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1,944 results for “Class I”
Development of a tool for quantifying need-supportive coaching in technology-mediated exercise classes
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Data on weights and lengths from retrospective growth analysis of different stem age classes of Betula nana ramets from the Arctic LTER Nutrient and Warming manipulations in mosit acidic tussock tundra at 1995, Toolik Lake, AK.
This data file contains the data on weights and lengths from retrospective growth analysis of different stem age classes of Betula nana ramets from the Arctic LTER Nutrient and Warming manipulations in moist acidic tussock tundra at Toolik Lake.
Dateset The "blue eyed" in our school – overcoming stereotypes as the pathway to creating better conditions for pupil development in the school class - control group and equal socioeconomic status groups
<p>Dateset The “blue eyed” in our school – overcoming stereotypes as the pathway to creating better conditions for pupil development in the school class - control group and equal socioeconomic status groups</p>
JTeC: A Large Collection of Java Test Classes forTest Code Analysis and Processing
<p>The recent push towards test automation and test-driven development continues to scale up the dimensions of test code that needs to be maintained, analysed, and processed side-by-side with production code. As a consequence, on the one side regression testing techniques, e.g., for test suite prioritization or test case selection, capable to handle such large-scale test suites become indispensable; on the other side, as test code exposes own characteristics, specific techniques for its analysis and refactoring are actively sought. We present JTeC, a large-scale dataset of test cases that researchers can use for benchmarking the above techniques or any other type of tool expressly targeting test code. JTeC collects more than 2.5M+ test classes belonging to 31K+ GitHub projects and summing up to more than 430 Million LOCs of ready-to-use real-world test code.</p>
Data set for sub-millimetre MRI tissue class segmentation
<p>Sub-millimetre 7Tesla MRI image data set of the human brain for supervised training of algorithms to perform tissue class segmentation.</p> <p>The dataset contains preprocessed MRI images (co-registered + bias corrected) and corresponding ground truth labels.</p> <p>The dataset contains two different acquisitions:</p> <p>- MPRAGE dataset, based on 5 subjects, with T1w, PDw and T2w images</p> <p>- MP2RAGE dataset, based on 4 subjects, with inv1, inv2 and me gre images</p> <p> </p> <p>The following ground truth labels are provided:<br> [1] white matter<br> [2] grey matter<br> [3] cerebrospinal fluid<br> [4] ventricles<br> [5] subcortical<br> [6] vessels<br> [7] sagittal sinus</p> <p>Images are saved as nifti files and organized in BIDS format.</p> <p>This dataset is an extension of the following, initial dataset publication:</p> <p>* Dataset: A scalable method to improve gray matter segmentation at ultra high field MRI.</p> <p>The initial dataset is also available as a zenodo repository and can be downloaded from:<br> https://zenodo.org/record/1206163</p>
Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles (Dataset, Models & Code)
<p>Many digital libraries recommend literature to their users considering the similarity between a query document and their repository. However, they often fail to distinguish what is the relationship that makes two documents alike. In this paper, we model the problem of finding the relationship between two documents as a pairwise document classification task. To find the semantic relation between documents, we apply a series of techniques, such as GloVe, Paragraph-Vectors, BERT, and XLNet under different configurations (e.g., sequence length, vector concatenation scheme), including a Siamese architecture for the Transformer-based systems. We perform our experiments on a newly proposed dataset of 32,168 Wikipedia article pairs and Wikidata properties that define the semantic document relations. Our results show vanilla BERT as the best performing system with an F1-score of 0.93,<br> which we manually examine to better understand its applicability to other domains. Our findings suggest that classifying semantic relations between documents is a solvable task and motivates the development of recommender systems based on the evaluated techniques. The discussions in this paper serve as first steps in the exploration of documents through SPARQL-like queries such that one could find documents that are similar in one aspect but dissimilar in another.