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15,022 results for “differentiation”
Figure 7 in Distribution and molecular differentiation of Culex pipiens complex species in the Middle and Eastern Black Sea Regions of Turkey
Figure 7. Phylogenetic tree based on a 151-bp region within the CQ11 microsatellite region of Culex pipiens. The tree was constructed using the maximum likelihood method, and bootstrap values are shown as numbers on the tree.
Figure 5. Unrooted haplotype network. Each circle represents a in Distribution and molecular differentiation of Culex pipiens complex species in the Middle and Eastern Black Sea Regions of Turkey
Figure 5. Unrooted haplotype network. Each circle represents a haplotype, and the lines above each link indicate one mutation. Small black dots indicate intermediate, missing, or unsampled haplotypes.
Figure 4 in Distribution and molecular differentiation of Culex pipiens complex species in the Middle and Eastern Black Sea Regions of Turkey
Figure 4. The phylogenetic tree is based on a 651-bp region of the Ace-2 gene from Culex pipiens. The tree was constructed using the maximum likelihood method, and bootstrap values are shown as numbers on the tree.
Differential impact of impaired steryl ester biosynthesis on the metabolome of tomato seeds and fruits
<p>Steryl esters (SE) are a storage pool of sterols that accumulates in cytoplasmic lipid droplets and helps to maintaining plasma membrane sterol homeostasis throughout plant growth and development. Ester formation of plant SE is catalyzed by phospholipid:sterol acyltransferase (PSAT) and acyl-CoA:sterol acyltransferase (ASAT), which transfer long-chain fatty acid groups to free sterols from phospholipids and acyl-CoA, respectively. Comparative mass spectrometry-based metabolomic analysis between ripe fruits and seeds of a tomato (Solanum lycopersicum cv Micro-Tom) mutant lacking functional PSAT and ASAT enzymes (slasat1xslpsat1) shows that disruption of SE biosynthesis has a differential impact on the metabolome of these organs, including changes in the relative proportions of free and glycosylated sterols. Significant perturbations were observed in the fruit lipidome in contrast to the mild effect detected in the lipidome of seeds. A contrasting response was also observed in phenylpropanoid metabolism, which is down-regulated in fruits and appears to be stimulated in seeds. Comparison of global metabolic changes using volcano plot analysis suggests that disruption of SE biosynthesis favors a general state of metabolic activation that is more evident in seeds than fruits. Interestingly, there is an induction of autophagy in both tissues, which may contribute along with other metabolic changes to the phenotypes of early seed germination and enhanced fruit resistance to Botrytis cinerea displayed by the slasat1xslpsat1 mutant. The results of this study reveal unreported connections between SE metabolism and the metabolic status of plant cells, and lay the basis for further studies aimed at elucidating the mechanisms underlying the observed effects.</p> <p> </p> <p>Data: </p> <p>W1-54; AxP LC polar.zip: raw files LC-polar</p> <p>W1-1 (1)-(54); AxP LC lipid.zip: raw files lipid LC</p> <p>GCtomato.zip: raw files GC polar</p> <p>spreadsheet (.csv) with sample IDs</p>
Figure 2 in Examining metrics and magnitudes of molecular genetic differentiation used to delimit cetacean subspecies based on mitochondrial DNA control region sequences
Figure 2. Relationship between ΦST and Nei's estimate of net divergence (dA) among cetacean population, subspecies, and species pairs estimated using mitochondrial DNA control region sequence data. Specific values mentioned in the text are numbered: 1 = Neophocaena species; 2 = killer whale populations. The three green squares in the left-hand side of the figure (ΦST <0.07) represent, from bottom to top, the subspecies comparisons for S. attenuata, S. longirostris, and L. obscurus, respectively.
Figure 1 in Examining metrics and magnitudes of molecular genetic differentiation used to delimit cetacean subspecies based on mitochondrial DNA control region sequences
Figure 1. Box and whisker plots showing median and 1st and 3rd quartiles, and minimum and maximum values for six metrics of genetic divergence among cetacean population, subspecies, and species pairs estimated using mitochondrial DNA control region sequence data.
