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13,587 results for “specification”
Notified bodies, horizontal specifications and harmonised standards for construction materials third party assessment according to the CPR - EU 305/2011
<p>This dataset was extracted from NANDO, the website of the European Commission for notified bodies. It contains the list of notified bodies, horizontal specifications and harmonised standards for construction materials third party assessment according to the CPR - EU 305/2011</p>
Data for Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery
<p><strong>Description of the datasets</strong></p> <p>Data are organized as folders and compressed with tar.gz.</p> <p>There are two compressed data folder: <strong>data </strong>which used for cattle genome graphs experiment and <strong>data_human</strong> which we used for human genome graphs experiment. </p> <p><strong>Cattle genome graphs experiments</strong></p> <p>First you need to unzip the file using command <em>tar -xvzf data.tar.gz</em>. After unzipping, the data folder is organized as follows:</p> <ul> <li>Utilities: contain bovine ARS-UCD 1.2 fasta reference with the accompanying index.</li> <li>Bin: contain the softwares used in the paper (vg, liftover, vcf2diploid)</li> <li>Part1: data for analysis in variant prioritization section, further subdivided into: <ul> <li>vcf_sim: variant files from four animal in each breed used to simulate reads</li> <li>reads_sim: simulated short reads used for read mapping</li> <li>vcf_freq: variants augmented to graphs filtered based on allele frequency</li> </ul> </li> <li>Part2: data used for analysis in the section of graph mapping with breeds-filtered variants, further subdivided into: <ul> <li>vcf_breed: variant files used to graphs construction.</li> </ul> </li> <li>Part3: data used for analysis in the section of consensus genome, further subdivided into: <ul> <li>read_sims: simulated reads as in the part1, but the coordinates are liftovered to the new consensus genomes.</li> <li>reference: contain the original reference and consensus references.</li> <li>vcf_consensus: contain major allele variants to construct consensus genomes.</li> </ul> </li> <li>Part4: data analysis in the section of whole genome graph construction and variant genotyping. <ul> <li>vcf_construct: variants from chromosome 1-29 from 82 Brown Swiss used to construct BSW whole genome graph.</li> <li>BSW_graph: whole genome Brown Swiss graph with the three accompanying indexes (xg,gcsa, and gbwt).</li> </ul> </li> </ul> <p><strong>Human genome graphs experiments</strong></p> <p>First you need to unzip the <em>data_human</em> file using command <em>tar -xvzf data</em><em>_hum.tar.gz</em>. After unzipping, the data folder is organized as follows:</p> <ul> <li>reference: the g1k_v37 reference used as a graph backbone</li> <li>vcf_sim: variant files from four individuals in each population used to simulate reads</li> <li>reads_sim: simulated short reads used for read mapping</li> <li>vcf_freq: variants augmented to graphs filtered based on allele frequency</li> </ul>
Fig. 4 in Silk Spinning Behavior Varies from Species-Specific to Individualistic in Embioptera: Do Environmental Correlates Account for this Diversity?
Fig. 4. Computation of similarity between two sequences. For two individuals of Aposthonia borneensis (Hagen) (Oligotomidae), the first 500 steps of their spin sequences are shown (A and B).The red bar underlining a short sequence indicates one 15-step subsequence that is highly similar between these two individuals. For all possible pairs of 15 step subsequences, the heatmap displays the sequence similarity (C), with red areas indicating regions of the spin sequence that are highly similar.The profiles on the margins of the heat map indicate the marginal maxima—that is, for each 15-step subsequence, what is the similarity to the most similar subsequence in the other individual. Portions of the sequence with similarities about 12 were deemed sufficiently similar to the other sequence (vertical or horizontal lines), amounting to about 5% of individual 1's sequence and 10% of individual 2's sequence.
Fig. 3 in Silk Spinning Behavior Varies from Species-Specific to Individualistic in Embioptera: Do Environmental Correlates Account for this Diversity?