</p> <p>Additional information can be found on <a href="https://github.com/malteos/semantic-document-relations/">GitHub</a>.</p> <p>The following data is supplemental to the experiments described in our research paper. The data consists of:</p> <ul> <li>Datasets (articles, class labels, cross-validation splits)</li> <li>Pretrained models (Transformers, GloVe, Doc2vec)</li> <li>Model output (prediction) for the best performing models</li> </ul> <p><strong>Dataset</strong></p> <p>The Wikipedia article corpus is available in <code>enwiki-20191101-pages-articles.weighted.10k.jsonl.bz2</code>. The original data have been downloaded as <a href="https://dumps.wikimedia.org/enwiki/">XML dump</a>, and the corresponding articles were extracted as plain-text with <a href="https://radimrehurek.com/gensim/scripts/segment_wiki.html">gensim.scripts.segment_wiki</a>. The archive contains only articles that are available in training or test data.</p> <p>The actual dataset is provided as used in the stratified k-fold with <code>k=4</code> in <code>train_testdata__4folds.tar.gz</code>.</p> <pre><code>├── 1 │ ├── test.csv │ └── train.csv ├── 2 │ ├── test.csv │ └── train.csv ├── 3 │ ├── test.csv │ └── train.csv └── 4 ├── test.csv └── train.csv 4 directories, 8 files </code></pre> <p>Pretrained models</p> <p>PyTorch: vanilla and Siamese BERT + XLNet</p> <p>Pretrained model for each fold is available in the corresponding model archives:</p> <pre><code># Vanilla model_wiki.bert_base__joint__seq512.tar.gz model_wiki.xlnet_base__joint__seq512.tar.gz # Siamese model_wiki.bert_base__siamese__seq512__4d.tar.gz model_wiki.xlnet_base__siamese__seq512__4d.tar.gz </code></pre>
Replication package for class comment analysis
<p>This project contains the necessary material to replicate the project. It also contains supplementary data to give better insights into the results.</p>
Patents and certificates of addition granted in France from 1880 to 1903 by class of industry
<p><strong>**TITRE**</strong><br> Etat des brevets d'invention et des certificats d'addition délivrés en France entre 1880 et 1903 par classes d'industrie</p> <p><strong>**VARIABLES**</strong><br> CLASS : le nom donné est le nom de la classe d'industrie qui apparaît dans la source originale.</p> <p>SUB-CLASS : le nom donné est le nom de la sous-classe d'industrie qui apparaît dans la source originale.</p> <p>TYPE : brevets d'invention ou certificats d'addition</p> <p>YEAR : année de délivrance<br> NUMBER : le nombre de brevets d'invention et de certificats d'addition délivrés.</p> <p><strong>**SOURCES**</strong></p> <p><em>La propriété industrielle : organe officiel du Bureau international de l'Union pour la protection de la propriété industrielle</em></p> <p><br> année 1880 à 1884 : 1885/12, p. 13 ; année 1885<em> </em>:<em> </em>1886/8, p. 62 ; année 1886 : 1887/9, p. 72 ; année 1887 : 1889/5, p. 73 ; année 1888 : 1889/6, p. 90 ; année 1889 : 1890/07, p. 86 ;</p> <p>année 1890 : 1891/08, p. 110 ; année 1891 : 1892/08, p. 134 ; année 1892 : 1893/07, p. 100 ; année 1893 : 1894/08, p. 102 ; année 1894 : 1896/05, p. 81; année 1895 : 1897/02, p. 32; année 1896 : 1898/06, p. 100; année 1897 : 1899/01, p. 16 ; année 1898 : 1900/03, p. 55 ; année 1899 : 1900/08, p. 140 ;</p> <p>année 1900 : 1902/02, p. 32 ; année 1901 : 1903/03, p. 52 ; année 1902 : 1904/04, p. 72 ; année 1903 : 1906/03, p. 48.</p> <p>--------------------------------------------------------------------------------------------------</p> <p><strong>**TITLE**</strong><br> Number of patents granted and certificates of addition in France between 1880 and 1903 by classes of industry</p> <p><strong>**VARIABLES**</strong></p> <p>CLASS : the name given is the one of the class of industry that appears in the original source (in French).</p> <p>SUB-CLASS : the name given is the one of the sub-class of industry that appears in the original source (in French).</p> <p>TYPE : Patent (brevets) or certificate of addition</p> <p>YEAR : year of issue<br> <br> NUMBER : the number of patents and certificates of addition granted.