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Dataset results
217 results for “CI”
The HDAC inhibitor CI-994 acts as a molecular memory aid by facilitating synaptic and intra-cellular communication after learning [RNA-seq]
GEO Series GSE185453. Mus musculus. 32 samples. Type: Expression profiling by high throughput sequencing.
Iso-Seq analysis of barley CI 16151 and fast-neutron-derived, immune-compromised mutants infected with the powdery mildew fungus (Blumeria graminis f. sp. hordei; isolate 5874)
GEO Series GSE165730. Hordeum vulgare; Blumeria hordei. 6 samples. Type: Expression profiling by high throughput sequencing; Other.
Parallel analysis of RNA ends (PARE) sequencing of Barley CI 16151 and fast-neutron-derived, immune-compromised mutants infected with the powdery mildew fungus (Blumeria graminis f. sp. hordei; isolat
GEO Series GSE116691. Hordeum vulgare; Blumeria hordei. 5 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Figure 1 from: Arvanitidis C, Basset A, van Tienderen P, Huertas Olivares CI, Di Muri C, de Moncuit L, Los W (2024) LifeWatch ERIC Strategic Working Plan Outcomes. Research Ideas and Outcomes 10: e119943. https://doi.org/10.3897/rio.10.e119943
Figure 1 The four Priorities identified for the next implementation period of LW ERIC.
Figure 1 from: Argañaraz CI, Gleiser RM (2017) Does urbanization have positive or negative effects on Crab spider (Araneae: Thomisidae) diversity? Zoologia 34: 1-8. https://doi.org/10.3897/zoologia.34.e19987
Figure 1 - Location of sampling sites in Córdoba city, Argentina.
Selective auditory attention in CI users - EEG data
<h2><span>Experiment</span></h2> <p><span>We conducted a selective auditory attention experiment, </span><span>where stimuli were presented in the free room over two </span><span>loudspeakers separated by</span> <span>60°. </span><span>Before each trial, participants received instructions directing their attention to a specific audiobook. This guidance was provided visually on a screen, featuring a symbol indicating the selected audiobook’s direction. </span><span>Initially, we conducted eight trials in a single-speaker scenario, where only one audiobook was presented from alternating sides. Each trial lasted approximately two minutes. After every two trials, the presented story changed. In twelve subsequent trials, we implemented a competing-speaker paradigm, where two stories were presented simultaneously. However, the distractor story started 10 s later, affording participants time to discern the target speaker. We further randomized the organization by starting with the block of s2 stimuli instead of s1 for every second participant. </span></p> <p> </p> <h2><span>EEG Recording</span></h2> <p><span>We collected EEG data using an actiCHamp System (BrainProducts GmbH, Germany) equipped with 32 electrodes. For each participant between two and four electrodes were removed due to their proximity to the CI magnet and sound processor. The sampling rate was set at 1 kHz, and an online low-pass filter with a cutoff frequency of 280 Hz was implemented. Prior to the experiment, electrode impedances were maintained below 20 kΩ. We monitored the impedances through<br>both the single-speaker and competing-speaker scenarios, and, if needed, applied additional conductive gel to ensure that the impedances remained below the threshold of 20 kΩ. For synchronizing the audio and the EEG recording, we used an audio splitter and recorded the presented audio as two auxiliary channel over the EEG recorder with two StimTraks (BrainProducts GmbH, Germany) as adapter. We performed an offline correlation analysis between the recorded audio signal and delayed versions of the clean stimuli. The delay with highest value in Pearson’s r is used to align the respective stimuli with the EEG recording. Additionally, we sent onse</span></p> <h2><span>Dataset</span></h2> <p><span>We provide the data in hdf5 format. </span></p> <p><span>It includes:</span></p> <ul> <li><span>The EEG recording (raw and ICA-cleaned (read the paper for the method))</span></li> <li><span>Stimuli and precalculated features (speech envelope and onset envelope)</span></li> </ul> <p><span>For organization of the file and an example of how to read the data using python, see the <a href="../api/records/10980117/draft/files/hdf5_dataset_info.txt/content" target="_blank" rel="noopener noreferrer">hdf5_dataset_info.txt</a> file.</span></p>
