cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17045/sthlmuni.7324898
title: Open data: Visual load does not decrease the auditory steady state response to 40-Hz amplitude-modulated tones

description: Open data: Visual load does not decrease the auditory steady state response to 40-Hz amplitude-modulated tones<br>The main results files are saved separately:<br>- ASSR_study1.html: R output of the main analyses- ASSR_study1_subset_subjects.html: R output of the main analyses- ASSR_study2.html: R output of the main analyses<br>The studies were preregistered:Study 1: https://doi.org/10.17605/OSF.IO/UYJVAStudy 2: https://doi.org/10.17605/OSF.IO/JVMFD<br><b>DATA & FILE OVERVIEW</b><br>File List:The files contain the raw data, scripts, and results of main and supplementary analyses of two electroencephalography (EEG) studies (Study1, Study2). Links to the hardware and software are provided under methodological information.<br>ASSR_study1_experiment_scripts.zip: contains the Python files to run the experiment. <br>ASSR_study1_rawdata.zip: contains raw datafiles for each subject<br>- data_EEG: EEG data in bdf format (generated by Biosemi)- data_log: logfiles of the EEG session (generated by Python)- data_WMC: logfiles of the working memory capacity task (generated by Python)<br>ASSR_study1_EEG_scripts.zip: Python-MNE scripts to process the EEG data<br>ASSR_study1_EEG_preprocessed.zip: Preprocessed EEG data from Python-MNE<br>ASSR_study1_analysis_scripts.zip: R scripts to analyze the data together with the main datafiles. The main files in the folder are: <br>- ASSR_study1.html: R output of the main analyses- ASSR_study1_subset_subjects.html: R output of the main analyses but after excluding five subjects who were excluded because of stricter, preregistered artifact rejection criteria<br>ASSR_study1_figures.zip: contains all figures and tables that are created by Python-MNE and R.<br>ASSR_study2_experiment_scripts.zip: contains the Python files to run the experiment<br>ASSR_study2_rawdata.zip: contains raw datafiles for each subject<br>- data_EEG: EEG data in bdf format (generated by Biosemi)- data_log: logfiles of the EEG session (generated by Python)- data_WMC: logfiles of the working memory capacity task (generated by Python)<br>ASSR_study2_EEG_scripts.zip: Python-MNE scripts to process the EEG data<br>ASSR_study2_EEG_preprocessed.zip: Preprocessed EEG data from Python-MNE<br>ASSR_study2_analysis_scripts.zip: R scripts to analyze the data together with the main datafiles. The main files in the folder are:<br>- ASSR_study2.html: R output of the main analyses- ASSR_compare_performance_between_studies.html: R output of analyses that compare behavioral performance between study 1 and study 2.<br>ASSR_study2_figures.zip: contains all figures and tables that are created by Python-MNE and R.<br><b>Instrument- or software-specific information needed to interpret the data:</b>MNE-Python (Gramfort A., et al., 2013): https://mne.tools/stable/index.html#Rstudio used with R (R Core Team, 2016): https://rstudio.com/products/rstudio/Wiens, S. (2017). Aladins Bayes Factor in R (Version 3). https://www.doi.org/10.17045/sthlmuni.4981154.v3<br><br><br><br>
DOI: 10.17045/sthlmuni.7324898.v1
title: Open data: Visual load does not decrease the auditory steady state response to 40-Hz amplitude-modulated tones

