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FIGURE A5 in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE A5. Scatter plot displaying how beam shift, measured by the apparent growth (scale) of the shell in the final x-ray radiograph relative to the first x-ray radiograph, varies with (1) time of day the scan was performed, and (2) the overall scan time. We found that beam shift decreased throughout the day, likely due to the tube warming up as more scans are run. There was no correlation between overall scan time and the amount of beam shift.
FIGURE A1.2 in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE A1.2. The range of volume measurements for each exposure times when three scans were reconstructed using ten methods. The blue dot represents the simple surface determination used for all shells in this study. The error bars represent the data range for each exposure time.
FIGURE 4. A in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE 4. A video moving through slices of a pteropods shell scanned at 500 ms exposure time, with five xray radiographs averaged per view and an overall scan time of 75 minutes. There are streak artefacts perpendicular to the shell edge that are likely caused by beam hardening or shell movement during the scan. For video file, see https://palaeo-electronica.org/content/2020/ 2923-investigating-ct-scan-quality.
Рис. 5. Пятнистый оΛень неоΑнократно снят фотоΛовушками в бассейнах рек Обор и Àурмин. 15.10.2020. 14.49. Фото А. С. БатаΛова Fig. 5. Sika deer repeatedly photographed by camera traps in the basins of the rivers Obor and Durmin; 15.10.2020. 14:49. Photo by A. S. Batalova in New data on the distribution of sika deer Cervus nippon Temminck, 1838 in the Lower Amur Region
Рис. 5. Пятнистый оΛень неоΑнократно снят фотоΛовушками в бассейнах рек Обор и Àурмин. 15.10.2020. 14.49. Фото А. С. БатаΛова Fig. 5. Sika deer repeatedly photographed by camera traps in the basins of the rivers Obor and Durmin; 15.10.2020. 14:49. Photo by A. S. Batalova
Рис. 1. Δинамика чисΛенности меΛких мΛекопитающих в Цасучейском бору: 1 — суммарная чисΛенность (особей / 100 циΛинΑро-суток); Αоминирующие виΑы: 2 — забайкаΛьский хомячок, 3 — бурозубка тунΑряная, 4 — бурозубка крошечная, 5 — поΛёвка монгоΛьская, 6 — поΛёвка РаΑΑе, 7 — красная поΛёвка; A — остепнённый сосняк, B — первичная гарь, С — старая гарь, D — повторная гарь; стреΛка указывает время прохожΑения пожара. Ось X — гг., ось Y — чисΛенность Fig. 1. Population dynamics of small mammals in the Tsasucheysky Pine Forest: 1 — total abundance (individuals / 100 cylinder-days); dominant species: 2 — Cricetulus pseudogriseus, 3 — Sorex tundrensis, 4 — S. minutissimus, 5 — Alexandromys mongolicus, 6 — Lasiopodomys raddei, 7 — Myodes rutilus; A — steppe pine forest, B — primary burns site, С — old burns site; D — repeated burns site; the arrow indicates the time of the fire. The X-axis shows years; the Y-axis shows population density in Population dynamics of small mammals after spring fires in steppe pine forest
Рис. 1. Δинамика чисΛенности меΛких мΛекопитающих в Цасучейском бору: 1 — суммарная чисΛенность (особей / 100 циΛинΑро-суток); Αоминирующие виΑы: 2 — забайкаΛьский хомячок, 3 — бурозубка тунΑряная, 4 — бурозубка крошечная, 5 — поΛёвка монгоΛьская, 6 — поΛёвка РаΑΑе, 7 — красная поΛёвка; A — остепнённый сосняк, B — первичная гарь, С — старая гарь, D — повторная гарь; стреΛка указывает время прохожΑения пожара. Ось X — гг., ось Y — чисΛенность Fig. 1. Population dynamics of small mammals in the Tsasucheysky Pine Forest: 1 — total abundance (individuals / 100 cylinder-days); dominant species: 2 — Cricetulus pseudogriseus, 3 — Sorex tundrensis, 4 — S. minutissimus, 5 — Alexandromys mongolicus, 6 — Lasiopodomys raddei, 7 — Myodes rutilus; A — steppe pine forest, B — primary burns site, С — old burns site; D — repeated burns site; the arrow indicates the time of the fire. The X-axis shows years; the Y-axis shows population density
Fig. 5 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 5. Absolute counts of Eosinophils. The dotted horizontal lines represent reference ranges based on average values ± 2 × S.D. of values of foxes from groups A3, B and D at 0 wpi. Error bars (S.E.M).
