cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5728968.v1
title: Additional file 2: Table S2. of Comparison, alignment, and synchronization of cell line information between CLO and EFO

description: Final EFO-CLO alignment result. The 874 EFO-CLO mapped cell lines aligned and merged into CLO (Tab. 1 in the excel file) and 344 EFO unique immortalized permanent cell lines added to CLO (Tab. 2 in the excel file). File is stored in Microsoft Excel spreadsheet (xlsx) format. (XLSX 54Â kb)
DOI: 10.6084/m9.figshare.5728962
title: MOESM4 of Prostate cancer small non-coding RNA transcriptome in Arabs

description: Additional file 4. miRNA editing summary.
DOI: 10.6084/m9.figshare.5728962.v1
title: MOESM4 of Prostate cancer small non-coding RNA transcriptome in Arabs

description: Additional file 4. miRNA editing summary.
DOI: 10.6084/m9.figshare.5728956
title: Additional file 1 of An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

description: Breast cancer datasets. Summary Tables of GEO datasets retrived and selected for inclusion into the current study. (XLS 2931 kb)
DOI: 10.6084/m9.figshare.5728956.v1
title: Additional file 1 of An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

description: Breast cancer datasets. Summary Tables of GEO datasets retrived and selected for inclusion into the current study. (XLS 2931 kb)
DOI: 10.6084/m9.figshare.5728953
title: Additional file 1: Table S1. of Comparison, alignment, and synchronization of cell line information between CLO and EFO

description: EFO cell lines drawn from external sources. In the initial step of the EFO-CLO comparison and alignment process, there are 428 and 20 EFO cell lines which were imported from Cell Line Ontology and 20 in BRENDA Tissue and Enzyme Source Ontology respectively. These 448 EFO cell lines were excluded from the entire mapping process. File is stored in Microsoft Excel spreadsheet (xlsx) format. (XLSX 47Â kb)
DOI: 10.6084/m9.figshare.5728953.v1
title: Additional file 1: Table S1. of Comparison, alignment, and synchronization of cell line information between CLO and EFO

description: EFO cell lines drawn from external sources. In the initial step of the EFO-CLO comparison and alignment process, there are 428 and 20 EFO cell lines which were imported from Cell Line Ontology and 20 in BRENDA Tissue and Enzyme Source Ontology respectively. These 448 EFO cell lines were excluded from the entire mapping process. File is stored in Microsoft Excel spreadsheet (xlsx) format. (XLSX 47Â kb)
DOI: 10.6084/m9.figshare.5728947
title: Additional file 3: of Constraint-based perturbation analysis with cluster Newton method: a case study of personalized parameter estimations with irinotecan whole-body physiologically based pharmacokinetic model

description: The median values of Kp from parameter sets with SSR 0.03 or less after first CNM. This file shows the median values of Kp from parameter sets with SSR 0.03 or less after first CNM. The values are fixed in second CNM with constraints. (XLS 46 kb)
DOI: 10.6084/m9.figshare.5728947.v1
title: Additional file 3: of Constraint-based perturbation analysis with cluster Newton method: a case study of personalized parameter estimations with irinotecan whole-body physiologically based pharmacokinetic model

description: The median values of Kp from parameter sets with SSR 0.03 or less after first CNM. This file shows the median values of Kp from parameter sets with SSR 0.03 or less after first CNM. The values are fixed in second CNM with constraints. (XLS 46 kb)
DOI: 10.6084/m9.figshare.5728944
title: MOESM3 of Prostate cancer small non-coding RNA transcriptome in Arabs

description: Additional file 3. miRNA expression comparison in each pair of PCa samples.
DOI: 10.6084/m9.figshare.5728944.v1
title: MOESM3 of Prostate cancer small non-coding RNA transcriptome in Arabs

description: Additional file 3. miRNA expression comparison in each pair of PCa samples.
DOI: 10.6084/m9.figshare.12895331
title: Dataset for "Is Software Engineering Research Addressing Software Engineering Problems?" (ASE 2020)

description: Analysis of papers from 2019 SE conferences. Data for "Is Software Engineering Research Addressing Software Engineering Problems", published in Automated Software Engineering Conference (ASE 2020), Extended Abstract.
DOI: 10.6084/m9.figshare.5728935
title: Additional file 11 of An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

description: Significant drugs for Tumor vs Adjacent 4 gene signatures. The list of candidate drugs from connectivity mapping analysis using the 4 Tumor-vs-Adjacent gene signatures. List drugs are significant in at least three out of four input gene signatures. (XLSX 19 kb)
DOI: 10.6084/m9.figshare.5728929
title: MOESM2 of Prostate cancer small non-coding RNA transcriptome in Arabs