Machine Proofs for Adams Differentials and Extension Problems among CW Spectra
<p>Update notes: In this version, we reduce the number of spectra in this project from 210 to 49 (compared to the cw210 version), while keeping the outcome sufficient to prove <a href="https://arxiv.org/abs/2412.10879">the Last Kervaire Invariant Problem</a>. The size of the proof file <a href="https://zenodo.org/api/records/14875532/draft/files/proofs.db.rar/content" target="_blank" rel="noopener noreferrer">proofs.db.rar</a> is also reduced from 600MB to 44MB, leading to easier track for proofs.</p> <p>In this Zenodo repository we upload the computations of Adams differentials and extensions among many CW spectra and their proofs. This data will be used in the <a href="https://arxiv.org/abs/2412.10879">proof of the Last Kervaire Invariant Problem</a> by Weinan Lin, Guozhen Wang and Zhouli Xu.</p> <p>In <strong>programs.rar</strong>, we have two programs ./Adams and ./ss provided for both windows users and mac users and a definition file <strong>Adams.json</strong> for spectra involved in this project. The source code for the two programs is contained in <strong>source code.zip</strong>. You can also find the source code on Github <a href="https://github.com/WayneLin92/SSeqCpp">https://github.com/WayneLin92/SSeqCpp</a> together with user manual for the programs.</p> <p>In <strong>programs.rar</strong> there is also a demo for ./ss which is a category of five spectra: S0, C2, Ceta, Cnu, Csigma.</p> <p><strong>kervaire_database.rar</strong> contains all the Adams spectral sequence data and extension data. They are sqlite3 database files and can be read directly by the ./ss program. We also provide the same data in csv format in <strong>kervaire_csv.rar</strong>.</p> <p>The two zip files<strong> proofs.db.rar</strong> and <strong>proofs_csv.rar</strong> are proofs of all the differentials. Inside <strong>proofs_csv.rar</strong> there are 3 csv files. We break it to 3 csv files because Microsoft Excel has a limit of 1,000,000 rows.</p> <p>On the website <a href="https://waynelin92.github.io/ss/kervaire-49.html">https://waynelin92.github.io/ss/kervaire-49.html</a> you can find plots of the data. The website source code (html/javascript) is actually contained in <strong>programs.rar</strong>/webpages in this repository.</p> <p>Please read <strong>instructions.pdf</strong> for more infomation.</p>
Cast Away in the Adriatic: Low Degree of Parallel Genetic Differentiation in Three-Spined Sticklebacks
<p>This repository incorporates data and scripts associated with the paper "Cast Away in the Adriatic: Low Degree of Parallel Genetic Divergence in Three-Spined Sticklebacks".</p> <p>Included in the repository are the following compressed folders: </p> <ul> <li>Moments_models&data.zip: two-population demographic models and SFS to run in <em>moments.</em></li> <li>Stairwayplot.zip: blueprint files for multiple mutation rates and results for StairwayPlots.</li> <li>TreeMix.zip: pipeline to infer population splits and mixture events from allele frequency data using TreeMix, including input files.</li> <li>VCF.zip: a filtered VCF file for all three-spined stickleback samples.</li> </ul> <p>The scripts for TreeMix and demographic analyses in <em>moments</em> are also available on <a href="https://github.com/carolindahms">GitHub</a>.</p>
Fig. 6 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 6. The results of AMOVA computed on the genetic data and hierarchical ANOVA of the morphometric data. A = AMOVA of both regions together. B = AMOVA of the two regions separately. C = Hierarchical ANOVA of both regions together. D = Hierarchical ANOVA of the two regions separately. The patterns of the columns are consistent in all charts. BR: between region component of variance (dark grey); BP: variation among the populations within the regions (black); BS: variation among the samples/generations within the populations (white); WS: within sample compo-
Fig. 4 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 4. UPGMA dendrogram constructed using CAVALLI-SFORSA & EDWARDS chord distances with a Maculinea teleius sample (3tKv) as out group. Bootstrap values were obtained using 2000 replicates
