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318 results for “MDD”
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal density of Lepomis in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal density of Lepomis measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal density of Lepomis gulosus in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal density of Lepomis gulosus measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal density of Lepomis marginatus in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal density of Lepomis marginatus measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal density of Lepomis punctatus in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal density of Lepomis punctatus measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal density of Elassoma evergladei in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal density of Elassoma evergladei measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal density of Cichlasoma urophthalma in units of numberPerMeterSquared on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal density of Cichlasoma urophthalma measurements in numberPerMeterSquared units and were aggregated to a yearly timescale.
Florida Coastal Everglades site, station Taylor Slough Trexler Site MDD, study of animal species richness of Osteichthyes in units of number on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Florida Coastal Everglades (FCE) contains animal species richness of Osteichthyes measurements in number units and were aggregated to a yearly timescale.
Data and code for Fitzgerald et al: MDD seeded co-expression networks
<p>Below is a decription of the data and code supplied within this repository related to Fitzgerald et al "Astrocyte fatty acid metabolism as a driver of risk for major depressive disorder"</p> <table> <tbody> <tr> <td>Generated data </td> </tr> <tr> <td>Data</td> <td>About</td> <td> </td> </tr> <tr> <td>All_GTEx_DLPFC_networks.RData</td> <td>Non-thresholded coexpression summary statistics for MDD risk genes in GTEx frontal cortex</td> <td> </td> </tr> <tr> <td>my_big_negative_GTEx_DLPFC_list.RData</td> <td>"All_GTEx_DLPFC_networks.Rdata" data filtered to those genes with R < -0.5 and FDR < 0.05</td> <td> </td> </tr> <tr> <td>my_big_positive_GTEx_DLPFC_list.RData</td> <td>"All_GTEx_DLPFC_networks.Rdata" data filtered to those genes with R > 0.5 and FDR < 0.05</td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>Generated code</td> </tr> <tr> <td>File</td> <td>About</td> <td>Related figure</td> </tr> <tr> <td>Chang_bootstrap.R</td> <td>Bootstrapping of coexpression networks in the Chang et all data for comparing FADS1 coexpressed genes across disease states</td> <td>Fig 4G</td> </tr> <tr> <td>CMC_QC.R</td> <td>Quality control for the common mind consortium data for validation of coexpression networks</td> <td>Supp</td> </tr> <tr> <td>Cont_vs_MDD_modscores.R</td> <td>Generating module scores in snRNA-seq data</td> <td>Fig 4E</td> </tr> <tr> <td>FADS1_clustering.R</td> <td>Clustering of snRNA-seq data using genes coexpressed with FADS1</td> <td>Fig 5</td> </tr> <tr> <td>gene_analysis.sh</td> <td>Annotation of GWAS summary statistics using Hi-C data</td> <td>Fig 2A</td> </tr> <tr> <td>gene_set_analysis.sh</td> <td>GWAS enrichment analysis using MAGMA</td> <td>Fig 6C</td> </tr> <tr> <td>GTEx_coexp_networks.R</td> <td>Generating seeded coexpression networks for MDD risk genes in the GTEx dataset</td> <td>Fig 2B</td> </tr> <tr> <td>GTEx_QC_1.R</td> <td>Filtering of the GTEx dataset</td> <td>NA</td> </tr> <tr> <td>GTEx_QC_2.R</td> <td>Normalisation and regression of technical covariates from the GTEx data</td> <td>NA</td> </tr> <tr> <td>Labonte_et_al_QC.R</td> <td>Quality control, filtering and regression of technical covariates from the Labonte et al dataset</td> <td>Fig 4F</td> </tr> <tr> <td>Milo_analysis.R</td> <td>Neighbourhood based analysis for differentially abundant nuclei between control and MDD nuclei</td> <td>Fig 5H</td> </tr> <tr> <td>Nagy_et_al_astro_subsetting.R</td> <td>Subsetting astrocytes from the full Nagy et al snRNA-seq dataset </td> <td>NA</td> </tr> <tr> <td>Network_analysis.R</td> <td>To generate and analyse a graph of coexpression networks</td> <td>Fig 3E</td> </tr> <tr> <td>NicheNet.R</td> <td>For a NicheNet analysis to infer patterns of cell-cell communication</td> <td>Fig 6F</td> </tr> <tr> <td>Vizium_analysis.R</td> <td>Processing spatial RNA-seq data and generating cell scores for spatial inference of identified cell states</td> <td>Fig 5F</td> </tr> </tbody> </table>