Java OSS Travis-CI Build Failure Dataset
<p>Presented here are the GitHub repositories, Travis-CI build logs, and their categorizations, that were used in the publication "An Empirical Analysis of Build Failures in the Continuous Integration Workflows of Java-Based Open-Source Software" in <em>14th International Conference on Mining Software Repositories (MSR'17)</em>, 2017 (<a href="https://doi.org/10.1109/MSR.2017.54">https://doi.org/10.1109/MSR.2017.54</a>)</p> <p>Files:</p> <ul> <li><strong>git-repositories.tar.gz</strong><br> contains the Git repositories analyzed. Each commit that triggered a Travis-CI build (beginning from the time the continuous mining process was started) is tagged with the Travis-CI build ID</li> <li><strong>logcat-categories-and-patterns.tar.gz</strong><br> contains the error categories of the analyzed log files that were coded from the exploratory analysis</li> <li><strong>projects.csv</strong><br> maps the Travis-CI project ID to the GitHub project slug</li> <li><strong>travis-ci-logs.tar</strong><br> contains for each project the analyzed log files that were scraped from Travis-CI. Each txt.gz file in the project folders contains the log of one Travis <em>job</em>. A build may have multiple jobs.</li> </ul> <p>What is currently not part of this upload is the data for associating builds (as indicated by the git tag) and their job logs (the name of the txt.gz files). This can however be queried from the Travis-CI API (<a href="https://docs.travis-ci.com/api">https://docs.travis-ci.com/api</a>)</p>
A Phase II Study of CI-1033 in Treating Patients With Metastatic (Stage IV) Breast Cancer
ClinicalTrials.gov study NCT00051051. IPD Sharing: Not stated. Countries: 9. Publications: 0.
Risk Factors and Deep Learning Model for CI-AKI
ClinicalTrials.gov study NCT06596785. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Gemcitabine With or Without CI-994 in Treating Patients With Advanced Non-small Cell Lung Cancer
ClinicalTrials.gov study NCT00005093. IPD Sharing: Not stated. Countries: 2. Publications: 0.
CI-994 in Treating Patients With Advanced Myeloma
ClinicalTrials.gov study NCT00005624. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Benefits of a Contralateral Routing of Signals (CROS) System in Unilateral CI-recipients
ClinicalTrials.gov study NCT03078920. IPD Sharing: NO. Countries: 1. Publications: 0.
QoL Between CIEDs With and Without Rate Adaptive Pacing
ClinicalTrials.gov study NCT04383392. IPD Sharing: NO. Countries: 1. Publications: 0.
Cost-effectiveness Analysis on Remote Monitoring for CIEDs in Japan by Using Systematic Review Methodology
ClinicalTrials.gov study NCT03747809. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Effects of CI on Tinnitus and Its Symptoms
ClinicalTrials.gov study NCT05453019. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Performance of Different Sound Paths in Adult NeuroZti CI-users
ClinicalTrials.gov study NCT07033130. IPD Sharing: NO. Countries: 1. Publications: 0.
Safety and Efficacy Study of CI-135 CAR-T Cells in Subjects with Relapsed or Refractory Acute Myeloid Leukemia
ClinicalTrials.gov study NCT05266950. IPD Sharing: NO. Countries: 1. Publications: 0.
PH 1 Evaluation Of Oral CI-1033 In Combination With Paclitaxel/ Carboplatin As 1st Line Chemotherapy In NSCLC Patients
ClinicalTrials.gov study NCT00174356. IPD Sharing: Not stated. Countries: 2. Publications: 0.
CI-1040 in Treating Patients With Advanced Breast, Colon, Pancreatic, or Non-Small Cell Lung Cancer
ClinicalTrials.gov study NCT00033384. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Multicenter Phase 2 Study of CI-1040 in Patients With Advanced Nonsmall-Cell Lung, Breast, Colon and Pancreatic Cancer
ClinicalTrials.gov study NCT00034827. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.