Fig. 2 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 2. Measured traits on the wings of Maculinea nausithous. Forewing: anal length (a), length of the outer margin (b), apical angle (β). Hindwing: anal length (c), costal length (d), basal angle (γ), widths
Fig. 3 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 3. UPGMA dendrogram constructed using CAVALLI-SFORSA & EDWARDS chord distances (A) and UPGMA phenogram built on the basis of the Euclidean distances among the average canonical
Fig. 1 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 1. Sample sites. Őrség region (West Hungary): Kétvölgy (Kv) and Magyarszombatfa (Mfa). Transylvania (Romania): Răscruci (Ras) and Fânatele Clujului (Fan)
Fig. 7 in Pattern Of Genetic And Morphometric Differentiation In Maculinea Nausithous (Lepidoptera: Lycaenidae) In The Carpathian Basin
Fig. 7. Results of the classification of individuals. A: Bar plot of the individuals as a result of the Bayesian clustering analysis. B: Distribution of the two genetic clusters in the two regions. 1: genetic cluster 1; 2: genetic cluster 2. C: Allocation of the individuals at the regional level on the basis of their
Dataset: Measuring stimulus-evoked neurophysiological differentiation in distinct populations of neurons in mouse visual cortex
<p>This dataset contains the calcium imaging and behavioral data analyzed in our paper, "Measuring stimulus-evoked neurophysiological differentiation in distinct populations of neurons in mouse visual cortex".</p> <p>These data were obtained at the Allen Brain Observatory as part of the <em>OpenScope</em> project, which is operated by the Allen Institute.</p> <p>Analysis code is available at <a href="https://github.com/wmayner/openscope-differentiation">https://github.com/wmayner/openscope-differentiation</a>.</p>
Predictors of genomic differentiation within a hybrid taxon
<p>Hybridization is increasingly recognized as an important evolutionary force. Novel genetic methods now enable us to address how the genomes of parental species are combined in hybrid lineages. However, we still do not know the relative importance of admixed proportions, genome architecture and local selection in shaping hybrid genomes. Here, we take advantage of the genetically divergent island populations of Italian sparrow on Crete, Corsica and Sicily to investigate the predictors of genomic variation within a hybrid taxon. We test if differentiation is affected by recombination rate, selection, or variation in ancestry proportions. We find that the relationship between recombination rate and differentiation is less pronounced within hybrid lineages than between the parent species, as expected if purging of minor parent ancestry in low recombination regions reduces the variation available for differentiation. In addition, we find that differentiation between islands is correlated with differences in signatures of selection in two out of three comparisons. Signatures of selection within islands are correlated across all islands, suggesting that shared selection may mould genomic differentiation. The best predictor of strong differentiation within islands is the degree of differentiation from house sparrow, and hence loci with Spanish sparrow ancestry may vary more freely. Jointly, this suggests that constraints and selection interact in shaping the genomic landscape of differentiation in this hybrid species.</p>
Age, sex, length (mm), weight (g), and plasma sex steroid concentrations (ng/ml) of greater amberjack Seriola dumerili reared in sea cages during the process of sex differentiation
<p>The dataset contains an excel file with the age, sex, total length (mm), wet weight (g) and plasma concentrations (ng/ml) of the following sex steroids, measured with the use of liquid chromatography/tandem mass spectrometry (LC-MS/MS): adrenosterone (Ad), androstenedione (Δ4), 11-ketotestosterone (11ΚΤ), testosterone (Τ), estradiol (Ε2), progesterone (P4) and 17,20β-dihydroxy-4-pregnen-3-one (17,20βP).</p>
Differential effects of early or late exposure to prenatal maternal immune activation on mouse embryonic neurodevelopment