Fig. 2 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 2. Arithmetic mean worm burden at necropsy per group. Foxes of groups A were inoculated once and necropsied at 9 wpi (A1), 13 wpi (A2) or 23 wpi (A3), while foxes of groups challenged once (B) or twice (D) and the control foxes of the first (C) and second challenge (E) were necropsied 23 wpi. Bar indicates mean with outlier excluded. Error bars = S.E.M.
Fig. 3 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 3. Arithmetic mean worm fecundity (expressed as final LPG/number female worms at necropsy) per group. Foxes of groups A were inoculated once and necropsied at 9 wpi (A1), 13 wpi (A2) or 23 wpi (A3), while foxes of groups challenged once (B) or twice (D) and the control foxes of the first (C) and second challenge (E) were necropsied 23 wpi. Bar indicates mean with outlier excluded. Error bars = S.E.M.
Fig. 1 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 1. Experimental design: inoculations with 100 third stage larvae (L3) of Angiostrongylus vasorum are indicated by triangles, challenge inoculations (also with 100 L3) by circles and the differing group termination times by squares.
Fig. 4 in Repeated inoculations with the lung and heartworm nematode Angiostrongylus vasorum result in increasing larval excretion and worm burden in the red fox (Vulpes vulpes)
Fig. 4. Arithmetic mean larval counts (first stage larvae per gram of feces) of foxes dogs experimentally inoculated at 0 wpi and challenged once (group B) or twice (group D) with 100 third stage larvae of Angiostrongylus vasorum from 6 to 22 wpi. Y-axis log10 transformed. Arrows indicate the challenge time points.
Рис. 5. Варианты преΑсказанной Αоменной структуры скавенΑжер-рецепторов гемоцитов моΛΛюсков Planorbarius corneus. Сокращения (зΑесь и ΑаΛее): SR — богатый цистеином Αомен скавенΑжер-рецептора, Filament — Αомен промежуточного фиΛамента, TSP1 — повторы тромбоспонΑина типа 1, KR — крингΛ-Αомен, LDLa — Αомен рецептора Λипопротеинов низкой пΛотности кΛасса А Fig. 5. Variants of the predicted domain structure of scavenger receptors from hemocytes of Planorbarius corneus molluscs. Abbreviations (here and in what follows): SR — scavenger receptor Cys-rich domain, Filament — intermediate filament protein, TSP1 — thrombospondin type 1 repeats, KR — kringle domain, LDLa — low-density lipoprotein receptor domain class A in Pathogen recognition molecules from hemocytes of Planorbarius corneus molluscs (Planorbidae, Pulmonata)
Рис. 5. Варианты преΑсказанной Αоменной структуры скавенΑжер-рецепторов гемоцитов моΛΛюсков Planorbarius corneus. Сокращения (зΑесь и ΑаΛее): SR — богатый цистеином Αомен скавенΑжер-рецептора, Filament — Αомен промежуточного фиΛамента, TSP1 — повторы тромбоспонΑина типа 1, KR — крингΛ-Αомен, LDLa — Αомен рецептора Λипопротеинов низкой пΛотности кΛасса А Fig. 5. Variants of the predicted domain structure of scavenger receptors from hemocytes of Planorbarius corneus molluscs. Abbreviations (here and in what follows): SR — scavenger receptor Cys-rich domain, Filament — intermediate filament protein, TSP1 — thrombospondin type 1 repeats, KR — kringle domain, LDLa — low-density lipoprotein receptor domain class A
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)
BRAIN Journal-A Repeated Signal Difference for Recognising Patterns-Figure 3. Binary input stimulus dataset
<p>If the input value is 1, then the neuron is likely to be part of the cohesive set and would update the weight and also the global and local counts each event. If the input value is 0, then the neuron is not likely to be part of the cohesive set. For this case, it would not update the weight value as it is 0. It does update the global count as that uses unit increments, but only updates the local count when an earlier trigger switch tells it to. Each update event is also counted, so that averaged totals can be produced. </p>
BRAIN Journal-A Repeated Signal Difference for Recognising Patterns-Figure 2. Schematic of the same neuron N1, shared between 2 different patterns P1 and P2.
