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878 results for “human factors”

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zenodo32/100

Human umbilical cord mesenchymal stem cell-derived exosomes combined with mouse nerve growth factor can more effectively ameliorate the motor disorder and brain pathological injury in mice with cerebral palsy

<p>Supplementary Table 1.The statistics of the &nbsp;pole-climbing experiments and the horizontal network test</p> <p>Supplementary Table 2.Results of Kruskal&ndash;Wallis test as presented in pole-climbing experiments and the horizontal network test.</p> <p>Supplementary Figure 1. Identification of human umbilical cord mesenchymal stem cell exosomes (hUC-MSCs-exos)</p> <p>Supplementary Figure 2. Results of horizontal network test and pole-climbing experiments.</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

Human umbilical cord mesenchymal stem cell-derived exosomes combined with mouse nerve growth factor can more effectively ameliorate themotor disorder and brain pathological injury inmice with cerebral palsy

<p>This research design.</p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

Human and Organizational Factors and their Influence on Turnover in Global Software Development Projects

<p><strong>LIST OF PAPERS -&nbsp;Human and Organizational Factors and their Influence on Turnover in Global Software Development Projects</strong></p> <p>&nbsp;</p>

opencc-by-4.0Jul 2022View details →
zenodo32/100

Benchmark and integration of resources for the estimation of human transcription factor activities

<p>Data used to benchmark human TF-target datasets via TF activities in 3 benchmark datasets. Described in&nbsp;<a href="https://www.biorxiv.org/content/biorxiv/early/2018/06/18/337915.full.pdf">Garcia-Alonso et al 2019</a></p> <p>Check&nbsp;<a href="https://github.com/saezlab/TFbenchmark">https://github.com/saezlab/TFbenchmark</a>&nbsp;to access the corresponding code.</p> <p>&nbsp;</p> <p>&nbsp;</p> <p><strong>Study abstract</strong></p> <p>Prediction of transcription factor (TF) activities from the gene expression of their targets (i.e. TF regulon) is becoming a widely-used approach to characterize the functional status of transcriptional regulatory circuits. Several strategies and datasets have been proposed to link the target genes likely regulated by a TF, each one providing a different level of evidence. The most established ones are: (i) manually curated repositories, (ii) interactions derived from ChIP-seq binding data, (iii)&nbsp;<em>in silico</em>&nbsp;prediction of TF binding on gene promoters, and (iv) reverse-engineered regulons from large gene expression datasets. However, it is not known how these different sources of regulons affect the TF activity estimations, and thereby downstream analysis and interpretation. Here we compared the accuracy and biases of these strategies to define human TF regulons by means of their ability to predict changes in TF activities in three reference benchmark datasets. We assembled a collection of TF-target interactions among 1,541 TFs and evaluated how the different molecular and regulatory properties of the TFs, such as the DNA-binding domain, specificities or mode of interaction with the chromatin, affect the predictions of TF activity changes. We assessed their coverage and found little overlap on the regulons derived from each strategy and better performance by literature-curated information followed by ChIP-seq data. We provide an integrated resource of all TF-target interactions derived through these strategies with a confidence score, as a resource for enhanced prediction of TF activities.</p>

opencc-by-4.0Jun 2018View details →
zenodo32/100

Supplementary Material for Human Factors in the Design of Chatbot Interactions: Conversational Design Practices

<p>Supplementary Material for the thesis entitled <em>Human Factors in the Design of Chatbot Interactions: Conversational Design Practices.</em></p> <p>This repository contains the following files<em>:</em></p> <ul> <li><em>systematic_literature_review_data -&gt; </em>Dataset of the retrieved papers from the SLR, the indication of papers that were removed at each step of the protocol, the list of accepted papers, and the search strings that were used;</li> <li><em>guide_vX -&gt; </em>Faithful prints of the guide&#39;s web pages that were shared with the validation participants. V1 was used in the survey, V2 was used in the case study, and V3 is the final version;</li> <li><em>validation_survey</em> -&gt; <ul> <li>A copy of the Google Forms questionnaire that was used in the survey;</li> <li>Sheet with the answers to this survey;</li> </ul> </li> <li><em>validation_case_study</em> -&gt; <ul> <li><em>conversation_samples -&gt; </em>Conversations made by the participants in the case study stages. In each file, the conversation from the left was made without the guide, and the one from the right was created with the guide;</li> <li><em>interview_transcripts -&gt; </em>Transcripts of the interviews conducted with each participant at the last stage of the case study;</li> <li><em>instructions_to_participants.pdf</em> -&gt; File provided to participants containing the instructions for each step of the case study;</li> <li><em>transcripts_coding.xlsx -&gt; </em>Sheet containing transcripts from participants&#39; responses and the corresponding code after the thematic analysis;</li> </ul> </li> </ul>

opencc-by-4.0Jan 2023View details →
zenodo32/100

Managing Human Factors in Automated Vehicle Development: Towards Challenges and Practices