description: Open data: Visual load does not decrease the auditory steady state response to 40-Hz amplitude-modulated tones<br>The main results files are saved separately:<br>- ASSR_study1.html: R output of the main analyses- ASSR_study1_subset_subjects.html: R output of the main analyses- ASSR_study2.html: R output of the main analyses<br>The studies were preregistered:Study 1: https://doi.org/10.17605/OSF.IO/UYJVAStudy 2: https://doi.org/10.17605/OSF.IO/JVMFD<br><b>DATA & FILE OVERVIEW</b><br>File List:The files contain the raw data, scripts, and results of main and supplementary analyses of two electroencephalography (EEG) studies (Study1, Study2). Links to the hardware and software are provided under methodological information.<br>ASSR_study1_experiment_scripts.zip: contains the Python files to run the experiment. <br>ASSR_study1_rawdata.zip: contains raw datafiles for each subject<br>- data_EEG: EEG data in bdf format (generated by Biosemi)- data_log: logfiles of the EEG session (generated by Python)- data_WMC: logfiles of the working memory capacity task (generated by Python)<br>ASSR_study1_EEG_scripts.zip: Python-MNE scripts to process the EEG data<br>ASSR_study1_EEG_preprocessed.zip: Preprocessed EEG data from Python-MNE<br>ASSR_study1_analysis_scripts.zip: R scripts to analyze the data together with the main datafiles. The main files in the folder are: <br>- ASSR_study1.html: R output of the main analyses- ASSR_study1_subset_subjects.html: R output of the main analyses but after excluding five subjects who were excluded because of stricter, preregistered artifact rejection criteria<br>ASSR_study1_figures.zip: contains all figures and tables that are created by Python-MNE and R.<br>ASSR_study2_experiment_scripts.zip: contains the Python files to run the experiment<br>ASSR_study2_rawdata.zip: contains raw datafiles for each subject<br>- data_EEG: EEG data in bdf format (generated by Biosemi)- data_log: logfiles of the EEG session (generated by Python)- data_WMC: logfiles of the working memory capacity task (generated by Python)<br>ASSR_study2_EEG_scripts.zip: Python-MNE scripts to process the EEG data<br>ASSR_study2_EEG_preprocessed.zip: Preprocessed EEG data from Python-MNE<br>ASSR_study2_analysis_scripts.zip: R scripts to analyze the data together with the main datafiles. The main files in the folder are:<br>- ASSR_study2.html: R output of the main analyses- ASSR_compare_performance_between_studies.html: R output of analyses that compare behavioral performance between study 1 and study 2.<br>ASSR_study2_figures.zip: contains all figures and tables that are created by Python-MNE and R.<br><b>Instrument- or software-specific information needed to interpret the data:</b>MNE-Python (Gramfort A., et al., 2013): https://mne.tools/stable/index.html#Rstudio used with R (R Core Team, 2016): https://rstudio.com/products/rstudio/Wiens, S. (2017). Aladins Bayes Factor in R (Version 3). https://www.doi.org/10.17045/sthlmuni.4981154.v3<br><br><br><br>
DOI: 10.6084/m9.figshare.12737625
title: Additional file 8 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 8. Table 3. Venn-diagram related genes.
DOI: 10.6084/m9.figshare.12737628
title: Additional file 9 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 9. Table 4. List of DEG.
DOI: 10.6084/m9.figshare.12737625.v1
title: Additional file 8 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 8. Table 3. Venn-diagram related genes.
DOI: 10.6084/m9.figshare.12737619
title: Additional file 6 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 6. Table 1. Maaslin Analysis Output (H2O Group for Genotype Comparison).
DOI: 10.6084/m9.figshare.12737622
title: Additional file 7 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 7. Table 2. Maaslin Analysis Output (ABX Groups for Genotype Comparison).
DOI: 10.6084/m9.figshare.12737628.v1
title: Additional file 9 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 9. Table 4. List of DEG.
DOI: 10.6084/m9.figshare.12737622.v1
title: Additional file 7 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 7. Table 2. Maaslin Analysis Output (ABX Groups for Genotype Comparison).
DOI: 10.6084/m9.figshare.12737619.v1
title: Additional file 6 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 6. Table 1. Maaslin Analysis Output (H2O Group for Genotype Comparison).
DOI: 10.6084/m9.figshare.12737601
title: Additional file 12 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 12. Table 7. Pathway analysis ABX FAD vs WT.
DOI: 10.6084/m9.figshare.12737598
title: Additional file 11 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 11. Table 6. Pathway analysis GF FAD vs WT.
DOI: 10.6084/m9.figshare.12737601.v1
title: Additional file 12 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 12. Table 7. Pathway analysis ABX FAD vs WT.
DOI: 10.6084/m9.figshare.12737595
title: Additional file 10 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 10. Table 5. Pathway analysis SPF FAD vs WT.
DOI: 10.6084/m9.figshare.12737598.v1
title: Additional file 11 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 11. Table 6. Pathway analysis GF FAD vs WT.
DOI: 10.6084/m9.figshare.12737591
title: Additional file 3 of Nuclear proteome of virus-infected and healthy potato leaves

description: Additional file 3: Table S3. Proteins detected only in the nucleus of healthy potato leaves.
DOI: 10.6084/m9.figshare.12737595.v1
title: Additional file 10 of Different effects of constitutive and induced microbiota modulation on microglia in a mouse model of Alzheimer’s disease

description: Additional file 10. Table 5. Pathway analysis SPF FAD vs WT.
DOI: 10.6084/m9.figshare.12737588
title: Additional file 2 of Nuclear proteome of virus-infected and healthy potato leaves

description: Additional file 2: Table S2. Proteins detected only in the nucleus of PVA-infected potato leaves.
DOI: 10.6084/m9.figshare.12737591.v1
title: Additional file 3 of Nuclear proteome of virus-infected and healthy potato leaves

description: Additional file 3: Table S3. Proteins detected only in the nucleus of healthy potato leaves.
DOI: 10.6084/m9.figshare.12737585
title: Additional file 1 of Nuclear proteome of virus-infected and healthy potato leaves