description: Additional file 2: Table S4. miRNA reads summary.
DOI: 10.6084/m9.figshare.5728929.v1
title: MOESM2 of Prostate cancer small non-coding RNA transcriptome in Arabs

description: Additional file 2: Table S4. miRNA reads summary.
DOI: 10.6084/m9.figshare.5728923
title: Additional file 2 of OptPipe - a pipeline for optimizing metabolic engineering targets

description: OptPipe - Supplementary Results. Additional Tables. (XLSX 221 kb)
DOI: 10.6084/m9.figshare.5728923.v1
title: Additional file 2 of OptPipe - a pipeline for optimizing metabolic engineering targets

description: OptPipe - Supplementary Results. Additional Tables. (XLSX 221 kb)
DOI: 10.6084/m9.figshare.5728920
title: Additional file 10 of An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

description: Tumor vs Adjacent 4 gene signatures. The 4 non-joint 41-gene signatures are included, each consisting of genes equally distanced in the rankings of the 164 significant genes from Tumor vs Adjacent differential expression analysis. (XLSX 21 kb)
DOI: 10.6084/m9.figshare.5728920.v1
title: Additional file 10 of An integrated meta-analysis approach to identifying medications with potential to alter breast cancer risk through connectivity mapping

description: Tumor vs Adjacent 4 gene signatures. The 4 non-joint 41-gene signatures are included, each consisting of genes equally distanced in the rankings of the 164 significant genes from Tumor vs Adjacent differential expression analysis. (XLSX 21 kb)
DOI: 10.6084/m9.figshare.5728863
title: Additional file 9: Table S8. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Functional annotation of the hub genes in glioblastoma multiforme. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.5728863.v1
title: Additional file 9: Table S8. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Functional annotation of the hub genes in glioblastoma multiforme. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.5728839
title: Additional file 8: Table S7. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Functional annotation of the hub genes in breast cancer. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.5728839.v1
title: Additional file 8: Table S7. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Functional annotation of the hub genes in breast cancer. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.5728833
title: Additional file 9: Table S2. of The Toll pathway underlies host sexual dimorphism in resistance to both Gram-negative and Gram-positive bacteria in mated Drosophila

description: Column information for the transcriptomic analysis. This table contains the information on the samples used in the DESeq2 analysis with the function â DESeqDataSetFromMatrixâ and Additional file 8: Table S1. (CSV 1 kb)
DOI: 10.6084/m9.figshare.5728833.v1
title: Additional file 9: Table S2. of The Toll pathway underlies host sexual dimorphism in resistance to both Gram-negative and Gram-positive bacteria in mated Drosophila

description: Column information for the transcriptomic analysis. This table contains the information on the samples used in the DESeq2 analysis with the function â DESeqDataSetFromMatrixâ and Additional file 8: Table S1. (CSV 1 kb)
DOI: 10.6084/m9.figshare.5728827
title: Additional file 7: Table S6. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Hubs in the network of glioblastoma multiforme. (XLSX 57 kb)
DOI: 10.6084/m9.figshare.5728827.v1
title: Additional file 7: Table S6. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Hubs in the network of glioblastoma multiforme. (XLSX 57 kb)
DOI: 10.6084/m9.figshare.5728815
title: Additional file 8: Table S1. of The Toll pathway underlies host sexual dimorphism in resistance to both Gram-negative and Gram-positive bacteria in mated Drosophila

description: Count matrix for the transcriptomic analysis. This matrix contains the normalized read counts used in the DESeq2 analysis with the function â DESeqDataSetFromMatrixâ . (CSV 2291 kb)
DOI: 10.6084/m9.figshare.5728815.v1
title: Additional file 8: Table S1. of The Toll pathway underlies host sexual dimorphism in resistance to both Gram-negative and Gram-positive bacteria in mated Drosophila

