cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5081313
title: Crustal thickness and Vp/Vs database from the Amazonian Craton and adjacent provinces

description: This database includes results of crustal thickness and Vp/Vs estimated from stations located in the Amazonian Craton and adjacent provinces. If you used this database, please cite:<br> <br> ALBUQUERQUE, D. F. et al. Crustal structure of the Amazonian Craton and adjacent provinces in Brazil. Journal of South American Earth Sciences, v. 79, p. 431–442, 2017. DOI: 10.1016/j.jsames.2017.08.019
DOI: 10.25442/hku.14880114
title: Supporting data for "Preservation and taphonomy of colouration in dinosaurs and their close relatives"

description: Guide to Dataset UsageFile organisation|- Chapter 2: Improving palaeocolour prediction with machine learning algorithms |-Chapter 2 Datasets |-Chapter 2 Scripts<br>|- Chapter 3: Sediment encased pressure temperature maturation simulates the natural diagenesis of melanin pigments<br>|- Chapter 4: Sediment–encased pressure–temperature maturation elucidates thepreservation potential of polyene derived avian pigments |-Chapter 4_TOF-SIMS DATA |-Chapter 4_Vibrational and Optical Spectroscopy DATA<br>
DOI: 10.25442/hku.14880114.v1
title: Supporting data for "Preservation and taphonomy of colouration in dinosaurs and their close relatives"

description: Guide to Dataset UsageFile organisation|- Chapter 2: Improving palaeocolour prediction with machine learning algorithms |-Chapter 2 Datasets |-Chapter 2 Scripts<br>|- Chapter 3: Sediment encased pressure temperature maturation simulates the natural diagenesis of melanin pigments<br>|- Chapter 4: Sediment–encased pressure–temperature maturation elucidates thepreservation potential of polyene derived avian pigments |-Chapter 4_TOF-SIMS DATA |-Chapter 4_Vibrational and Optical Spectroscopy DATA<br>
DOI: 10.5517/ccdc.csd.cc25n1rn
title: CCDC 2015271: Experimental Crystal Structure Determination

description: Related Article: Philipp C. Stegner, Christian A. Fischer, D. Thao Nguyen, Andreas Rösch, Johanne Penafiel, Jens Langer, Michael Wiesinger, Sjoerd Harder|2020|Eur.J.Inorg.Chem.|2020|3387|doi:10.1002/ejic.202000671
DOI: 10.5517/ccdc.csd.cc25n1sp
title: CCDC 2015272: Experimental Crystal Structure Determination

description: Related Article: Philipp C. Stegner, Christian A. Fischer, D. Thao Nguyen, Andreas Rösch, Johanne Penafiel, Jens Langer, Michael Wiesinger, Sjoerd Harder|2020|Eur.J.Inorg.Chem.|2020|3387|doi:10.1002/ejic.202000671
DOI: 10.5517/ccdc.csd.cc25n1tq
title: CCDC 2015273: Experimental Crystal Structure Determination

description: Related Article: Philipp C. Stegner, Christian A. Fischer, D. Thao Nguyen, Andreas Rösch, Johanne Penafiel, Jens Langer, Michael Wiesinger, Sjoerd Harder|2020|Eur.J.Inorg.Chem.|2020|3387|doi:10.1002/ejic.202000671
DOI: 10.5517/ccdc.csd.cc25n2kh
title: CCDC 2015296: Experimental Crystal Structure Determination

description: Related Article: Niall Collins, Robert Connon, Goar Sanchez-Sanz, Paul Evans|2020|Eur.J.Org.Chem.|2020|6228|doi:10.1002/ejoc.202001065
DOI: 10.5517/ccdc.csd.cc25n8bg
title: CCDC 2015475: Experimental Crystal Structure Determination

description: Related Article: Dmitri V. Konarev, Salavat S. Khasanov, Maxim V. Mikhailenko, Mikhail S. Batov, Alexander F. Shestakov, Alexey V. Kuzmin, Akihiro Otsuka, Hideki Yamochi, Hiroshi Kitagawa, Rimma N. Lyubovskaya|2021|Eur.J.Inorg.Chem.|2021|86|doi:10.1002/ejic.202000946
DOI: 10.5517/ccdc.csd.cc25nc18
title: CCDC 2015559: Experimental Crystal Structure Determination

