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4,563 results for “correlations”
Correlations between a Shintergy synchronized brain and a laser eld; a possible fractal structure of Consciousness (Part I of 7 – Local measure in time and space).
<p>Data set from Correlations between a Shintergy synchronized brain and a laser eld; a possible fractal structure of Consciousness (Part I of 7 – Local measure in time and space), and figures.</p>
Internal climate variability and spatial temperature correlations during the past 2000 years
<p>Climate model output of the iLOVECLIM model. The repository contains:</p> <p>Data on 9 ensemble members corresponding to ensemble members 1-9 in the publication:</p> <p>1: 0ka_trans_013000to015000.nc</p> <p>2: 0ka_trans_precipcorr_AC_x0.4_AS_x1.6_013000to015000.nc</p> <p>3: 0ka_trans_7params_6_013000to015000.nc</p> <p>4: 0ka_trans_7params_12_013000to015000.nc</p> <p>5: 0ka_trans_7params_30_013000to015000.nc</p> <p>6: 0ka_trans_8params_6_013000to015000.nc</p> <p>7: 0ka_trans_8params_26_013000to015000.nc</p> <p>8: 0ka_trans_8params_35_013000to015000.nc</p> <p>9: 0ka_trans_8params_40_013000to015000.nc</p> <p> </p> <p>Three different data files for every ensemble member</p> <p>atmym: yearly mean atmospheric output (t2m is used for temperature in the manuscript)</p> <p>CLIO2: yearly mean ocean surface output (temp is used for SST in the manuscript)</p> <p>graevolu: collection of monthly mean 1 dimensional ocean outputs (ADPro is used for AMOC strength in the manuscript)</p>
Data and code repository for Science Advances submission: Uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
<p>Data and codes related to the findings reported in the manuscript, "Uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy", are deposited. Please refer to the notes located within each folder for further descriptions.</p>
Correlated k coefficients for H2-He atmospheres; 196 spectral windows and 1060 pressure-temperature points
<p>There are 72 correlated k-coefficients datasets, using the naming convention m-xxx_coyyy.data.196.tar.zip, where xxx is the metallicity in dex relative to solar, and yyy is the C/O ratio relative to solar, as a multiplication factor. For example a metallicity of 0.0 and a C/O ratio of 1.0 indicates solar abundances. There are an additional 5 datasets that do not include the TiO and VO opacities, as indicated by the "_noTiOVO" designation in the file name. We use the Lodders et al. 2010 value for the solar C/O=0.458. The spectral windows are listed in the file 196_windows.txt (intervals defined as starting at lambda1 and ending at lambda2), and the k-coefficients can be read in and checked using the script in the IDL code read_k_coefficients.pro. The k-coefficients are calculated for a grid of 1060 pressure-temperature points listed in the file PT_list_1060.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, where the abundances for each metallicity-C/O combination have been calculated using equilibrium chemistry, as described in Marley et al. 2021. There are 12 Fe/H values: 0.0, 0.5, 0.7, 1.0, 1.5, 1.5, 1.7, 2.0, -0.25, -0.3, -0.5, -0.75, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5.</p> <p> The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, FeH, H2O, H2S, HCN, LiCl, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The references for the line lists and broadening parameters used in these opacity calculations can also be found in Marley et al 2021, and are included here for convenience in the file Table_2_Marley_et.al.2021.png</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>cp_all: contains the mean molecular weight for each layer. The head capacity values do not include the proper H2 heat capacity and should not be used.</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1060-point pressure-temperature grid.</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_cia: relative abundances for the species that could be used for calculating collision-induced absorption (CIA)</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Correlated k coefficients for H2-He atmospheres; 11 spectral windows and 1060 pressure-temperature points
<p>There are 72 correlated k-coefficients datasets, using the naming convention m-xxx_coyyy.data.11.tar.zip, where xxx is the metallicity in dex relative to solar, and yyy is the C/O ratio relative to solar, as a multiplication factor. For example a metallicity of 0.0 and a C/O ratio of 1.0 indicates solar abundances. There are an additional 10 datasets that do not include the TiO and VO opacities, as indicated by the "_noTiOVO" designation in the file name. We use the Lodders et al. 2010 value for the solar C/O=0.458. The spectral windows are listed in the file 11_windows.txt (intervals defined as starting at lambda1 and ending at lambda2), and the k-coefficients can be read in and checked using the script in the IDL code read_k_coefficients.pro. The k-coefficients are calculated for a grid of 1060 pressure-temperature points listed in the file PT_list_1060.</p> <p>The correlated-k coefficients are calculated using pre-mixed opacities, where the abundances for each metallicity-C/O combination have been calculated using equilibrium chemistry, as described in Marley et al. 2021. There are 12 Fe/H values: 0.0, 0.5, 0.7, 1.0, 1.5, 1.5, 1.7, 2.0, -0.25, -0.3, -0.5, -0.75, and -1.0; and 6 C/O values: 0.25, 0.5, 1.0, 1.5, 2.0 and 2.5.</p> <p> The opacity sources included in the calculations are: C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, FeH, H2O, H2S, HCN, LiCl, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The references for the line lists and broadening parameters used in these opacity calculations can also be found in Marley et al 2021, and are included here for convenience in the file Table_2_Marley_et.al.2021.png</p> <p>Each dataset contains the following files:</p> <p>ascii_data: the correlated k coefficients file in ascii format. This can be read by the included IDL code.</p> <p>binary_data: the correlated k coefficients file in binary format</p> <p>cp_all: contains the mean molecular weight for each layer. The head capacity values do not include the proper H2 heat capacity and should not be used.</p> <p>full_abunds: the relative abundances for all the species from the chemistry files, on the 1060-point pressure-temperature grid.</p> <p>sum_in_atoms: relative abundances for the alkali metals</p> <p>sum_in_cia: relative abundances for the species that could be used for calculating collision-induced absorption (CIA)</p> <p>sum_in_layer: relative abundances for all molecules included in the correlated k-coefficients calculations</p> <p><em>Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.</em></p>