MDD-Molecular Dynamics Dataset: Collection of protein-ligand complex simulations
<p>Dataset is part of the paper: https://chemrxiv.org/engage/chemrxiv/article-details/664c73f6418a5379b0de8152.</p> <p>This dataset consists of molecular dynamics (MD) simulations of 862 unique protein-ligand complexes, covering a wide range of protein families and diverse chemical classes of ligands. It is derived from publicly available repositories and represents the largest single source of MD simulations to date.</p> <p>All protein-ligand complexes included in the dataset were prepared following a standardized protocol. Missing atoms in the protein structures were added using the PDBFixer tool. The protein targets were parameterized using the AMBER99SB-ILDN force field, while ligands were parameterized with the ANTECHAMBER module within the ACPYPE tool. Ligand partial charges were determined to match the quantum-mechanically generated electrostatic potential via the Restrained Electrostatic Potential (RESP) method, and the remaining parameters were set using the GAFF2 force field. The molecular dynamics simulations were performed using GROMACS. The simulations were configured in a cubic simulation box with periodic boundary conditions and employed a TIP3P water model within an electrostatically neutral environment. The simulation protocol included an initial minimization cycle, followed by temperature equilibration in the NVT ensemble and pressure equilibration in the NPT ensemble. Production simulations were conducted over a period of 200 ns, with a timestep of 100 ps.</p> <p>Constructing a large, representative set of MD simulations poses challenges due to the high computational costs and complexities associated with preparing molecular systems. Moreover, given the limited number of suitable training examples (complexes) and the large volume of MD data from each simulation, careful filtering and feature selection are crucial. This dataset is valuable for exploring how molecular dynamics simulation data can be integrated with protein-ligand binding affinity prediction tasks, an essential component of in silico drug discovery pipelines. MD simulations, in particular, offer a dynamic view by illustrating the temporal interactions within protein-ligand complexes, potentially providing additional insights for affinity and specificity estimates.</p>
Publication analysis on MDD
<p>Supplementary material 1: original data of MDD publication, Supplementary material 2: python code for analysis.</p>
Cortical Excitability and Inhibition in MDD
ClinicalTrials.gov study NCT01718730. IPD Sharing: NO. Countries: 1. Publications: 1.
Effectiveness Study of Scopolamine Combined With Escitalopram in Patients With MDD
ClinicalTrials.gov study NCT03131050. IPD Sharing: NO. Countries: 1. Publications: 3.
IV Ketamine Vs. in Esketamine for MDD TRD
ClinicalTrials.gov study NCT06488586. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Acupoint Thermal Radiation Characteristics in Adolescents with MDD
ClinicalTrials.gov study NCT06750640. IPD Sharing: NO. Countries: 1. Publications: 0.
Home-based Transcranial Direct Current Stimulation (tDCS) for Major Depressive Disorders (MDD)
ClinicalTrials.gov study NCT05205915. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Study Comparing Discontinuation Symptoms Of DVS SR In Subjects With Major Depressive Disorder (MDD)
ClinicalTrials.gov study NCT01056289. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Behavioral Activation + Cognitive Processing Therapy for PTSD and Comorbid MDD
ClinicalTrials.gov study NCT02874131. IPD Sharing: NO. Countries: 1. Publications: 5.
Movement for Depression - An RCT Assessing the Effects of Physical Activity Promotion for People With MDD
ClinicalTrials.gov study NCT03403881. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Transcranial Direct Current Stimulation (tDCS) in the Treatment of Major Depressive Disorder (MDD)
ClinicalTrials.gov study NCT01078948. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Efficacy of H7-Coil DTMS Compared to H1-Coil DTMS in Subjects With Major Depression Disorder (MDD)
ClinicalTrials.gov study NCT03012724. IPD Sharing: Not stated. Countries: 3. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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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.