</p> <p> </p> <p><strong>**SOURCES**</strong><br> <em>La propriété industrielle : organe officiel du Bureau international de l'Union pour la protection de la propriété industrielle</em></p> <p>year 1880 to 1884 : 1885/12, p. 13 ; year 1885 : 1886/8, p. 62 ; year 1886 : 1887/9, p. 72 ; year 1887 : 1889/5, p. 73 ; year 1888 : 1889/6, p. 90 ; year 1889 : 1890/07, p. 86 ;</p> <p>year 1890 : 1891/08, p. 110 ; year 1891 : 1892/08, p. 134 ; year 1892 : 1893/07, p. 100 ; year 1893 : 1894/08, p. 102 ; year 1894 : 1896/05, p. 81; year 1895 : 1897/02, p. 32; year 1896 : 1898/06, p. 100; year 1897 : 1899/01, p. 16 ; year 1898 : 1900/03, p. 55 ; year 1899 : 1900/08, p. 140 ;</p> <p>year 1900 : 1902/02, p. 32 ; year 1901 : 1903/03, p. 52 ; year 1902 : 1904/04, p. 72 ; year 1903 : 1906/03, p. 48.</p>
MSL Curiosity Rover Images with Science and Engineering Classes
<p> </p> <p><strong>Please note that the file msl-labeled-data-set-v2.1.zip</strong><strong> below contains the latest images and labels associated with this data set. </strong></p> <p> </p> <p><strong>Data Set Description</strong></p> <p>The data set consists of 6,820 images that were collected by the Mars Science Laboratory (MSL) Curiosity Rover by three instruments: (1) the Mast Camera (Mastcam) Left Eye; (2) the Mast Camera Right Eye; (3) the Mars Hand Lens Imager (MAHLI). With the help from Dr. Raymond Francis, a member of the MSL operations team, we identified 19 classes with science and engineering interests (see the "Classes" section for more information), and each image is assigned with 1 class label. We split the data set into training, validation, and test sets in order to train and evaluate machine learning algorithms. The training set contains 5,920 images (including augmented images; see the "Image Augmentation" section for more information); the validation set contains 300 images; the test set contains 600 images. The training set images were randomly sampled from sol (Martian day) range 1 - 948; validation set images were randomly sampled from sol range 949 - 1920; test set images were randomly sampled from sol range 1921 - 2224. All images are resized to 227 x 227 pixels without preserving the original height/width aspect ratio.</p> <p><strong>Directory Contents</strong></p> <ul> <li>images - contains all 6,820 images</li> <li>class_map.csv - string-integer class mappings</li> <li>train-set-v2.1.txt - label file for the training set</li> <li>val-set-v2.1.txt - label file for the validation set</li> <li>test-set-v2.1.txt - label file for the test set</li> </ul> <p>The label files are formatted as below:</p> <p>"Image-file-name class_in_integer_representation"</p> <p><strong>Labeling Process</strong></p> <p>Each image was labeled with help from three different volunteers (see Contributor list). The final labels are determined using the following processes:</p> <ul> <li>If all three labels agree with each other, then use the label as the final label.</li> <li>If the three labels do not agree with each other, then we manually review the labels and decide the final label.</li> <li>We also performed error analysis to correct labels as a post-processing step in order to remove noisy/incorrect labels in the data set. </li> </ul> <p><strong>Classes</strong></p> <p>There are 19 classes identified in this data set. In order to simplify our training and evaluation algorithms, we mapped the class names from string to integer representations. The names of classes, string-integer mappings, distributions are shown below:</p> <p>Class name, counts (training set), counts (validation set), counts (test set), integer representation</p> <p>Arm cover, 10, 1, 4, 0</p> <p>Other rover part, 190, 11, 10, 1</p> <p>Artifact, 680, 62, 132, 2</p> <p>Nearby surface, 1554, 74, 187, 3</p> <p>Close-up rock, 1422, 50, 84, 4</p> <p>DRT, 8, 4, 6, 5</p> <p>DRT spot, 214, 1, 7, 6</p> <p>Distant landscape, 342, 14, 34, 7</p> <p>Drill hole, 252, 5, 12, 8</p> <p>Night sky, 40, 3, 4, 9</p> <p>Float, 190, 5, 1, 10</p> <p>Layers, 182, 21, 17, 11</p> <p>Light-toned veins, 42, 4, 27, 12</p> <p>Mastcam cal target, 122, 12, 29, 13</p> <p>Sand, 228, 19, 16, 14</p> <p>Sun, 182, 5, 19, 15</p> <p>Wheel, 212, 5, 5, 16</p> <p>Wheel joint, 62, 1, 5, 17</p> <p>Wheel tracks, 26, 3, 1, 18</p> <p> </p> <p><strong>Image Augmentation</strong></p> <p>Only the training set contains augmented images. 