description: Related Article: Štefan Malatinec, Eva Bednářová, Hiroki Tanaka, Martin Kotora|2021|Eur.J.Org.Chem.|2021|1249|doi:10.1002/ejoc.202001493
DOI: 10.5517/ccdc.csd.cc237sms
title: CCDC 1943905: Experimental Crystal Structure Determination

description: Related Article: Yan Zhang, Baoxing Zeng, Yifan Liu, Pan Li, Lijuan Chen, Junwei Zhao|2020|Eur.J.Inorg.Chem.|2020|3416|doi:10.1002/ejic.202000519
DOI: 10.5517/ccdc.csd.cc25npwf
title: CCDC 2015895: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25npxg
title: CCDC 2015896: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25npyh
title: CCDC 2015897: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25npzj
title: CCDC 2015898: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nq0l
title: CCDC 2015899: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nq1m
title: CCDC 2015900: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nq2n
title: CCDC 2015901: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nq3p
title: CCDC 2015902: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nq4q
title: CCDC 2015903: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nq5r
title: CCDC 2015904: Experimental Crystal Structure Determination

description: Related Article: Michael Tolzmann, Lina Schürmann, Alexander Hepp, Werner Uhl, Marcus Layh|2020|Eur.J.Inorg.Chem.|2020|4024|doi:10.1002/ejic.202000723
DOI: 10.5517/ccdc.csd.cc25nvc2
title: CCDC 2016034: Experimental Crystal Structure Determination

description: Related Article: Nicola Panza,  Armando di Biase,  Silvia Rizzato,  Emma Gallo,  Giorgio Tseberlidis,  Alessandro Caselli|2020|Eur.J.Org.Chem.|2020|6635|doi:10.1002/ejoc.202001201
DOI: 10.5517/ccdc.csd.cc25p0xt
title: CCDC 2016206: Experimental Crystal Structure Determination

description: Related Article: Elena N. Shaitanova,  Igor I. Gerus,  Olga A. Balabon,  Viktor E. Ivasyshyn,  Karen V. Tarasenko,  Constantin G. Daniliuc,  Günter Haufe|2020|Eur.J.Org.Chem.|2020|7156|doi:10.1002/ejoc.202001218
DOI: 10.5517/ccdc.csd.cc25p0yv
title: CCDC 2016207: Experimental Crystal Structure Determination

description: Related Article: Elena N. Shaitanova,  Igor I. Gerus,  Olga A. Balabon,  Viktor E. Ivasyshyn,  Karen V. Tarasenko,  Constantin G. Daniliuc,  Günter Haufe|2020|Eur.J.Org.Chem.|2020|7156|doi:10.1002/ejoc.202001218
DOI: 10.5517/ccdc.csd.cc25pd2c
title: CCDC 2016552: Experimental Crystal Structure Determination

description: Related Article: Susann Kintzel, Kai Eckhardt, Jürgen Getzschmann, Volodymyr Bon, Julia Grothe, Stefan Kaskel|2020|Eur.J.Inorg.Chem.|2020|3167|doi:10.1002/ejic.202000359
DOI: 10.5517/ccdc.csd.cc25p89g
title: CCDC 2016435: Experimental Crystal Structure Determination

description: Related Article: Joanne W. L. Wong, Shao‐An Hua, Serhiy Demeshko, Sebastian Dechert, Shengfa Ye, Franc Meyer|2020|Eur.J.Inorg.Chem.|2020|4137|doi:10.1002/ejic.202000697
DOI: 10.5517/ccdc.csd.cc25p8bh
title: CCDC 2016436: Experimental Crystal Structure Determination

description: Related Article: Joanne W. L. Wong, Shao‐An Hua, Serhiy Demeshko, Sebastian Dechert, Shengfa Ye, Franc Meyer|2020|Eur.J.Inorg.Chem.|2020|4137|doi:10.1002/ejic.202000697
DOI: 10.5517/ccdc.csd.cc25psth
title: CCDC 2016947: Experimental Crystal Structure Determination