description: Count matrix for the transcriptomic analysis. This matrix contains the normalized read counts used in the DESeq2 analysis with the function â DESeqDataSetFromMatrixâ . (CSV 2291 kb)
DOI: 10.6084/m9.figshare.5728809
title: Additional file 6: Table S5. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Hubs in the network of breast cancer. (XLSX 57 kb)
DOI: 10.6084/m9.figshare.5728809.v1
title: Additional file 6: Table S5. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Hubs in the network of breast cancer. (XLSX 57 kb)
DOI: 10.6084/m9.figshare.5728800
title: Additional file 5: Table S4. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Hubs in the network of ovarian cancer. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.5728800.v1
title: Additional file 5: Table S4. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Hubs in the network of ovarian cancer. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.5728785
title: Additional file 4: Table S3. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The DNA methylation interaction network of glioblastoma multiforme. This table describes all the DNA methylation interaction pairs in the network. (XLSX 12818 kb)
DOI: 10.6084/m9.figshare.5728785.v1
title: Additional file 4: Table S3. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The DNA methylation interaction network of glioblastoma multiforme. This table describes all the DNA methylation interaction pairs in the network. (XLSX 12818 kb)
DOI: 10.6084/m9.figshare.5728770
title: Additional file 3: Table S2. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The DNA methylation interaction network of breast cancer. This table describes all the DNA methylation interaction pairs in the network. (XLSX 12808 kb)
DOI: 10.6084/m9.figshare.5728770.v1
title: Additional file 3: Table S2. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The DNA methylation interaction network of breast cancer. This table describes all the DNA methylation interaction pairs in the network. (XLSX 12808 kb)
DOI: 10.6084/m9.figshare.5728749
title: Additional file 1: Table S1. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The DNA methylation interaction network of ovarian cancer. This table describes all the DNA methylation interaction pairs in the network. (XLSX 12331 kb)
DOI: 10.6084/m9.figshare.5728749.v1
title: Additional file 1: Table S1. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The DNA methylation interaction network of ovarian cancer. This table describes all the DNA methylation interaction pairs in the network. (XLSX 12331 kb)
DOI: 10.6084/m9.figshare.5728725
title: Additional file 18: Table S17. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The control signature of glioblastoma multiforme. The signature contains the same number of DNA methylation sites with our prognostic genes. The sites in the signature are the most significant ones with the prognostic risks of cancer patients. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.5728725.v1
title: Additional file 18: Table S17. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The control signature of glioblastoma multiforme. The signature contains the same number of DNA methylation sites with our prognostic genes. The sites in the signature are the most significant ones with the prognostic risks of cancer patients. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.5728707
title: Additional file 17: Table S16. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The control signature of breast cancer. The signature contains the same number of DNA methylation sites with our prognostic genes. The sites in the signature are the most significant ones with the prognostic risks of cancer patients. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.5728707.v1
title: Additional file 17: Table S16. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The control signature of breast cancer. The signature contains the same number of DNA methylation sites with our prognostic genes. The sites in the signature are the most significant ones with the prognostic risks of cancer patients. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.5728695
title: Additional file 16: Table S15. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The control signature of ovarian cancer. The signature contains the same number of DNA methylation sites with our prognostic genes. The sites in the signature are the most significant ones with the prognostic risks of cancer patients. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5728695.v1
title: Additional file 16: Table S15. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The control signature of ovarian cancer. The signature contains the same number of DNA methylation sites with our prognostic genes. The sites in the signature are the most significant ones with the prognostic risks of cancer patients. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5728674
title: Additional file 15: Table S14. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The prognostic genes of glioblastoma multiforme. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.5728674.v1
title: Additional file 15: Table S14. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The prognostic genes of glioblastoma multiforme. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.5728656
title: Additional file 14: Table S13. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Samples in the training data set and test data set of glioblastoma multiforme. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.5728656.v1
title: Additional file 14: Table S13. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Samples in the training data set and test data set of glioblastoma multiforme. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.5728638
title: Additional file 13: Table S12. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The prognostic genes of breast cancer. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5728638.v1
title: Additional file 13: Table S12. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The prognostic genes of breast cancer. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5728614
title: Additional file 12: Table S11. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Samples in the training and test sets of breast cancer. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.5728593
title: Additional file 11: Table S10. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The prognostic genes of ovarian cancer. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5728593.v1
title: Additional file 11: Table S10. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: The prognostic genes of ovarian cancer. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5728581
title: Additional file 2: of Calls during agonistic interactions vary with arousal and raise audience attention in ravens

description: Praat script used to analyze defensive calls in common ravens. (TXT 4.30 kb)
DOI: 10.6084/m9.figshare.5728581.v1
title: Additional file 2: of Calls during agonistic interactions vary with arousal and raise audience attention in ravens

description: Praat script used to analyze defensive calls in common ravens. (TXT 4.30 kb)
DOI: 10.6084/m9.figshare.5728569
title: Additional file 10: Table S9. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Samples in the training and test sets of ovarian cancer. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.5728569.v1
title: Additional file 10: Table S9. of Identification of prognostic signature in cancer based on DNA methylation interaction network

description: Samples in the training and test sets of ovarian cancer. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.5728467
title: BET-seq Processed Data

description: This fileset contains all of the intermediate processed files from the BET-seq manuscript concerning motif refinement in the regions flanking the core binding motifs of the Pho4 and Cbf1 yeast transcription factors.
DOI: 10.6084/m9.figshare.5728452
title: Data - prepubertal males and femles, postpubertal näive, and ppostpubertal sexually experienced males