Fig. 3. Kinematic diagrams displaying relative proportion of spin-steps in each position as relative size of the circles. Saturated black color of the body represents dorsal spinning; dark gray represents kinematics when the embiopteran faces the framework silk and spins with her ventral surface facing the camera and the emerging silk structure. Spinning was recorded during hour-long filming sessions in the laboratory in an apparatus as shown in Supp Fig. 1 [online only]. (A) Notoligotoma hardyi average spin dynamics, (B) Haploembia tarsalis average spin dynamics, (C) Diagram shows the positions of the different possible spinsteps whereby the words are placed in the position of the front foot as the embiopteran steps around her body to release silk with each foot fall.The same steps are taken on the left as well during spinning. See Supp Video 2 [online only] for examples of spinning behavior exhibited by individual females.
Fig. 5 in Silk Spinning Behavior Varies from Species-Specific to Individualistic in Embioptera: Do Environmental Correlates Account for this Diversity?
Fig. 5. Phylogenetic relationships and sequence similarities (n = 15) for all individuals in this study. (A) Sequence similarities are depicted as a heat map, with the diagonal representing self-similarities.The small outlined boxes along the diagonal indicate all intraspecific comparisons, and the mean intraspecific similarity for each species is depicted above the heat map. For comparison, the inset graph, (B) shows the similarity among pairs of species for a trait that is evolving according to the Ornstein-Uhlenbeck model.The large clade constituting the top 19 species shows high similarity among species (mostly dark colors in the upper left), but low similarity to the two outgroups to this clade (bottom six species, shows as lighter gray colors).The phylogenetic tree is based on Miller et al. 2012.
Fig. 7 in Silk Spinning Behavior Varies from Species-Specific to Individualistic in Embioptera: Do Environmental Correlates Account for this Diversity?
Fig. 7. Predictors of intraspecific similarity scores. The three panels show the partial residual plots for the three variables selected in the final model for a subsequence length of 15. Intraspecific similarity as a function of: (A) mean annual temperature, (B) temperature seasonality, and (C) silk gallery structure. Two-letter codes indicate the species as in Fig. 6.
BIDS wildtype data selection from "Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories"
<p>Data package selecting wildtype animals from the “Dysfunctional Autism Risk Genes Cause Circuit-Specific Connectivity Deficits With Distinct Developmental Trajectories” article, formatted corresponding to the Brain Imaging Data Structure. The relevant publication can be found via DOI <a href="https://doi.org/10.1093/cercor/bhy046">10.1093/cercor/bhy046</a> .</p>
Computational Studies of Substrate Transport and Specificity in a Phospholipid Flippase
<p>MD trajectories of all-atom and CG simulations of PI4P activated E2P state of the Drs2p-Cdc50p complex.</p>
SMART2: Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys
<p>To increase the evidence base supporting specific methods to measure social interaction, we compared data from self-reported contact surveys and wearable proximity sensors from a cohort of schoolchildren in the Pittsburgh metropolitan area.</p> <p> </p> <p>Enrollment in the Social Mixing and Respiratory Transmission (SMART) study operated on an opt-out basis, and all students registered in a participating school before the start of the study were eligible to participate. Students in kindergarten (typically aged 5 years) to 12<sup>th</sup> grade (typically aged 18 years) from two elementary (K to 4<sup>th</sup> grade, K to 5<sup>th</sup> grade), two middle (5<sup>th</sup> to 6<sup>th</sup> grade, 7<sup>th</sup> to 8<sup>th</sup> grade), two elementary-middle (K to 8<sup>th</sup> grade), and two high (both 9<sup>th</sup> to 12<sup>th</sup> grade) schools were eligible to participate in SMART. Participation rates were high in all schools (82 to 99%). Each school provided aggregate demographic information about the school population, and individual grade and sex of participating students.</p> <p><em>Proximity sensor deployments</em></p> <p>The details of proximity sensor deployments have been described in detail elsewhere (60). In brief, participating students were given proximity sensors in plastic pouches and instructed to wear the pouch around their neck for the duration of the school day without removing or otherwise tampering with the sensor. In six of the eight schools, all participating students were given a sensor; in two schools, the large student population limited the deployment to randomly selected classrooms in each grade. Deployments typically lasted from the first class period (08:00 – 09:00) to the last class period (14:00 – 15:00). Deployment days in each school were chosen to be representative of a typical school day, without any special schoolwide or grade-specific activities that could modify normal contact patterns.