description: Additional file 1: Table S1. Proteins found in the nucleus of cells of healthy leaves from potato lines v2–108.
DOI: 10.6084/m9.figshare.12737588.v1
title: Additional file 2 of Nuclear proteome of virus-infected and healthy potato leaves

description: Additional file 2: Table S2. Proteins detected only in the nucleus of PVA-infected potato leaves.
DOI: 10.6084/m9.figshare.12737585.v1
title: Additional file 1 of Nuclear proteome of virus-infected and healthy potato leaves

description: Additional file 1: Table S1. Proteins found in the nucleus of cells of healthy leaves from potato lines v2–108.
DOI: 10.6084/m9.figshare.12737526
title: Additional file 2 of The influence of developmental diet on reproduction and metabolism in Drosophila

description: Additional file 2. Data. Data generated and analysed during this study.
DOI: 10.6084/m9.figshare.12737526.v1
title: Additional file 2 of The influence of developmental diet on reproduction and metabolism in Drosophila

description: Additional file 2. Data. Data generated and analysed during this study.
DOI: 10.6084/m9.figshare.12737453
title: Additional file 3 of Early administration of glucocorticoid for thyroid storm: analysis of a national administrative database

description: Additional file 3 : Supplemental Figure 3. Posterior density distribution of each coefficient of regression model (A) Regression coefficient at the level of patient, (B) Regression coefficient at the level of hospitals.
DOI: 10.6084/m9.figshare.12737453.v1
title: Additional file 3 of Early administration of glucocorticoid for thyroid storm: analysis of a national administrative database

description: Additional file 3 : Supplemental Figure 3. Posterior density distribution of each coefficient of regression model (A) Regression coefficient at the level of patient, (B) Regression coefficient at the level of hospitals.
DOI: 10.6084/m9.figshare.12737345
title: Additional file 5 of Genomic diversity and population structure of the indigenous Greek and Cypriot cattle populations

description: Additional file 5: Table S4. Genetic differentiation index. Pairwise values for DEST, per analyzed breed. Maximum and minimum values within each of the predefined geographical groups are depicted in bold letters in gray rectangle. Maximum and minimum values considering all 115 breeds are in bold letters in green and yellow, respectively.
DOI: 10.6084/m9.figshare.12737345.v1
title: Additional file 5 of Genomic diversity and population structure of the indigenous Greek and Cypriot cattle populations

description: Additional file 5: Table S4. Genetic differentiation index. Pairwise values for DEST, per analyzed breed. Maximum and minimum values within each of the predefined geographical groups are depicted in bold letters in gray rectangle. Maximum and minimum values considering all 115 breeds are in bold letters in green and yellow, respectively.
DOI: 10.6084/m9.figshare.12737285
title: Additional file 3 of A comparative study on normal and obese mice indicates that the secretome of mesenchymal stromal cells is influenced by tissue environment and physiopathological conditions

description: Additional file 2. List of proteins identified in MSC secretome. “ND HFD tech biol replicates” spreadsheet: The sheet shows the list of proteins found in vWAT-MSCs, sWAT-MSCs, and BM-MSCs isolated from samples taken from ND-treated mice designated as 1, 2, and 3 and from HFD-treated mice designated as 4, 5, and 6. For each biological sample, there were two technical replicates (A, B). Proteins were listed with their UniProt identifiers. “ND HFD common data” spreadsheet: The proteins secreted by vWAT-MSCs isolated from samples taken from mouse 1, 2, and 3 were analyzed with a Venn graph to find common data. The procedure was also performed for sWAT-MSCs and BM-MSCs. The sheet also lists proteins isolated from samples taken from mice 4, 5, and 6, which were analyzed with the same method. “Venn comparison in ND or HFD” spreadsheet: The sheet shows the result of Venn diagram comparison among vWAT-MSCs, sWAT-MSCs, and BM-MSCs coming from ND- and HFD-treated mice. “Venn comparison in ND vs. HFD” spreadsheet: The sheet shows the result of Venn diagram comparison of vWAT-MSCs from ND-treated mice versus vWAT-MSCs from HFD-treated mice. The same procedure was employed for sWAT-MSCs and BM-MSCs.
DOI: 10.6084/m9.figshare.12737285.v1
title: Additional file 3 of A comparative study on normal and obese mice indicates that the secretome of mesenchymal stromal cells is influenced by tissue environment and physiopathological conditions