<p>It can be assumed that only one pattern fires during each time unit, where Rule 1 of the Introduction states that if a neuron fires a stronger signal for a pattern, it sends feedback to ask it to fire again, the next time unit. If it fires a weaker signal, the request is not to fire next time. Stronger and weaker relates to a more variable type of on or off. As the mechanism is not final yet, there could be some flexibility with it. Rule 1 also states that if the neuron does not fire for the current pattern, it receives the switch command from the last pattern it did fire for. Note that the actual firing event can produce either zero or some input and so an earlier event can also force a weak feedback signal. Rule 2 states that this particular feedback is only the on/off switch command and does not affect the size of the output value. A schematic of the idea is illustrated in Figure 2, which relates to the same neuron shared between 2 pattern events, at times t1 and t2. The schematic is described further in section 0. </p>
Repeat-masked <i>Strix occidentalis caurina</i> nuclear genome version 1.0 and complete mitochondrial genome
<p><strong>StrOccCau_1.0_nuc_finalMito_RepeatMasked.fa.bz2</strong> : This file is homology-based and <em>de novo</em> model-based repeat-masking of the reference <em>Strix occidentalis caurina</em> genome StrOccCau_1.0_nuc.fa from Hanna et al., 2017a,b) with the mitochondrial genome from Hanna et al. (2017c).</p> <p><strong>StrOccCau_1.0_nuc_finalMito_RepeatMasked.bed.bgz</strong> : This is a file in Browser Extensible Data (BED) format that provides the genomic intervals of the N-regions in the above masked assembly. The N-regions include hard-masked low complexity and repeat regions as well as N-regions that were gaps in the original assembly. I compressed the file using the bgzip tool from HTSlib version 1.7 (Davies et al. 2018).</p> <p>See full details of the creation of these files in section 2.1 of the materials and methods at protocols.io (http://dx.doi.org/10.17504/protocols.io.rmrd456).</p> <p>If you use these data, please cite the following:</p> <p>Hanna ZR. 2018. Repeat-masked <em>Strix occidentalis caurina</em> nuclear genome version 1.0 and complete mitochondrial genome. Version 1.0.0. <em>Zenodo.</em></p> <p> </p> <p><strong>References</strong></p> <p>Davies R, Randall JC, McCarthy SA, Bonfield J, Pollard MO, Marshall J, et al. 2018. HTSlib. Version 1.7. [Accessed 2018 Mar 19]. Available from: https://github.com/samtools/htslib</p> <p>Hanna ZR, Henderson JB, Wall JD, Emerling CA, Fuchs J, Runckel C, et al. 2017a. Northern Spotted Owl (<em>Strix occidentalis caurina</em>) Genome: Divergence with the Barred Owl (<em>Strix varia</em>) and Characterization of Light-Associated Genes. Genome Biology and Evolution. 9: 2522–2545. DOI: 10.1093/gbe/evx158</p> <p>Hanna ZR, Henderson JB, Wall JD, Emerling CA, Fuchs J, Runckel C, et al. 2017b. Supplemental dataset for Northern Spotted Owl (<em>Strix occidentalis caurina</em>) genome assembly version 1.0. <em>Zenodo</em>. DOI: 10.5281/zenodo.822859</p> <p>Hanna ZR, Henderson JB, Sellas AB, Fuchs J, Bowie RCK, Dumbacher JP. 2017c. Complete mitochondrial genome sequences of the northern spotted owl (<em>Strix occidentalis caurina</em>) and the barred owl (<em>Strix varia</em>; Aves: Strigiformes: Strigidae) confirm the presence of a duplicated control region. <em>PeerJ</em>. 5: e3901. DOI: 10.7717/peerj.3901</p> <p> </p>
Supplementary files for the manuscript "Assembly of Long Error-Prone Reads Using Repeat Graphs"