</p> <p> </p> <p>We used TelosB wireless sensors (61) programmed in the NesC language to send beacons every 20 seconds (beacon frequency 3 per minute). The receiving sensor recorded the contacting sensor’s identity, an internal time stamp, and a radio strength signal indicator (RSSI). Signal strength provided an estimate of physical proximity, but was highly dependent on the orientation of the two sensors and any obstructions between them and therefore could not be used to define an exact distance between contacts. Based on pilot studies and previous work on effective distances of respiratory virus transmission (29, 62), we chose a signal threshold (-80 dBm) that should correspond to contacts of relevance to respiratory disease transmission.</p> <p> </p> <p>The number of unique proximity sensor contacts recorded for a participant was defined as the total number of other participants with whom their proximity sensor recorded at least one interaction during each deployment. To explore patterns of contacts of varying length, we considered several values of the contact threshold, or the minimum number of recorded interactions between two proximity sensors required to be considered a unique contact. The number of interactions between any given pair of sensors was taken to be the maximum number of interactions recorded by either sensor, to account for battery failure, measurement error, or other malfunctions.</p> <p> </p> <p><em>Contact survey design</em></p> <p>Contact surveys were completed by participants in school under the supervision of project staff and teachers. Each sheet of the paper version allowed for information on up to 30 contacts to be recorded; additional sheets could be requested. Two versions were designed: one for middle- and high-school students, and a simplified version for elementary school students (although some elementary school children completed the middle- and high-school version, upon consultation with school administrators and teachers). Classrooms were randomly selected to participate from each grade, and students of several classrooms completed more than one contact survey over the course of the study period.</p> <p> </p> <p>Participants were asked to report information about any individual they talked with, played with, or touched the previous day, including the contact’s age and sex, whether they attended the same school as the participant, the context in which the contact was made, whether the contact involved direct or indirect (through a shared object) touch, and approximate duration of the contact. Students reported the total number of contacts made in the previous day, without detailed information, and additional demographic information about themselves and their household. The surveys were completed either on paper or by computer, depending on resources available in each school.</p> <p> </p> <p>We defined total survey contacts as the total number of individuals a student reported having interacted with on the day before the survey was completed. Detailed contacts were the subset of total contacts for which the student reported contact age, sex, duration, and context. We considered further subsets of detailed survey contacts, including those occurring within school, those reported to have lasted more than 10 minutes over the course of the day, and those occurring on the same day as a sensor deployment.</p> <p> </p>
Data 1 for "Population- and age-specific patterns of haemosporidian assemblages and infection levels in European Bee-eaters (Merops apiaster)"
<p>Data related to the article "Population- and age-specific patterns of haemosporidian assemblages and infection levels in European Bee-eaters (<em>Merops apiaster</em>)" in the format .xlsx. The 1st sheet contains all variables for analyses done with the R script (see 10.5281/zenodo.3968360). The 2nd sheet contains explanations about the variables in sheet 1.</p>
"Mapping specific mental content during musical imagery" - Musical stimuli
<p>Six instrumental melodies composed by Joe Hisaishi, used as stimuli in the paper "<strong>Mapping the contents of consciousness during musical imagery"</strong></p>
The genome of the Xingu Scale-backed Antbird (Willisornis vidua nigrigula) reveals lineage-specific adaptations