description: Related Article: You-Jun Yu, Yun Hu, Sheng-Yi Yang, Wei Luo, Yi Yuan, Chen-Chen Peng, Jin-Feng Liu, Aziz Khan, Zuo-Quan Jiang, Liang-Sheng Liao|2020|Angew.Chem.,Int.Ed.|59|21578|doi:10.1002/anie.202006197
DOI: 10.5517/ccdc.csd.cc25pxd6
title: CCDC 2017058: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25pxf7
title: CCDC 2017059: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25pxg8
title: CCDC 2017060: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25pxh9
title: CCDC 2017061: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25pxjb
title: CCDC 2017062: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25pxkc
title: CCDC 2017063: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25pxmf
title: CCDC 2017065: Experimental Crystal Structure Determination

description: Related Article: Ryosuke Kobayashi, Toshiki Fujii, Hiroaki Imoto, and Kensuke Naka|2021|Eur.J.Inorg.Chem.|2021|217|doi:10.1002/ejic.202000810
DOI: 10.5517/ccdc.csd.cc25qnxh
title: CCDC 2017787: Experimental Crystal Structure Determination

description: Related Article: łukasz Szyszka,  Piotr Cmoch,  Marcin Górecki,  Magdalena Ceborska,  Mykhaylo A Potopnyk,  Sławomir Jarosz|2020|Eur.J.Org.Chem.|2021|897|doi:10.1002/ejoc.202001482
DOI: 10.6084/m9.figshare.14926713.v1
title: Figure 2. Spike antigen-specific IgG in serum from subjects with different MOS codes.

description: The mean and standard error of spike IgG ELISA OD values are shown for subjects that belong to different MOS groups with N &gt; 7 per MOS. * indicates significant (<i>p</i> &lt; 0.017) difference vs. other all other MOS codes.
DOI: 10.6084/m9.figshare.14926713
title: Figure 2. Spike antigen-specific IgG in serum from subjects with different MOS codes.

description: The mean and standard error of spike IgG ELISA OD values are shown for subjects that belong to different MOS groups with N &gt; 7 per MOS. * indicates significant (<i>p</i> &lt; 0.017) difference vs. other all other MOS codes.
DOI: 10.6084/m9.figshare.14926735.v1
title: Additional file 1 of Transcriptomic analysis of temporal shifts in berry development between two grapevine cultivars of the Pinot family reveals potential genes controlling ripening time

description: Additional file 1: Table S1. Clonal relation of PN and PNP confirmed by 24 SSR markers. Table S2. Sampling and phenotypical observations (BBCH) for 2014. Table S3. Sampling and phenotypical observations (BBCH) for 2017. Table S4. Pearsonr correlations of gene expression values over time between both years. Table S5. Top 500 genes influencing principal component PC1. Table S6. Top 500 genes influencing principal component PC2. Table S7. Cluster memberships of clusters obtained from the cluster analysis PN/PNP. Table S8. Cluster memberships of clusters obtained from the cluster analysis PN. Table S9. Cluster memberships of clusters obtained from the cluster analysis PNP. Table S10. GO term enrichment for the clusters from the cluster analysis of PN/PNP. Table S11. GO term enrichment for the clusters from the cluster analysis of PN. Table S12. GO term enrichment for the clusters from the cluster analysis of PNP. Table S13. Differentially expressed genes between PN and PNP in both years and filtering steps. Table S14. Overlap of 12 putatively ripening time control DEGs (time points: DAF 0-35 from 2014 intersecting with DAF 0-42 from 2017) and 388 veraison-specific DEGs (time points: DAF35+41 from 2014 intersecting with DAF42+49 from 2017) with previous transcriptomic grapevine studies. Table S15. VitisNet enrichment for intersecting DEGs. Table S16. VitisNet enrichment for regulatory DEGs. Table S17. VitisNet enrichment for veraison-specific DEGs. Table S18. Up- & Down-regulated TFs among the DEGs. Table S19. ENA sample identifier and metadata linked to the study for PNP RNA-Seq reads from 2014 (PRJEB39262). Table S20. ENA sample identifier and metadata linked to the study for PN RNA-Seq reads from 2014 (PRJEB39261). Table S21. ENA sample identifier and metadata linked to the study for PNP RNA-Seq reads from 2017 (PRJEB39264). Table S22. ENA sample identifier and metadata linked to the study for PN RNA-Seq reads from 2017 (PRJEB39263). Table S23. Sequences of primers used for qRT-PCR.
DOI: 10.6084/m9.figshare.14926742.v1
title: Additional file 2 of Genetic evidence for a causative effect of airflow obstruction on left ventricular filling: a Mendelian randomisation study

