <p>Lomax, A., J. Virieux, P. Volant, and C. Berge-Thierry (2000). Probabilistic earthquake location in 3D and layered models: introduction of a Metropolis–Gibbs method and comparison with linear locations. In: Advances in seismic event location, ed. C. H. Thurber and N. Rabinowitz, 101–134. Dordrecht and Boston: Kluwer Academic Publishers.</p> <p>Michele, M., Latorre, D., Emolo, A. (2019). An Empirical Formula to Classify the Quality of Earthquake Locations. Bulletin of the Seismological Society of America. Vol. 109, No. 6, pp. 2755–2761, December 2019, doi: 10.1785/0120190144.</p> <p>Scafidi, D., Viganò A., Ferretti G., and Spallarossa D. (2018). Robust picking and accurate location with RSNI-Picker2: real-time automatic monitoring of earthquakes and non-tectonic events, Seismol. Res. Lett, Vol. 89 (4), pp. 1478-1487, doi: 10.1785/0220170206.</p> <p>Scafidi D, Spallarossa D, Ferretti G, Barani S, Castello B, Margheriti L (2019). A complete automatic procedure to compile reliable seismic catalogs and travel-time and strong-motion parameters datasets. Seismol Res Lett 90(3):1308–1317.</p> <p>Scognamiglio, L., Tinti, E., Quintiliani, M. (2006). Time Domain Moment Tensor [Data set]. Istituto Nazionale di Geofisica e Vulcanologia (INGV). https://doi.org/10.13127/TDMT.</p> <p>Spallarossa, D., G. Ferretti, D. Scafidi, C. Turino, and M. Pasta (2014). Performance of the RSNI-Picker, Seismol. Res. Lett. 85, 1243–1254.</p> <p>Spallarossa D., Cattaneo M., Scafidi D., Michele M., Chiaraluce L., Segou M. and I. G. Main (2020). An automatically generated high-resolution earthquake catalogue for the 2016-2017 Central Italy seismic sequence, including P and S phase arrival times. Geophys. J. Int. doi: 10.1093/gji/ggaa604.</p>
16S rRNA sequences from Mediterranean Sparidae gut microbiome
<p><span>Animals have been developing key associations with micro-organisms through evolutionary processes and ecological diversification. Hence, in some host clades, phylogenetic distance between hosts is correlated to dissimilarity in microbiomes, a pattern called phylosymbiosis. Teleost fishes, despite being the most diverse and ancient group of vertebrate, have received little attention from the microbiome perspective and our understanding of its determinants is currently limited. In this study, we assessed the gut microbiome of 12 co-occurring species of teleost representing a large breadth of ecological diversity and originating from a single family (<i>i.e.</i> the Sparidae). We tested how host evolutionary history, diet composition and morphological traits are related to fish gut microbiome. Despite fish species having different microbiomes, there is no phylosymbiosis signal in this fish family, but gut length and diet had a strong influence on the microbiome. We revealed that the only species with a specialized herbivorous diet, <i>Sarpa salpa</i> had a 3.3 times longer gut than carnivorous species and such a long gut favor the presence of anaerobic bacteria typical of herbivorous gut microbiomes. Hence, dietary uniqueness is paired with both unique gut anatomy and unique microbiome.</span></p>
Raw sequencing metrics from two different prep methods for obtaining SARS-CoV2 genomes
<p>Sequencing_metrics_IlluminaDNAprep.xlsx contains metrics used for the determination of SARS-CoV2 genome assembly success using Illumina's DNA prep adapter-tagmentation method, coupled with the ARTIC protocol for gene-specific amplification of SARS-CoV2</p> <p>Sequencing_metrics_Seqwellprep.xlsx contains metrics used for the determination of SARS-CoV2 genome assembly success using Seqwell's Plexwell384 adapter-tagmentation method, coupled with the ARTIC protocol for gene-specific amplification of SARS-CoV2</p>
AnnData files for "Human dermal fibroblast subpopulations are conserved across single-cell RNA sequencing studies"
<p>AnnData files for "Human dermal fibroblast subpopulations are conserved across single-cell RNA sequencing studies". </p> <p>Includes Joined dataset with all four datasets at once.</p>
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.