description: Refers to MS submitted to EJN - Dec 2017
DOI: 10.6084/m9.figshare.5728452.v1
title: Data - prepubertal males and femles, postpubertal näive, and ppostpubertal sexually experienced males

description: Refers to MS submitted to EJN - Dec 2017
DOI: 10.6084/m9.figshare.5728449
title: Diatom assemblages from surface sediments of the Río de la Plata estuary, Uruguay

description: The Río de la Plata estuary (RdlP) exhibits environmental gradients associated with the freshwater input and oceanic water intrusion. The aim of this study was to assess diatom species distribution in surface sediment samples related to such environmental gradients. The internal section of RdlP was dominated by <i>Aulacoseira</i> spp<i>.</i>, <i>Eunotia</i> spp., <i>Staurosirella martyi</i>, <i>Actinocyclus normanii</i> and <i>Thalassiosira baltica</i>, indicatives of low salinity levels and high trophic conditions, associated with the riverine and estuarine regimes. The external section was dominated by <i>Coscinodiscus radiatus</i>, <i>Thalassiosira</i> spp., <i>Paralia sulcata</i>, <i>Cyclotella striata</i>, among other marine taxa, indicatives of high salinity and low trophic conditions, associated with the influence of the Southwestern Atlantic Ocean. Furthermore, the intermediate section presents a mixture of both diatom groups representing mixing conditions. The observed diatom species groups capture fairly well the RdlP environmental variability and can be reliably used for paleoenvironmental studies in this and other similar estuarine systems.
DOI: 10.6084/m9.figshare.5728449.v1
title: Diatom assemblages from surface sediments of the Río de la Plata estuary, Uruguay

description: The Río de la Plata estuary (RdlP) exhibits environmental gradients associated with the freshwater input and oceanic water intrusion. The aim of this study was to assess diatom species distribution in surface sediment samples related to such environmental gradients. The internal section of RdlP was dominated by <i>Aulacoseira</i> spp<i>.</i>, <i>Eunotia</i> spp., <i>Staurosirella martyi</i>, <i>Actinocyclus normanii</i> and <i>Thalassiosira baltica</i>, indicatives of low salinity levels and high trophic conditions, associated with the riverine and estuarine regimes. The external section was dominated by <i>Coscinodiscus radiatus</i>, <i>Thalassiosira</i> spp., <i>Paralia sulcata</i>, <i>Cyclotella striata</i>, among other marine taxa, indicatives of high salinity and low trophic conditions, associated with the influence of the Southwestern Atlantic Ocean. Furthermore, the intermediate section presents a mixture of both diatom groups representing mixing conditions. The observed diatom species groups capture fairly well the RdlP environmental variability and can be reliably used for paleoenvironmental studies in this and other similar estuarine systems.
DOI: 10.6084/m9.figshare.5728320
title: THE RICCI SCALAR IN THE DETERMINATION OF CURVATURE SINGULARITIES IN NON-SCHWARZSCHILD SPACETIMES

description: this work provides a simple method of determining spacetime singularities inherent in Non-Schwarzschild spacetimes using the Ricci scalar invariant.<br>
DOI: 10.6084/m9.figshare.5728320.v1
title: THE RICCI SCALAR IN THE DETERMINATION OF CURVATURE SINGULARITIES IN NON-SCHWARZSCHILD SPACETIMES

description: this work provides a simple method of determining spacetime singularities inherent in Non-Schwarzschild spacetimes using the Ricci scalar invariant.<br>
DOI: 10.6084/m9.figshare.5728183
title: EMREO_figshare_dogear.txt

description: This is a placeholder document to create the figshare accession number.<br>
DOI: 10.6084/m9.figshare.5727427
title: Data from BCRV infection of House Sparrow Nestlings

description: These files contain various data types collected from project in which house sparrow nestlings were infected with Buggy Creek virus. <br>
DOI: 10.6084/m9.figshare.5727427.v1
title: Data from BCRV infection of House Sparrow Nestlings

description: These files contain various data types collected from project in which house sparrow nestlings were infected with Buggy Creek virus. <br>
DOI: 10.6084/m9.figshare.5727104.v1
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104.v2
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104.v3
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104.v8
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104.v9
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104.v11
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727104.v10
title: Timelapse 8 - raw confocal files

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727090
title: Timelapse 8 - Maximum intensity projections - bleach corrected

description: See accompanying word documents
DOI: 10.6084/m9.figshare.5727090.v2
title: Timelapse 8 - Maximum intensity projections - bleach corrected

description: See accompanying word documents