<p>Antbirds (Thamnophilidae) are a large neotropical family of passerine bird renowned for the ant-following foraging strategies of several members of this clade. The high diversity of antbirds provides ample opportunity for speciation studies, however these studies can be hindered by the lack of an annotated antbird reference genome. In this study, we produced a high-quality annotated reference genome for the Xingu Scale-backed Antbird (<em>Willisornis vidua nigrigula</em>) using 10X Genomics Chromium linked-reads technology. The assembly is 1.09 Gb, with a scaffold N50 of 12.1 Mb and 17,475 annotated protein coding genes. We compare the proteome of <em>W. v. nigrigula</em> to several other passerines, and produce annotations for two additional antbird genomes in order to identify genes under lineage-specific positive selection and gene families with evidence for significant expansions in antbirds. Several of these genes have functions potentially related to the lineage-specific traits of antbirds, including adaptations for thermoregulation in a humid tropical environment.</p>
Example data set for 2D adaptive slice-specific z-shimming
<p>Input data and corresponding results for the scripts provided on github (https://github.com/neuroimaging-mug/R2s-mapping) for adpative slice-specific z-shimming in presence of macroscopic field variations.</p> <p>Please unzip all file in the repository path of ‘R2s-mapping’.</p>
Genome-wide association summary statistics for sex- and age-specific analysis of chronic back pain
<p>The dataset comprises summary-level statistics for age- and sex-specific genome-wide association study of chronic back pain (cBP) in individuals of European descent from UK Biobank (<a href="https://www.ukbiobank.ac.uk/">https://www.ukbiobank.ac.uk/</a>). The study was carried out under UK Biobank approved project #18219. </p> <p><strong>The dataset accompanies the paper (please cite if using the dataset):</strong></p> <p><a href="https://pubmed.ncbi.nlm.nih.gov/33021770/">Freidin, Maxim B.; Tsepilov, Yakov A.; Stanaway, Ian B.; Meng, Weihua; Hayward, Caroline; Smith, Blair H.; Khoury, Samar; Parisien, Marc; Bortsov, Andrey; Diatchenko, Luda; Børte, Sigrid; Winsvold, Bendik S.; Brumpton, Ben M.; Zwart, John-Anker; HUNT All-In Pain; Aulchenko, Yurii S.; Suri, Pradeep; Williams, Frances M.K. Sex- and age-specific genetic analysis of chronic back pain. Pain. 2020. doi:10.1097/j.pain.0000000000002100.</a></p> <p>The phenotype of cBP was defined as back pain for 3+ months. Linear mixed-effects additive model was fitted adjusting for age, genotyping array type, and 10 genetic PCs provided by UK Biobank. The following filters were applied: minor allele frequency >0.001, genotyping and individual call rates >0.98%, imputation quality score (INFO) >0.7. GWAS were carried out in males and females separately in the whole sample (<strong>allages</strong>) as well as in groups of younger than 65 years (<strong>under65</strong>) and 65+ years old (<strong>65plus</strong>) as detailed in the paper. Accordingly, 6 files are deposited here, corresponding to each group. </p> <p><strong>Column headers:</strong></p> <p>SNP, SNP rsID </p> <p>CHR, chromosome</p> <p>BP, genomic position (GRCh37 build)</p> <p>EA, effect allele (coded as "1")</p> <p>OTHER, other allele (coded as "0")</p> <p>A1FREQ, frequency of effect allele</p> <p>INFO, imputation quality</p> <p>BETA, effect size (for effect allele)</p> <p>SE, standard error of effect size</p> <p>PVAL, p-value for association</p>
High-quality large curated dataset of protein sequences (1.83 million) and their corresponding Position Specific Scoring Matrices
<p>As part of his master thesis at the Rostlab, which is located at the Technical University of Munich (TUM), Mr. Issar Arab developed the first language model that encodes evolutionary information of proteins explicitly. The pre-training involved the creation of a novel high-quality dataset of protein sequences (around 1.83 million proteins, or ~0.8 Billion amino acids) with their corresponding Position Specific Scoring Matrices (PSSMs). Those matrices reflect the relative frequency of each amino acid at each position in a protein and is derived from evolutionarily related proteins.</p> <p>Mr. Arab makes this work publicly available to help other researchers speed up their work to leverage AI to learn the representation of protein evolutionary information more explicitly. The set of sequences was derived by extracting all PSSMs from the <a href="https://predictprotein.org/">PredictProtein</a> (PP) cache, which were also part o the UniProt Reference Cluster with 50% sequence identity (uniref50 2019_12). The overlap between PP and uniref50 was further filtered to only include high-quality samples, e.g. only multiple sequence alignments with a certain number of aligned sequences were considered. The processing led to a training set of 1.83 Million sequences, a validation set of 879 instances, and a test set of 879 entries. The training data of proteins is reduced to 40% sequence identity, with respect to the validation/test sets, and contains sequences ranging between 18 and 9858 residues in length.