3,920 of the 5,920 images in the training set are augmented versions of the remaining 2000 original training images. Images taken by different instruments were augmented differently. As shown below, we employed 5 different methods to augment images. Images taken by the Mastcam left and right eye cameras were augmented using a horizontal flipping method, and images taken by the MAHLI camera were augmented using all 5 methods. Note that one can filter based on the file names listed in the train-set.txt file to obtain a set of non-augmented images.</p> <ul> <li>90 degrees clockwise rotation (file name ends with -r90.jpg)</li> <li>180 degrees clockwise rotation (file name ends with -r180.jpg)</li> <li>270 degrees clockwise rotation (file name ends with -r270.jpg)</li> <li>Horizontal flip (file name ends with -fh.jpg)</li> <li>Vertical flip (file name ends with -fv.jpg)</li> </ul> <p><strong>Acknowledgment</strong></p> <p>The authors would like to thank the volunteers (as in the Contributor list) who provided annotations for this data set. We would also like to thank the PDS Imaging Note for the continuous support of this work.</p>
Residential Building Occupancy Class Image Classifier
<p>0 : RES1 (single-family)</p> <p>1 : RES3 (multi-family)</p>
Song parameters, repertoire size and song sharing within and across age classes in the saffron finch
<p>Birds sing mostly to attract partners or to defend territories or resources. In relation to the first function, song can vary with age if older experienced males signal their quality through their vocal output. Regarding the second function, song can also vary with age if singing behavior helps mediate social interactions through repertoire sharing with neighbors. Here, we investigate whether song parameters change with age, and in which direction, in saffron finches Sicalis flaveola pelzelni, obligate secondary cavity nesters which produce elaborate melodious songs and show delayed plumage maturation. Cross-sectional comparisons revealed that second year (SY) males sing shorter syllables, and shorter and less versatile songs than older after second year males (ASY), as expected if the latter are more experienced singers. Longitudinal comparisons, which better depict age-related changes, showed that as birds age one year, song length and repertoire size do not change significantly, syllable duration shortens and, as expected for experienced singers, song versatility increases. Correlations between repertoire distance and nesting distance suggest that both SY and ASY males might be adjusting their repertoires to those of ASY neighbors; the former pattern conforms to the expectations if young birds try to emulate the songs of more experienced birds, while the latter is expected if song sharing helps de-escalating antagonistic social interactions amongst males. This research, which provides the first description of song parameters in young second year saffron finches, expands our knowledge of song variation across age classes in songbirds.</p>
Data from: Major histocompatibility complex class II variation in bottlenose dolphin from Adriatic Sea: inferences about the extent of balancing selection
The bottlenose dolphin (Tursiops truncatus) is the most common cetacean species worldwide and the only marine mammal species resident in the Croatian part of the Adriatic Sea. To gain insight into genetic diversity of bottlenose dolphins at adaptively important loci relevant to conservation, we analysed the polymorphism of major histocompatibility complex (MHC) genes, which play a key role in pathogen confrontation and clearance. Specifically, we examined the diversity of MHC class II DRA, DQA and DQB alleles in 50 bottlenose dolphins from the Adriatic Sea collected between 1997 and 2011 and in 12 animals from other Mediterranean locations. Notable variation in DQA, DQB and three-locus haplotypes was found, with all 10 DQA and 12 DQB alleles encoding unique protein products. Analysis of the ratio of non-synonymous to synonymous substitution rates suggests that positive selection acts at both highly variable loci. Phylogenetic analyses revealed trans-species polymorphism at the DQB locus, strongly indicating the influence of balancing selection in the long term. In fact, the balancing selection observed in bottlenose dolphins is higher than that reported for most other cetaceans and comparable to that seen in terrestrial mammals.