<p>This data set complements our publication with the title:</p> <p>&quot;Managing Human Factors in Automated Vehicle Development: Towards Challenges and Practices&quot; to appear in Proceedings of&nbsp;IEEE 31st International Requirements Engineering Conference (RE&#39;23), Hannover, Germany, 2023&nbsp;</p> <p>To support our research, we are providing two files:</p> <p>a) Interview Guide<br> b) Overview of Themes</p> <p>Please note that the themes mentioned in the theme file are not directly relevant to this specific paper. They relate to another study conducted using the same dataset. We have included these themes to demonstrate that the dataset was used for two separate papers, each examining different aspects.</p>

opencc-by-4.0Mar 2023View details →
zenodo32/100

Fcs files used in "Unravelling human hematopoietic progenitor cell diversity through association with intrinsic regulatory factors"

<p>Mass cytometry data from the manuscript, &quot;Unravelling human hematopoietic progenitor cell diversity through association with intrinsic regulatory factors&quot;. This repository contains singlet-gated, viable, CD45+, batch-corrected cells from tissue samples across three batches. BM=bone marrow, mPB=mobilized peripheral blood, FL=fetal liver, CB=cord blood. Each fcs files is a unique donor, except BM1, which&nbsp;was collected in each batch as a normalization control.</p>

opencc-by-4.0Aug 2023View details →
zenodo32/100

Continuous Experimentation and Human Factors

<p>This interview guide complements our&nbsp;manuscript, currently under submission, titled &quot;Continuous Experimentation and Human Factors: An Exploratory Study.&quot;</p>

opencc-by-4.0Jul 2023View details →
ClinicalTrials.gov32/100

Efficacy and Safety of Activated Recombinant Human Factor VII in Refractory Haemorrhagic Cystitis

ClinicalTrials.gov study NCT01561352. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

A Study of Bevacizumab (Avastin) in Combination With Neoadjuvant Treatment Regimens in Participants With Primary Human Epidermal Growth Factor Receptor 2 (HER2) Negative Breast Cancer

ClinicalTrials.gov study NCT00773695. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

A Study to Assess Preference for Subcutaneous Trastuzumab Treatment in Participants With Human Epidermal Growth Factor Receptor (HER)2-Positive Metastatic Breast Cancer Responding to First-Line Intrav

ClinicalTrials.gov study NCT01810393. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Efficacy and Safety of Activated Recombinant Human Factor VII in Severely Injured Trauma Patients

ClinicalTrials.gov study NCT01563523. IPD Sharing: Not stated. Countries: 9. Publications: 9.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

A Phase II, Double-Blind Trial of Recombinant Human Nerve Growth Factor for Treatment of HIV-Associated Sensory Neuropathy

ClinicalTrials.gov study NCT00000842. IPD Sharing: Not stated. Countries: 1. Publications: 6.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Weekly Gemcitabine and Trastuzumab in the Treatment of Patients With Human Epidermal Growth Factor Receptor 2 (HER2) Positive Metastatic Breast Cancer

ClinicalTrials.gov study NCT00193063. IPD Sharing: Not stated. Countries: 0. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

A Study to Evaluate Lumretuzumab in Combination With Pertuzumab and Paclitaxel in Participants With Metastatic Breast Cancer Expressing Human Epidermal Growth Factor Receptor (HER) 3 and HER2 Protein

ClinicalTrials.gov study NCT01918254. IPD Sharing: Not stated. Countries: 4. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Efficacy and Safety of Activated Recombinant Human Factor VII in Treatment of Bleeding in Patients Following Allogeneic Stem Cell Transplantation

ClinicalTrials.gov study NCT01562158. IPD Sharing: Not stated. Countries: 16. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Immuno Positron Emission Tomography Study of GSK2849330 in Subjects With Human Epidermal Growth Factor Receptor 3-Positive Solid Tumors

ClinicalTrials.gov study NCT02345174. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

Human Epidermal Growth Factor Receptor 2 (HER2) Positive Unresectable Locally Advanced or Metastatic Breast Cancer Disease Registry Study

ClinicalTrials.gov study NCT02393924. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Evaluation of Usability and Human Factors in the Novus System

ClinicalTrials.gov study NCT02738242. IPD Sharing: NO. Countries: 1. Publications: 5.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Factors Influencing the Composition of Human Milk

ClinicalTrials.gov study NCT04382989. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record