description: Additional file 2: Table S1. Detailed information on the IV used in the MR analyses. Table S2. Intercept from Egger-regression analyses. Table S3. Results from single SNP MR based on the ratio estimate and from leave-one-out MR based on the IVW method. Table S4. Association of the IV with potential covariates retrieved from a curated database of human genotype-phenotype associations. P-value of association displayed.
DOI: 10.6084/m9.figshare.14926742
title: Additional file 2 of Genetic evidence for a causative effect of airflow obstruction on left ventricular filling: a Mendelian randomisation study

description: Additional file 2: Table S1. Detailed information on the IV used in the MR analyses. Table S2. Intercept from Egger-regression analyses. Table S3. Results from single SNP MR based on the ratio estimate and from leave-one-out MR based on the IVW method. Table S4. Association of the IV with potential covariates retrieved from a curated database of human genotype-phenotype associations. P-value of association displayed.
DOI: 10.6084/m9.figshare.14926735
title: Additional file 1 of Transcriptomic analysis of temporal shifts in berry development between two grapevine cultivars of the Pinot family reveals potential genes controlling ripening time

description: Additional file 1: Table S1. Clonal relation of PN and PNP confirmed by 24 SSR markers. Table S2. Sampling and phenotypical observations (BBCH) for 2014. Table S3. Sampling and phenotypical observations (BBCH) for 2017. Table S4. Pearsonr correlations of gene expression values over time between both years. Table S5. Top 500 genes influencing principal component PC1. Table S6. Top 500 genes influencing principal component PC2. Table S7. Cluster memberships of clusters obtained from the cluster analysis PN/PNP. Table S8. Cluster memberships of clusters obtained from the cluster analysis PN. Table S9. Cluster memberships of clusters obtained from the cluster analysis PNP. Table S10. GO term enrichment for the clusters from the cluster analysis of PN/PNP. Table S11. GO term enrichment for the clusters from the cluster analysis of PN. Table S12. GO term enrichment for the clusters from the cluster analysis of PNP. Table S13. Differentially expressed genes between PN and PNP in both years and filtering steps. Table S14. Overlap of 12 putatively ripening time control DEGs (time points: DAF 0-35 from 2014 intersecting with DAF 0-42 from 2017) and 388 veraison-specific DEGs (time points: DAF35+41 from 2014 intersecting with DAF42+49 from 2017) with previous transcriptomic grapevine studies. Table S15. VitisNet enrichment for intersecting DEGs. Table S16. VitisNet enrichment for regulatory DEGs. Table S17. VitisNet enrichment for veraison-specific DEGs. Table S18. Up- & Down-regulated TFs among the DEGs. Table S19. ENA sample identifier and metadata linked to the study for PNP RNA-Seq reads from 2014 (PRJEB39262). Table S20. ENA sample identifier and metadata linked to the study for PN RNA-Seq reads from 2014 (PRJEB39261). Table S21. ENA sample identifier and metadata linked to the study for PNP RNA-Seq reads from 2017 (PRJEB39264). Table S22. ENA sample identifier and metadata linked to the study for PN RNA-Seq reads from 2017 (PRJEB39263). Table S23. Sequences of primers used for qRT-PCR.
DOI: 10.25919/716a-kj52
title: Parkes observations for project P1050 semester 2021APRS_10