Data from: Extra-pair mating in a passerine bird with highly duplicated MHC class II: Preference for the golden mean
Genes of the major histocompatibility complex (MHC) are essential in vertebrate adaptive immunity, and they are highly diverse and duplicated in many lineages. While it is widely established that pathogen-mediated selection maintains MHC diversity through balancing selection, the role of mate choice in shaping MHC diversity is debated. Here, we investigate female mating preferences for MHC class II (MHCII) in the bluethroat (<i></i>Luscinia svecica<i></i>), a passerine bird with high levels of extra-pair paternity and extremely duplicated MHCII. We genotyped family samples with mixed paternity and categorized their MHCII alleles according to their functional properties in peptide binding. Our results strongly indicate that females select extra-pair males in a non-random, self-matching manner that provides offspring with an allelic repertoire size closer to the population mean, as compared to offspring sired by the social male. This is consistent with a "compatible genes" model for extra-pair mate choice where the optimal allelic diversity is intermediate, not maximal. This "golden mean" presumably reflects a trade-off between maximizing pathogen recognition benefits and minimizing autoimmunity costs. Our study exemplifies how mate choice can reduce the population variance in individual MHC diversity and exert strong stabilizing selection on the trait. It also supports the hypothesis that extra-pair mating is adaptive through enhanced genetic quality of offspring.
Data from: Patterns of selection and allele diversity of class I and class II major histocompatibility loci across the species range of sockeye salmon (Oncorhynchus nerka)
The major histocompatibility complex (MHC), an important component of the vertebrate immune system, provides an important suite of genes to examine the role of genetic diversity at non-neutral loci for population persistence. We contrasted patterns of diversity at the two classical MHC loci in sockeye salmon (Oncorhynchus nerka), MHC class I (UBA) and MHC class II (DAB), and neutral microsatellite loci across 70 populations spanning the species range from Washington State to Japan. There was no correlation in allelic richness or heterozygosity between MHC loci or between MHC loci and microsatellites. The two unlinked MHC loci may be responding to different selective pressures; the distribution of FST values for the two loci was uncorrelated, and evidence for both balancing and directional selection on alleles and lineages of DAB and UBA was observed in populations throughout the species range but rarely on both loci within a population. These results suggest that fluctuating selection has resulted in the divergence of MHC loci in contemporary populations.
Data from: Intercolony movement of pre-breeding seabirds over oceanic scales: implications of cryptic age-classes for conservation and metapopulation dynamics
Aim: Demographic linkage between subpopulations plays a critical role in population processes. Metapopulation dynamics, however, remains one of the most poorly understood aspects of population biology. This is especially true for small, pelagic seabirds because their discrete subpopulations are located on offshore islands, separated by vast areas of open ocean, making monitoring logistically challenging. Seabird populations often contain large numbers of immature pre-breeders that may be important for subpopulation connectivity and demography, but are poorly studied. Here we provide evidence for intercolony movement of pre-breeding Leach's storm-petrels Oceanodroma leucorhoa among three colonies spanning the North Atlantic Ocean. We discuss their influence on metapopulation dynamics and the extinction risk of a subpopulation under threat from extreme predation. Location: North Atlantic Ocean Islands (Scotland, Canada & Iceland). Methods: We use a novel application of Bayesian stable isotope mixing models to infer recent movement of pre-breeding birds between three major breeding populations in the North Atlantic. Carbon and nitrogen stable isotope values from breeding birds (central place foragers) sampled at each colony were used as model sources and pre-breeding birds as model mixtures. Results: Of 134 pre-breeding Leach's storm-petrels sampled at three colonies across the North Atlantic, five had isotope mixing model estimates dissimilar (< 25%) to their colony of capture and were instead isotopically similar to another breeding region. Nineteen further pre-breeders had highly mixed signatures (< 50% for the colony of capture), indicating possible recent movement between colonies. Main conclusions: Our findings provide evidence for interpopulation connectivity of pre-breeding Leach's storm-petrels among colonies spanning the North Atlantic. These results highlight the significance of cryptic young age-classes in metapopulation dynamics and the demographic processes. Moreover, they provide us with a better understanding of how one subpopulation remains extant, despite experiencing extreme predation rates.