Evidence for Correlations Between BMI-Associated SNPs and circRNAs
<p><strong>The datasets provided here are part of the study "Evidence for Correlations Between BMI-Associated SNPs and circRNAs" by Rajcsanyi et al.</strong></p> <p><strong>Abstract of the study:</strong></p> <p>Circular RNAs (circRNAs) are regulators of processes like adipogenesis. Their expression can be modulated by SNPs. We analysed links between BMI-associated SNPs and circRNAs. First, we detected an enrichment of BMI-associated SNPs on circRNA genomic loci in comparison to non-significant variants. Analysis of sex-stratified GWAS data revealed that circRNA genomic loci encompassed more genome-wide significant BMI-SNPs in females than in males. To explore if the enrichment is restricted to BMI, we investigated nine additional GWAS studies. We showed an enrichment of trait-associated SNPs in circRNAs for four analysed phenotypes (body height, chronic kidney disease, anorexia nervosa and autism spectrum disorder). To analyse the influence of BMI-affecting SNPs on circRNA levels in vitro, we examined rs4752856 located on hsa_circ_0022025. The analysis of heterozygous individuals revealed an increased level of circRNA derived from the BMI-increasing SNP allele. We conclude that genetic variation may affect the BMI partly through circRNAs.</p> <p><strong>Information regarding the datasets:</strong></p> <p>The data provided represents the analysed as well as generated data throughout the study. For further information about the datasets used, processed and generated, please see the study by Rajcsanyi et al.</p> <p><strong>circRNA datasets:</strong></p> <p>The analysed circRNA datasets were extracted from four circRNA databases (circAtlas v2.0, circBase, CIRCpediaV2 and circVAR) and were further processed to exclude internal duplicates and circRNAs derived from sex chromosomes. These original datasets have been downloaded from the following websites:</p> <p><em>circAtlas v2.0: http://159.226.67.237:8080/new/links.php</em></p> <p><em>circBase: http://www.circbase.org/cgi-bin/downloads.cgi</em></p> <p><em>CIRCpediaV2: http://yang-laboratory.com/circpedia/download</em></p> <p><em>circVAR: http://soft.bioinfo-minzhao.org/circvar/</em></p> <p><strong>GWAS datasets:</strong></p> <p>The original genome-wide association study (GWAS) summary statistics dataset of the BMI GWAS by Yengo et al. (2018) were classified into significant (P < 5*10<sup>-8</sup>) and non-significant (P >= 5*10<sup>-8</sup>) SNPs. A subsequent sensitivty analysis adjusted the P-value threshold of the non-significant SNPs to either P >= 5*10<sup>-5</sup>, P >= 5*10<sup>-6</sup> or 5*10<sup>-7</sup>.<br> Please note that these datasets are not provided in this repository, as these were solely classified and divided based on the SNPs' P-value. The same applied for all additional GWAS data solely divided based on the P-value (GWAS data for Anorexia nervosa, Autism spectrum disorder, etc.). The original and complete summary statistcs data can be obtained in the stated references below for each GWAS. Yet, the datasets generated for an approximation of the linkage disequilibrium based on the GWAS data by Yengo et al. (2018, BMI) are provided in this repository.<br> <br> <em>BMI and body height: Yengo et al. (2018)</em></p> <p><em>BMI sex-stratified: Pulit et al. (2019)</em></p> <p><em>Anorexia nervosa: Watson et al. (2018)</em></p> <p><em>Amyotropic lateral scerlosis: Iacoangeli et al. (2020)</em></p> <p><em>Autism spectrum disorder: Grove et al. (2019)</em></p> <p><em>Chronic kidney disease: Wuttke et al. 2019</em></p> <p><em>Epilepsy: ILAE consortium et al. 2018</em></p> <p><em>Heart Failure: Shah et al. 2020</em></p> <p><em>Pernicious anemia: Glanville et al. 2021</em></p> <p><em>Ulcerative Colitis: de Lange et al. 2017</em></p> <p><strong>Generated data:</strong></p> <p>The unprocessed output data of the study produced by the custom R script is provided here. Please note that the amount of information (rsID, P-value, Beta-value, allele frequency, circRNA_ID, circRNA strand, etc.) can vary between the output files due to differences in the data included in each circRNA and GWAS dataset. These dataset represent the raw and thus unprocessed output data. The results/counts presented in the study were obtained by further processing these output files. Further, the data produced by the SNaPshot assay are provided as well.</p>
Data of FigS2, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of FigS2, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_FigS2.PNG). The corresponding raw data and subsequent data analysis obtained from proteomics analysis are provided as nine files in CSV format (31003A-179400_10.3390-cancers14133074_SS_SA_DHRS7_5_1-3_M1-3.csv). All further experiment related information provided as one meta-data-file (31003A-179400_10.3390-cancers14133074_SS_SA_DHRS7_5_1_M .txt) in txt format.</p>
Data of FigS4, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of FigS4, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_FigS4.PNG). The Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_6_M1.pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_6_M.txt) and three files in CSV-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_6_1-3.csv).</p>
Data of Fig7, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig7, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig7.PNG). The Corresponding raw data and subsequent data analysis obtained for TCGA analysis contains one file in txt-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_1_M.txt), and all further related information provided as one meta-data-file in pdf-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_1_M1.pdf)</p> <p> </p>
