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1,389
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Dataset results
1,389 results for “multimodality”
Multimodal epigenetic changes and altered NEUROD1 chromatin binding in the mouse hippocampus underlie FOXG1 syndrome
GEO Series GSE189113. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Temporal multimodal single-cell profiling of native hematopoiesis illuminates altered differentiation trajectories with age
GEO Series GSE175702. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing.
Direct transposition of native DNA for sensitive multimodal single-molecule sequencing
GEO Series GSE225314. Homo sapiens; Mus musculus. 28 samples. Type: Other.
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algorithms such as linear regression or neural networks attempt to fit the target variable as a function of the input variables without regard to the underlying joint distribution of the variables. As a result, these global models are not sensitive to variations in the local structure of the input space. Several algorithms, including the mixture of experts model, classification and regression trees (CART), and others have been developed, motivated by the fact that a variability in the local distribution of inputs may be reflective of a significant change in the target variable. While these methods can handle the non-stationarity in the relationships to varying degrees, they are often not scalable and, therefore, not used in large scale data mining applications. In this paper we develop Block-GP, a Gaussian Process regression framework for multimodal data, that can be an order of magnitude more scalable than existing state-of-the-art nonlinear regression algorithms. The framework builds local Gaussian Processes on semantically meaningful partitions of the data and provides higher prediction accuracy than a single global model with very high confidence. The method relies on approximating the covariance matrix of the entire input space by smaller covariance matrices that can be modeled independently, and can therefore be parallelized for faster execution. Theoretical analysis and empirical studies on various synthetic and real data sets show high accuracy and scalability of Block-GP compared to existing nonlinear regression techniques.
Multimodal and multisensory coding in the Drosophila larval peripheral gustatory center
GEO Series GSE149975. Drosophila melanogaster. 3 samples. Type: Expression profiling by high throughput sequencing.
Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS
GEO Series GSE219047. Mus musculus. 96 samples. Type: Expression profiling by high throughput sequencing.
Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS
GEO Series GSE201575. Mus musculus. 116 samples. Type: Expression profiling by high throughput sequencing.
Multimodal multiscale analysis reveals flexible DNA contacts of bacterial nucleoprotein filaments
GEO Series GSE157512. Escherichia coli. 36 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A Multimodal Study of Wild Tomato Species Introgressions Unravels the Genetic Basis of Transcriptome and Metabolome Variation in Important Fruit Traits
GEO Series GSE151451. Solanum lycopersicum x Solanum pennellii. 523 samples. Type: Expression profiling by high throughput sequencing.
SIGNAL-seq: Multimodal Single-cell Inter- and Intra-cellular Signalling Analysis I
GEO Series GSE256403. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing; Other.
Multimodal blood based profiling reveals insights into mechanisms of immunotherapy resistance
GEO Series GSE295942. Homo sapiens. 96 samples. Type: Expression profiling by high throughput sequencing.
SIGNAL-seq: Multimodal Single-cell Inter- and Intra-cellular Signalling Analysis II
GEO Series GSE256404. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing; Other.
Multimodal analysis reveals cellular diversity and divergent circuits of the zona incerta
GEO Series GSE273853. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Single-organism multimodal characterisation of eukaryotic plankton with Ukiyo-e-Seq
GEO Series GSE274796. marine plankton environmental sample. 70 samples. Type: Expression profiling by high throughput sequencing.
AMAR-seq: automated multimodal sequencing of DNA methylation, chromatin accessibility, and RNA expression with single-cell resolution
GEO Series GSE261788. Mus musculus; Homo sapiens. 83 samples. Type: Expression profiling by high throughput sequencing; Methylation profiling by high throughput sequencing; Other.
Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS
GEO Series GSE247519. Homo sapiens. 192 samples. Type: Expression profiling by high throughput sequencing.
Multimodal single cell analysis of molecular profiles of paired tissues of cutaneous T cell lymphoma
GEO Series GSE171811. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
BulkRNAseq - Neurotransmitters regulate distinct phases of multimodal human interneuron migration
GEO Series GSE182614. Homo sapiens. 52 samples. Type: Expression profiling by high throughput sequencing.
K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations
<p>ABSTRACT: Recognizing emotions during social interactions has many potential applications with the popularization of low-cost mobile sensors, but a challenge remains with the lack of naturalistic affective interaction data. Most existing emotion datasets do not support studying idiosyncratic emotions arising in the wild as they were collected in constrained environments. Therefore, studying emotions in the context of social interactions requires a novel dataset, and K-EmoCon is such a multimodal dataset with comprehensive annotations of continuous emotions during naturalistic conversations. The dataset contains multimodal measurements, including audiovisual recordings, EEG, and peripheral physiological signals, acquired with off-the-shelf devices from 16 sessions of approximately 10-minute long paired debates on a social issue. Distinct from previous datasets, it includes emotion annotations from all three available perspectives: self, debate partner, and external observers. Raters annotated emotional displays at intervals of every 5 seconds while viewing the debate footage, in terms of arousal-valence and 18 additional categorical emotions. The resulting K-EmoCon is the first publicly available emotion dataset accommodating the multiperspective assessment of emotions during social interactions.</p> <pre><code>+---------------------------------------+ | Changelog (last updated: Jul 7, 2020) | +---------------------------------------+ * Version 1.0.0 (Jul 7, 2020): - Updated emotion_annotations.tar.gz: - Updated aggregated external annotations to support the reproduction of technical validation results. * Version 0.2.0 (May 11, 2020): - Added data_quality_tables.tar.gz - Updated emotion_annotations.tar.gz - Newly added aggregated external annotations. - Updated metadata.tar.gz: - Added a new column to data_availability.csv to show the availability of aggregated external annotations. * Version 0.1.0 (Apr 25, 2020): - Added debate_audios.tar.gz - Added debate_recordings.tar.gz - Added e4_data.tar.gz - Added emotion_annotations.tar.gz (self, partner, external) - Added metadata.tar.gz - Added neurosky_polar_data.tar.gz</code></pre> <p> </p>
BioS-DB: a multimodal database of individuals in a public speaking scenario, including emotional annotation
<p>The BioS-DB (BioSpeech Database), is a database of indivduals speaking infront of others in both German and English. BioS-DB includes 55 indivdual (33 male and 22 female), with a mean age of 28.9 years ( ± 10.5 years). Individuals were predominately German Natives (33) - and either students (30) or staff from the computer science department at the University of Augsburg, Germany. The average speech length was 45 s for German and 42 s for English.</p> <p>During the speech, individuals were being evaluated for their emotion (valence / arousal) in a time-continuous way. Individuals were also attached to Blood Volume Pulse, and Skin Conductance sensors, while audio was captured from a lapel microphone and additionally a room microphone.</p> <p>Alice Baird, Shahin Amiriparian, Miriam Berschnider, Maximilian Schmitt, and Björn Schuller (2019),<em> Predicting Biological Signals from Speech: Introducing a Novel Multimodal Dataset and Results</em>, The Multimodal Signal Processing Conference, Kuala Lumpur, Malaysia, Sept 2019. 5 pages.</p> <p><strong>Version 2.0: </strong>This version contains the raw biological signal, and the individual annotations for re-computing the gold-standard. </p> <p>Alice Baird, Shahin Amiriparian, Manuel Milling, Björn Schuller (2020), <em>Emotion Recognition in Public Speaking Scenarios Utilising an LSTM-RNN Approach With Attention, </em>The Speech Language Technology Conference, held virtually (to appear) Jan. 2021. 5 pages. </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.