Data from: Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development
We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine (Vitis vinifera) and tomato (Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named "fight-club hubs" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named "switch genes" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops.
Data from: Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes
We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized.
Data from: MHC class I expression dependent on bacterial infection and parental factors in whitefish embryos (Salmonidae)
Ecological conditions can influence not only the expression of a phenotype, but also the heritability of a trait. As such, heritable variation for a trait needs to be studied across environments. We have investigated how pathogen challenge affects the expression of MHC genes in embryos of the lake whitefish Coregonus palaea. In order to experimentally separate paternal (i.e. genetic) from maternal and environmental effects, and determine whether and how stress affects the heritable variation for MHC expression, embryos were produced in full-factorial in vitro fertilizations, reared singly, and exposed at 208 degree days (late-eyed stage) to either one of two strains of Pseudomonas fluorescens that differ in their virulence characteristics (one increased mortality, while both delayed hatching time). Gene expression was assessed 48 h postinoculation, and virulence effects of the bacterial infection were monitored until hatching. We found no evidence of MHC class II expression at this stage of development. MHC class I expression was markedly down-regulated in reaction to both pseudomonads. While MHC expression could not be linked to embryo survival, the less the gene was expressed, the earlier the embryos hatched within each treatment group, possibly due to trade-offs between immune function and developmental rate or further factors that affect both hatching timing and MHC expression. We found significant additive genetic variance for MHC class I expression in some treatments. That is, changes in pathogen pressures could induce rapid evolution in MHC class I expression. However, we found no additive genetic variance in reaction norms in our study population.
Data from: TAPBPR mediates peptide dissociation from MHC class I using a leucine lever
Tapasin and TAPBPR are known to perform peptide editing on major histocompatibility complex class I (MHC I) molecules, however, the precise molecular mechanism(s) involved in this process remain largely enigmatic. Here, using immunopeptidomics in combination with novel cell-based assays that assess TAPBPR-mediate peptide exchange, we reveal a critical role for the K22-D35 loop of TAPBPR in mediating peptide exchange on MHC I. We identify a specific leucine within this loop that enables TAPBPR to facilitate peptide dissociation from MHC I. Moreover, we delineate the molecular features of the MHC I F pocket required for TAPBPR to promote peptide dissociation in a loop-dependent manner. These data reveal that chaperone-mediated peptide editing of MHC I can occur by different mechanisms dependent on the C-terminal residue that the MHC I accommodates in its F pocket and provide novel insights that may inform the therapeutic potential of TAPBPR manipulation to increase tumour immunogenicity.
Data from: No evidence for MHC class I based disassortative mating in a wild population of great tits
Genes of the major histocompatibility complex (MHC) are regarded as a potentially important target of mate choice due to the fitness benefits that may be conferred to the offspring. According to the complementary genes hypothesis, females mate with MHC dissimilar males to enhance the immunocompetence of their offspring or to avoid inbreeding depression. Here, we investigate whether selection favours a preference for maximally dissimilar or optimally dissimilar MHC class I types, based on MHC genotypes, average amino acid distances and the functional properties of the antigen-binding sites (MHC supertypes); and whether MHC type dissimilarity predicts relatedness between mates in a wild great tit population. In particular, we explore the role that MHC class I plays in female mate choice decisions while controlling for relatedness and spatial population structure, and examine the reproductive fitness consequences of MHC compatibility between mates. We find no evidence for the hypotheses that females select mates on the basis of either maximal or optimal MHC class I dissimilarity. A weak correlation between MHC allele sharing and relatedness, and between MHC supertype sharing and relatedness suggests that MHC dissimilarity at functional variants may not provide an effective index of relatedness. Moreover the reproductive success of pairs did not vary with MHC dissimilarity. Our results provide no support for the suggestion that selection favours, or that mate choice realises, a preference for complimentary MHC types.
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.