description: This is a request for observing time for the timing campaign of new pulsar discoveries from the reprocessing of the low-latitude Galactic plane section of the HTRU survey (P630). We have now completed 80 % of the survey with GPU based coherent acceleration search, template bank and fast folding algorithm pipelines, and now have discovered 68 previously unknown pulsars and 21 "class A" pulsars awaiting confirmation. Interesting science can usually only be derived from a new pulsar after confirmation and a follow-up timing campaign is carried out. One year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, spin-down rate, as well as to detect any unexpected behaviour of the pulsar which might result from emission instabilities. This timing project is necessary for the timing of the new double neutron star (DNS) system J1325-6253 discovered last semester and for following up our confirmed/to-be confirmed new pulsars from the HTRU Galactic plane survey. Pulsars on the observing list here have been confirmed and remaining candidates will be confirmed in the current 2020OCTS semester, the follow-up timing in 2021APRS will produce completely new and exciting results. In addition, this timing project will allow us to measure the advance of periastron of PSR J1325-6253, true Galactic plane pulsar population and boundaries of pulsar parameter space in the galactic plane.
DOI: 10.6084/m9.figshare.14926799
title: Additional file 10 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 10. Differentially expressed genes of all M cells subclusters.
DOI: 10.6084/m9.figshare.14926802
title: Additional file 11 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 11. Differentially expressed genes of FB clusters among endometriosis lesions, eutopic endometrium, and normal endometrium.
DOI: 10.6084/m9.figshare.14926799.v1
title: Additional file 10 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 10. Differentially expressed genes of all M cells subclusters.
DOI: 10.6084/m9.figshare.14926802.v1
title: Additional file 11 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 11. Differentially expressed genes of FB clusters among endometriosis lesions, eutopic endometrium, and normal endometrium.
DOI: 10.6084/m9.figshare.14926805
title: Additional file 12 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 12. Differentially expressed genes of CD4+ T cells along the pseudotime trajectory.
DOI: 10.6084/m9.figshare.14926805.v1
title: Additional file 12 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 12. Differentially expressed genes of CD4+ T cells along the pseudotime trajectory.
DOI: 10.6084/m9.figshare.14926817
title: Additional file 3 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 3. Differentially expressed genes of FBs, M cells, NK cells, T cells, ECs, Eps, mast cells, and neutrophils.
DOI: 10.6084/m9.figshare.14926817.v1
title: Additional file 3 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 3. Differentially expressed genes of FBs, M cells, NK cells, T cells, ECs, Eps, mast cells, and neutrophils.
DOI: 10.6084/m9.figshare.14926820
title: Additional file 4 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 4. Differentially expressed genes of all FBs subclusters.
DOI: 10.6084/m9.figshare.14926820.v1
title: Additional file 4 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 4. Differentially expressed genes of all FBs subclusters.
DOI: 10.6084/m9.figshare.14926823
title: Additional file 5 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 5. Differentially expressed genes of FBs along the pseudotime trajectory.
DOI: 10.6084/m9.figshare.14926823.v1
title: Additional file 5 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 5. Differentially expressed genes of FBs along the pseudotime trajectory.
DOI: 10.6084/m9.figshare.14926826
title: Additional file 6 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 6. The relative ratio of immune cells in endometriosis lesions, eutopic endometrium, and normal endometrium.
DOI: 10.6084/m9.figshare.14926826.v1
title: Additional file 6 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 6. The relative ratio of immune cells in endometriosis lesions, eutopic endometrium, and normal endometrium.
DOI: 10.6084/m9.figshare.14926829
title: Additional file 7 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 7. Differentially expressed genes of all T cells subclusters.
DOI: 10.6084/m9.figshare.14926829.v1
title: Additional file 7 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 7. Differentially expressed genes of all T cells subclusters.
DOI: 10.6084/m9.figshare.14926832
title: Additional file 8 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 8. The relative ratio of T cells subclusters in endometriosis lesions, eutopic endometrium, and normal endometrium.
DOI: 10.6084/m9.figshare.14926832.v1
title: Additional file 8 of Single-cell transcriptomic analysis of endometriosis provides insights into fibroblast fates and immune cell heterogeneity

description: Additional file 8. The relative ratio of T cells subclusters in endometriosis lesions, eutopic endometrium, and normal endometrium.