</p> <p>Refer to the Jupyter notebook for a detailed description of the files' structure and a Python code snippet to correctly manipulate this data.</p> <p>To access the full original work, please visit the following link: <a href="https://mediatum.ub.tum.de/node?id=1579236">Manuscript</a> <br><br><strong>Note:</strong> The dataset was recently used to fine tune a protein sequence language model (<a href="https://github.com/issararab/PEvoLM">PEvoLM</a>). The work was presented at the CIBCB'23 conference. If you use PEvoLM or this dataset in your work, please cite the following publication:</p> <p>- Issar Arab, <strong>PEvoLM: Protein Sequence Evolutionary Information Language Model</strong>, <em>IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Eindhoven, Netherlands</em>, (2023), pp. 1-8, doi:<a href="https://ieeexplore.ieee.org/document/10264890">10.1109/CIBCB56990.2023.10264890</a></p>
Gestational Cd exposure in the CD-1 mouse induces sex-specific hepatic insulin insensitivity, obesity and metabolic syndrome in adult female offspring
<p>There is compelling evidence that developmental exposure to some toxic metals increases risk for obesity and obesity-related morbidity including cardiovascular disease and type 2 diabetes in adults. To explore the hypothesis that developmental Cd exposure increased risk of obesity later in life, male and female CD-1 mice were maternally exposed to 500 ppb CdCl<sub>2</sub> in drinking water during a human gestational equivalent period (GD0 - PND10). Hallmark indicators of metabolic disruption, hepatic steatosis, and metabolic syndrome were evaluated prior to birth through adulthood. Blood Cd levels in dams were similar to those observed in human pregnancy cohorts. There were no observed impacts of exposure on dams or pregnancy-related outcomes. Results of glucose and insulin tolerance testing revealed that Cd-exposure impaired glucose homeostasis in young adult offspring. Exposure-related increases in circulating triglycerides and hepatic steatosis were apparent only in females. By PND120, Cd-exposed females had become 30% heavier with 700% more perigonadal fat than unexposed control females. There was no evidence of dyslipidemia, steatosis, increased weight gain, nor increased adiposity in Cd-exposed male offspring. Hepatic transcriptome analysis at PND1, PND21, and PND42 revealed evidence for female-specific increases in oxidative stress and mitochondrial dysfunction with significant early disruption of retinoic acid signaling and altered insulin receptor signaling consistent with hepatic insulin sensitivity in adult females. The observed steatosis and metabolic syndrome-like phenotypes resulting from exposure to 500 ppb CdCl<sub>2</sub> during the pre- and perinatal period of development equivalent to human gestation indicate that Cd acts developmentally as a sex-specific delayed obesogen.</p>
Sign-specific stimulation "hot" and "cold" spots in Parkinson's disease validated with machine learning
<p><strong>Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become a standard therapy for Parkinson’s disease (PD). Despite extensive experience, however, the precise target of optimal stimulation and the relationship between site of stimulation and alleviation of individual signs remains unclear. We examined whether machine learning could predict the benefits in specific parkinsonian signs when informed by precise locations of stimulation.</strong></p> <p> </p> <p><strong>We studied 275 PD patients who underwent STN-DBS between 2003 and 2018. We selected pre-DBS and best available post-DBS scores from motor items of the Unified Parkinson's Disease Rating Scale (UPDRS-III) to discern sign-specific changes attributable to DBS. Volumes of tissue activated (VTAs) were computed and weighted by i) tremor, ii) rigidity, iii) bradykinesia, and iv) axial signs changes. Then, sign-specific sites of optimal (“hot spots”) and suboptimal efficacy (“cold spots”) were defined. These areas were subsequently validated using machine learning prediction of sign-specific outcomes with in-sample and out-of-sample data (n=51 STN-DBS patients from another institution).