<p>Supplementary files for the manuscript "Assembly of Long Error-Prone Reads Using Repeat Graphs"</p> <p> </p> <p>Contents<br> ---------</p> <p>* `human_assemblues` - Flye assemblies of the human ONT sequencing data + QUAST benchmarking<br> of Flye, Canu and MaSuRCA assemblies. Scripts for assembly graph analysis are also included.</p> <p>* `nctc_assemblis` - Flye assemblies of the NCTC 21 bacterial dataset.</p> <p>* `yeast_assemblies` - working directories Flye, Canu, Falcon, Hinge and Miniasm assemblies of <br> yeast PB and ONT datasets + final assemblies + quast report. Some large files <br> (such as read alignments) were deleted.</p> <p>* `worm_assemblies` - working directories Flye, Canu, Falcon, Hinge and Miniasm assemblies of <br> the c. elegans dataset + final assemblies + quast report. Some large files <br> (such as read alignments) were deleted. `tandem_misassemblies` directory contain<br> the detailed analysis of nine tandem misassemblies. We recommend "gepard" dot-plotter for visualization.</p> <p>* `metagenome_assemblies` - Flye and Canu assemblies of a PacBio mock metagenome dataset.<br> In addition to metagenome assemblies, each bacteria was reassembled separately to<br> estimate the rate of divergence between the target genomes and the available references.</p> <p>* `simulated_data` - two assemblies of the simulated data illustrating Figure 1 (from Appendix I),<br> as well as simulated unbridged repeats benchmark.</p> <p><br> Software versions and parameters<br> --------------------------------</p> <p>* Flye - 2.3.5 (commit 20afeda)<br> * Canu - 1.7.1 (commit dfa60b8)<br> * Falcon - 0.3.0 (FALCON-Integrate commit 7498ef9)<br> * HINGE - 0.5.0 (commit 79fdf66)<br> * Miniasm - 0.2-r168-dirty (commit 40ec280) / Minimap2 2.8-r711-dirty (commit 8fc5f8d)<br> * Quast - 5.0.0 (commit de6973bb)</p> <p>Flye and Canu were run with the default parameters. The config files / scripts for<br> Falcon, HINGE and Miniasm could be found in the 'asm_config' archive folder.</p> <p>The HUMAN (but not the HUMAN+) assembly was generated with the earlier <br> Flye version 2.3.2 (released on Feb 20 2018) to provide a fair comparison <br> with the Canu and MaSuRCA assemblies (which were not updated since the release of Flye 2.3.2).<br> We note that the HUMAN assembly using the latest Flye version 2.3.5 has <br> NGA50 = 7.3 Mb and improves over the Flye 2.3.2 assembly (NGA50 = 6.3Mb). <br> HUMAN+ was assembled using the latest Flye and Canu versions (as of September 2018).</p> <p>The code for unbridged repeat resolution is currently available <br> in a separate 'flye-trestle' branch (commit 6100d32)</p>
A high-frequency and high-resolution image time series of the Gornergletscher - Swiss Alps - derived from repeated UAV surveys
<p>This dataset is based on aerial photographs of the Gornergletscher glacial system (Switzerland) collected during ten intensive UAV surveys carried out approximately every two weeks throughout the summer 2017.</p> <p>The final products consist in a series of 10 cm resolution ortho-images, Digital Elevation Models of the glacier surface, and Matching Maps that can be used to quantify ice surface displacements.</p>
Human-specific tandem repeat expansion and differential gene expression during primate evolution