<p>Exposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental and psychiatric disorders. MIA-induced deficits in adolescent and adult offspring have been well characterized, however, less is known about the effects of MIA-exposure on embryo development. To address this gap, we collected high-resolution ex vivo magnetic resonance imaging (MRI) of C57BL/6 mouse embryos (gestational day [GD]18) who were prenatally exposed to MIA either early (GD9) or late (GD17) in gestation. We further examined hippocampal neuroanatomy using electron microscopy and identified differential effects due to MIA-timing. </p> <p>The data published here was collected and analyzed for the following publication available as a preprint on BioRxiv (https://www.biorxiv.org/content/10.1101/2021.07.14.452084v2). Briefly, We identify striking neuroanatomical changes in the embryo brain, particularly in the late exposed offspring. An increase in apoptotic cell density was observed in the GD9 exposed offspring, while an increase in the density of dark neurons and glia, putative markers for increased neuroinflammation and oxidative stress, was observed in GD17 exposed offspring, particularly in females. Overall, our findings integrate imaging techniques across different scales to identify differential impact of MIA-timing on the earliest stages of neurodevelopment.</p> <p>In this dataset, you will find a total of <strong>187 preprocessed structural MRIs </strong>(in MINC format) of whole embryos at gestational day 18. These embryos were exposed to poly I:C or vehicle control (0.9% sterile saline) at GD9 or 17. A multi-channel 7.0-T MRI scanner with a 40 cm diameter bore (Varian Inc., Palo Alto, CA), with a custom-built 16-coil solenoid array was used to acquire T2-weighted, gadolinium enhanced structural images at 40 μm3 resolution images from 16 samples concurrently (3D fast spin echo sequence using a cylindrical k-space acquisition; TR/TE=350/12 ms, echo train length=6, two averages, field-of-view 20 mm x 20 mm x 25 mm, matrix size=504 x 504 x 630).</p> <p>An N4 correction for B1 bias field inhomogeneities and denoising using non-local means (minc_anlm) was applied to the T2-weighted images, and the background was set to zero using minc tools. The demographics information for each animal is included in the <strong>demographics.csv</strong> file. </p> <p>The dorsal hippocampus was selected as a region of interest in which the total number and density of total cells, dark neurons, dark glia, apoptotic cells were assessed (as presented in our manuscript). This is available in the <strong>EM_raw_data_per_slice.csv</strong> and <strong>EM_average_per_mouse.csv </strong>files. </p> <p>Included in this data set are the <strong>structural MRIs in MINC format</strong>, corresponding demographics information (<strong>demographics.csv</strong>), electron microscopy data from the dorsal hippocampus (<strong>EM_raw_data_per_slice.csv</strong> and <strong>EM_average_per_mouse.csv)</strong> data, and a <strong>readme.txt</strong> file providing further detail on the data structure and content, and on how to interpret the data column titles.The raw (not-preprocessed) MINC files, as well as MINC files cropped to the head of the embryos available upon request to the authors. </p> <p>Finally, the authors would like to acknowledge the funding bodies that supported the completion of this work including the Canadian Institute for Health Research, the Fonds de Recherche du Québec en Santé, and the Healthy Brains for Healthy Lives at McGill University.</p>
Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in Sorghum bicolor
<p>Supplementery materials of journal article "Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in <em>Sorghum bicolor</em>"</p>
A Parameterized Model for Differential Galaxy Counts at Any Wavelength
<p>Collected literature values of Schechter functions, resulting parameter values of fits to those data as a function of wavelength, and Python scripts to compute simulated differential galaxy counts based on those parameterisations.</p> <p> </p> <p>Future revisions of galaxy_counts.py can be found at https://github.com/Onoddil/macauff/blob/main/macauff/ galaxy counts.py, and future revisions of literature and parameterisations can be found at https://onoddil.github.io/galaxy evolution/galaxy counts.html.</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.