</strong></p> <p><strong> </strong></p> <p><strong>Tremor and rigidity hot spots were largely located outside and dorsolateral to STN whereas hot spots for bradykinesia and axial signs had larger overlap with STN. Using VTA overlap with sign-specific hot and cold spots, support vector machine (SVM) classified patients into quartiles of efficacy with ≥92% accuracy. The accuracy remained high (68-98%) when only considering VTA overlap with hot spots but was markedly lower (41-72%) when only using cold spots. The model also performed poorly (44-48%) when using only stimulation voltage, irrespective of stimulation location. Out-of-sample validation accuracy was ≥96% when using VTA overlap with the sign-specific hot and cold spots.</strong></p> <p><br> <strong>In two independent datasets, distinct brain areas could predict sign-specific clinical changes in PD patients with STN-DBS. With future prospective validation, these findings could individualize stimulation delivery to optimize quality of life improvement. </strong></p> <p><strong>Hot and cold spots for each sign are publicly available as binary labels in NIfTI format. </strong></p>
ss-PDMFA: size-specific, probabilistic, dynamic material flow analysis
<p><strong>Description of the dataset:</strong></p> <p>This dataset is related to the following publication:</p> <p>Title: Size-specific, dynamic, probabilistic material flow analysis of titanium dioxide releases into the environment</p> <p>Authors: Yuanfang Zheng, Bernd Nowack </p> <p>Submitted to the journal Environmental Science & Technology in November 2020.</p> <p>The files contain input files, final codes and raw results of the ss-PDMFA model.</p> <p> </p>
Research Artifact: How are Project-Specific Forums Utilized? A Study of Participation, Content, and Sentiment in the Eclipse Ecosystem
<p><strong>Research Artifact: How are Project-Specific Forums Utilized? A Study of Participation, Content, and Sentiment in the Eclipse Ecosystem</strong></p> <p><a href="https://github.com/yusufsn/EclipseForumData">https://github.com/yusufsn/EclipseForumData</a></p> <p>This is a research artefact for the paper: <strong>How are Project-Specific Forums Utilized? A Study of Participation, Content, and Sentiment in the Eclipse Ecosystem</strong>. This artifact is a repository consisting of collected dataset including (i) 289,061 threads, (ii) 216,864 extracted links from threads, (iii) 2,170 contributors, and the results of our qualitative analysis, (i) 1,142 manually annotated type of discussion and (ii) 1,142 manually annotated sentiment analysis. This artefact aims to enable researchers to replicate our mixed-methods quantitative results of the paper and reuse the dataset for further software engineering research.</p> <p>Contents</p> <ul> <li>dataset: <ul> <li><code>289061_threads.csv.zip</code> - 289,061 collected main threads of all users without post from webmaster (.zip format)</li> <li><code>216864_links.csv.zip</code> - 216,864 extracted links from collected threads (.zip format)</li> <li><code>2170_contributors.csv</code> - 2,170 list of contributions (.csv format)</li> </ul> </li> <li>Results of manual analysis: <ul> <li><a href="https://docs.google.com/spreadsheets/d/e/2PACX-1vQoRpcbrV66OEB4vaCG9Njq65zW7XpLRITYG3BlUOoa_DmeOKcdQIgYJ8y2aSlmL3y9bCUhjpP3rYmT/pubhtml">Manual annotation of discussion type</a></li> <li><a href="https://docs.google.com/spreadsheets/d/e/2PACX-1vQfyvsP1Zq3b9p_BYwkkgYXuEePJB6sIroC47jOUMcR5P8t7DCJFNpOJD565SPgqi--L3AAIQWs2kC5/pubhtml">Manual annotation of sentiment analysis</a></li> </ul> </li> </ul> <p>Authors</p> <ul> <li><a href="https://yusufsn.github.io/">Yusuf Sulistyo Nugroho</a></li> <li><a href="https://syful-is.github.io/">Syful Islam</a></li> <li>Keitaro Nakasai</li> <li><a href="https://ifrazrehman.github.io/">Ifraz Rehman</a></li> <li><a href="https://hideakihata.github.io/">Hideaki Hata</a></li> <li><a href="https://raux.github.io/">Raula Gaikovina Kula</a></li> <li><a href="https://cs.uwaterloo.ca/~m2nagapp/">Meiyappan Nagappan</a></li> <li><a href="https://matsumotokenichi.github.io/">Kenichi Matsumoto</a></li> </ul>
Protein codes for tetrameric and dimeric 6-phosphogluconate dehydrogenases and their signature sequence relevant to the cofactor specificity in the 6PGDH family.
<p>Here we present the Uniprot or Genbank code for tetrameric and dimeric 6-phosphogluconate dehydrogenases collected from different organisms. Besides, we include the sequence of the <span class="math-tex">\(\beta2-\alpha2\)</span> motif regarding the cofactor specificity in the 6PGDH family. </p> <p>The sequence data allows generating a phylogenetic tree of the 6PGDH family. The enzymes cluster first by their oligomerization state and then by their sequence in the <span class="math-tex">\(\beta2-\alpha2\)</span> motif, as is shown in the annexed figure. </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.