<p>THIS DATASET IS PART OF THE FOLLOWING STUDY:<br> <a href="https://www.pnas.org/content/early/2019/10/22/1912175116">https://www.pnas.org/content/early/2019/10/22/1912175116</a></p> <p> </p> <p>THE RAW SEQUENCING 10x GENOMICS READS CAN BE DOWNLOADED FROM SRA:<br> <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA593056">https://www.ncbi.nlm.nih.gov/bioproject/PRJNA593056</a></p> <p><br> ORIGINAL UPLOAD: 09/06/2019</p> <p>UPDATES: 10/28/2019; 01/27/2020</p> <p>DESCRIPTION: Contigs were assembled using Phased-SV (<a href="https://www.nature.com/articles/s41467-018-08148-z">Chaisson et al, Nature Communications 2019</a>) on six human haplotypes (i.e., H0 and H1 in NA19240, HG00514, and HG00733), and six nonhuman haplotypes (this study, H0 and H1 in Clint the chimpanzee, Kamilah the gorilla, and Susie the orangutan). The long read data (PacBio CLR) from NHPs were phased into haplotypes H0 and H1 using linked reads from 10X Genomics prior to assembly, whenever possible. If not possible (e.g., in the case of long runs of homozygosity regions), long reads from both haplotypes were used to generate a "squished assembly". Using human haplotype data, we identified 21,442 polymorphic STRs/VNTRs, followed by a targetted phasing of these regions in the three NHPs. All of the human and nonhuman primate contigs were padded by 2 kbp both upstream and downstream, followed by mapping against the human reference (GRCh38). We did the same for "squished assemblies" from a Yoruban individual, CHM13, and three NHPs as described in <a href="https://science.sciencemag.org/content/360/6393/eaar6343">Kronenberg et al, Science 2018</a>. The BAM and BAI files in this dataset contain the alignment of all these contigs against GRCh38.</p>
Fig. 1. Repeat family selection for the P. decorus diagnostic assay. A in A novel quantitative real-time PCR diagnostic assay for fecal and nasal swab detection of an otariid lungworm, Parafilaroides decorus
Fig. 1. Repeat family selection for the P. decorus diagnostic assay. A. Number of sequencing reads for P. decorus compared to outgroup species reads for each repeat family (1–104) on a log scale. Arrows indicate repeat families with no reads from the outgroup species. Plot was made using Tableau Software, 2019. B. Within a cluster, reads with similar sequences are closer together. Edges connect a read with its closest match (creating a pair) and the length of this edge represents the amount of overlap between the reads. The mean edge width provides context for the lengths in the cluster, so in a cluster with a larger mean edge width the edges are actually longer than edges in a cluster with a smaller mean edge width. Reads therefore may be distant because of sequence divergence, or in the case of a long repeat (more than 150 base pairs), because of a lack of overlap between reads. However, because there will likely be continuous reads covering different regions of the repeat, these longer repeats should still appear as a tight, though possibly larger, cluster. Read dots that stray from the central cluster most likely represent sequence divergence. Higher density therefore indicates lower sequence divergence.
Fig. 2 in Heterochromatin distribution and chromosomal mapping of microsatellite repeats in the genome of Frieseomelitta stingless bees (Hymenoptera: Apidae: Meliponini)
Fig. 2. Metaphase spreads of females of Frieseomelitta varia (a, g), Frieseomelitta sp. n. (b, h), Frieseomelitta meadewaldoi (c, i), Frieseomelitta dispar (d, j), Frieseomelitta francoi (e, k), and Frieseomelitta doederleini (f, l) afer basespecific fluorochrome staining. The arrows indicate the GC-rich regions.
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.