Data of Fig8, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig8, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig8.PNG). The Corresponding raw data and subsequent data analysis obtained for immunohistochemistry contains one file in txt-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_12_1_M .txt) and one file in csv-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_12_1.csv), and all further related information provided as one meta-data-file in pdf-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_12_1_M1 .pdf)</p> <p> </p>
Data of Fig4, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig4, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig4.PNG). The Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_3_M_1.pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_3_M.txt). Corresponding raw data and subsequent data analysis obtained from RT-PCR analysis provided as one files in TXT format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_4_M.txt), all further experiment related information provided as one meta-data-file in pdf format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_4_M_1.pdf).</p>
Data of Fig2, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig2, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig2.PNG). The corresponding raw data and subsequent data analysis obtained from proteomics analysis are provided as three files in CSV format (31003A-179400_10.3390-cancers14133074_SS_SA_DHRS7_5_1-3.csv). All further experiment related information provided as one meta-data-file (31003A-179400_10.3390-cancers14133074_SS_SA_DHRS7_5_1_M .txt) in txt format. Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_1_M_1 .pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_1_M.txt). Corresponding raw data and subsequent data analysis obtained from RT-PCR analysis provided as one files in TXT format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_2_M.txt), all further experiment related information provided as one meta-data-file in pdf format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_2_M_1.pdf).</p>
Data of Fig5, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig5, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig5.PNG). The Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_4_M_1.pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_4_M.txt) and three files in CSV-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_4_3.csv). Corresponding raw data and subsequent data analysis obtained from RT-PCR analysis provided as one files in TXT format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_5_M .txt) and three files in CSV format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_5-1-3.csv), all further experiment related information provided as three meta-data-files in pdf format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_5_M_1-3.pdf).</p>
Data of Fig6, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig6, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig6.PNG). The Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_5_M1.pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_5_M.txt) and three files in CSV-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_5_1-3.csv).</p> <p> </p>
Data of Fig3, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig3, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig3.PNG). The Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_2_M_1.pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_2_M.txt). Corresponding raw data and subsequent data analysis obtained from RT-PCR analysis provided as one files in TXT format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_3_M.txt), all further experiment related information provided as one meta-data-file in pdf format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_3_M_1.pdf).</p>
Data of Fig1, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig1, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (doi: 10.3390/cancers14133074) contains the original figures as PNG-format (10.3390-cancers14133074_Fig1.PNG). Raw data and related Meta data are provides as one file in TXT format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_1_M.txt) and one file in PDF-Format (31003A-179400_10.3390-cancers14133074_SSDHRS7_1_1_M_1.pdf).</p>
Data of Fig9, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of Fig9, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_Fig9.PNG). The Corresponding raw data and subsequent data analysis obtained for immunohistochemistry contains one file in txt-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_12_1_M.pdf) and one file in csv-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_12_1.csv), and all further related information provided as one meta-data-file in pdf-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_1_M .txt)</p> <p> </p>
Data of FigS3, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of FigS3, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_FigS3.PNG). The Corresponding raw data and subsequent data analysis obtained for TCGA analysis contains one file in txt-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_3_M .txt), six files in csv-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_3-1-6 .csv) and one file in sps-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_3-4 .sps). All further related information provided as one meta-data-file in pdf-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_2_M 1.pdf).</p>
Data of FigS5, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of FigS5, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_FigS5.PNG). The Corresponding raw data and subsequent data analysis obtained from western blot analysis contains the original figures of the raw blots and antibody dilutions as PDF-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_7_M1.pdf), data analysis (densitometry) and all further experiment related information provided as one meta-data-file in txt format (31003A-179400_10.3390-cancers14133074_SSDHRS7_2_7_M.txt).</p> <p> </p>
Data of FigS6, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of FigS6, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_FigS6.PNG). The Corresponding raw data and subsequent data analysis obtained for TCGA analysis contains two files in txt-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_1-2_M.txt). All further related information provided as one meta-data-file in pdf-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_1_M1.pdf).</p> <p> </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.