description: Additional file 2. List of proteins identified in MSC secretome. “ND HFD tech biol replicates” spreadsheet: The sheet shows the list of proteins found in vWAT-MSCs, sWAT-MSCs, and BM-MSCs isolated from samples taken from ND-treated mice designated as 1, 2, and 3 and from HFD-treated mice designated as 4, 5, and 6. For each biological sample, there were two technical replicates (A, B). Proteins were listed with their UniProt identifiers. “ND HFD common data” spreadsheet: The proteins secreted by vWAT-MSCs isolated from samples taken from mouse 1, 2, and 3 were analyzed with a Venn graph to find common data. The procedure was also performed for sWAT-MSCs and BM-MSCs. The sheet also lists proteins isolated from samples taken from mice 4, 5, and 6, which were analyzed with the same method. “Venn comparison in ND or HFD” spreadsheet: The sheet shows the result of Venn diagram comparison among vWAT-MSCs, sWAT-MSCs, and BM-MSCs coming from ND- and HFD-treated mice. “Venn comparison in ND vs. HFD” spreadsheet: The sheet shows the result of Venn diagram comparison of vWAT-MSCs from ND-treated mice versus vWAT-MSCs from HFD-treated mice. The same procedure was employed for sWAT-MSCs and BM-MSCs.
DOI: 10.6084/m9.figshare.12737250
title: Additional file 8 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 8: Table S7. Fusion transcripts.
DOI: 10.6084/m9.figshare.12737253
title: Additional file 9 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 9: Table S8. Druggable genes.
DOI: 10.6084/m9.figshare.12737244
title: Additional file 6 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 6: Table S5. RNA-seq in spinal tumors.
DOI: 10.6084/m9.figshare.12737247
title: Additional file 7 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 7: Table S6. CIS genes.
DOI: 10.6084/m9.figshare.12737241
title: Additional file 5 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 5: Table S4. RNA-seq in brain tumors.
DOI: 10.6084/m9.figshare.12737250.v2
title: Additional file 8 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 8: Table S7. Fusion transcripts.
DOI: 10.6084/m9.figshare.12737253.v2
title: Additional file 9 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 9: Table S8. Druggable genes.
DOI: 10.6084/m9.figshare.12737244.v2
title: Additional file 6 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 6: Table S5. RNA-seq in spinal tumors.
DOI: 10.6084/m9.figshare.12737247.v2
title: Additional file 7 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 7: Table S6. CIS genes.
DOI: 10.6084/m9.figshare.12737250.v1
title: Additional file 8 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 8: Table S7. Fusion transcripts.
DOI: 10.6084/m9.figshare.12737241.v2
title: Additional file 5 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 5: Table S4. RNA-seq in brain tumors.
DOI: 10.6084/m9.figshare.12737247.v1
title: Additional file 7 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 7: Table S6. CIS genes.
DOI: 10.6084/m9.figshare.12737253.v1
title: Additional file 9 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 9: Table S8. Druggable genes.
DOI: 10.6084/m9.figshare.12737238
title: Additional file 4 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 4: Table S3. Significant deletions.
DOI: 10.6084/m9.figshare.12737241.v1
title: Additional file 5 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 5: Table S4. RNA-seq in brain tumors.
DOI: 10.6084/m9.figshare.12737235
title: Additional file 3 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 3: Table S2. Significantly Mutated Genes.
DOI: 10.6084/m9.figshare.12737244.v1
title: Additional file 6 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 6: Table S5. RNA-seq in spinal tumors.
DOI: 10.6084/m9.figshare.12737232
title: Additional file 2 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 2: Table S1. Mouse Phenotypes.
DOI: 10.6084/m9.figshare.12737238.v2
title: Additional file 4 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 4: Table S3. Significant deletions.
DOI: 10.6084/m9.figshare.12737232.v2
title: Additional file 2 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 2: Table S1. Mouse Phenotypes.
DOI: 10.6084/m9.figshare.12737235.v2
title: Additional file 3 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 3: Table S2. Significantly Mutated Genes.
DOI: 10.6084/m9.figshare.12737238.v1
title: Additional file 4 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 4: Table S3. Significant deletions.
DOI: 10.6084/m9.figshare.12737226
title: Additional file 12 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 12: Table S11. sgRNA sequences.
DOI: 10.6084/m9.figshare.12737232.v1
title: Additional file 2 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 2: Table S1. Mouse Phenotypes.
DOI: 10.6084/m9.figshare.12737235.v1
title: Additional file 3 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 3: Table S2. Significantly Mutated Genes.
DOI: 10.6084/m9.figshare.12737226.v2
title: Additional file 12 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 12: Table S11. sgRNA sequences.
DOI: 10.6084/m9.figshare.12737223
title: Additional file 11 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 11: Table S10. GDSC glioma drug sensitivities.
DOI: 10.6084/m9.figshare.12737226.v1
title: Additional file 12 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 12: Table S11. sgRNA sequences.
DOI: 10.6084/m9.figshare.12737223.v2
title: Additional file 11 of PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas

description: Additional file 11: Table S10. GDSC glioma drug sensitivities.