cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11945436
title: Additional file 4 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 4:Table S3. List of identified locus-specific chromatin interactions at β-globin LCR. The list of locus-specific inter- and intra-chromosomal DNA interactions identified by multiplexed CAPTURE-3C-seq analysis of β-globin LCR is shown. Data processing and statistical analyses were performed as described in Methods. Results compiled from two or three independent CAPTURE-3C-seq experiments are shown.
DOI: 10.6084/m9.figshare.25273516
title: Robust Personalized Federated Learning with Sparse Penalization*

description: Federated learning (FL) is an emerging topic due to its advantage in collaborative learning with distributed data. Due to the heterogeneity in the local data-generating mechanism, it is important to consider personalization when developing federated learning methods. In this work, we propose a personalized federated learning (PFL) method to address the robust regression problem. Specifically, we aim to learn the regression weight by solving a Huber loss with the sparse fused penalty. Additionally, we designed our personalized federated learning for robust and sparse regression (PerFL-RSR) algorithm to solve the estimation problem in the federated system efficiently. Theoretically, we show that the proposed PerFL-RSR reaches a convergence rate of O(1/T), and the proposed estimator is statistically consistent. Thorough experiments and real data analysis are conducted to corroborate the theoretical results of our proposed personalized federated learning method.
DOI: 10.6084/m9.figshare.11945436.v1
title: Additional file 4 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 4:Table S3. List of identified locus-specific chromatin interactions at β-globin LCR. The list of locus-specific inter- and intra-chromosomal DNA interactions identified by multiplexed CAPTURE-3C-seq analysis of β-globin LCR is shown. Data processing and statistical analyses were performed as described in Methods. Results compiled from two or three independent CAPTURE-3C-seq experiments are shown.
DOI: 10.6084/m9.figshare.25273516.v1
title: Robust Personalized Federated Learning with Sparse Penalization*

description: Federated learning (FL) is an emerging topic due to its advantage in collaborative learning with distributed data. Due to the heterogeneity in the local data-generating mechanism, it is important to consider personalization when developing federated learning methods. In this work, we propose a personalized federated learning (PFL) method to address the robust regression problem. Specifically, we aim to learn the regression weight by solving a Huber loss with the sparse fused penalty. Additionally, we designed our personalized federated learning for robust and sparse regression (PerFL-RSR) algorithm to solve the estimation problem in the federated system efficiently. Theoretically, we show that the proposed PerFL-RSR reaches a convergence rate of O(1/T), and the proposed estimator is statistically consistent. Thorough experiments and real data analysis are conducted to corroborate the theoretical results of our proposed personalized federated learning method.
DOI: 10.6084/m9.figshare.11945442
title: Additional file 5 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 5:Table S4. List of captured hierarchical and non-hierarchical SEs. Hi-Hub, hub enhancer within the hierarchical SE; Hi-NonHub, non-hub enhancer within the hierarchical SE; NonHi-NonHub, non-hierarchical SE.
DOI: 10.6084/m9.figshare.11945442.v1
title: Additional file 5 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 5:Table S4. List of captured hierarchical and non-hierarchical SEs. Hi-Hub, hub enhancer within the hierarchical SE; Hi-NonHub, non-hub enhancer within the hierarchical SE; NonHi-NonHub, non-hierarchical SE.
DOI: 10.6084/m9.figshare.11945448
title: Additional file 6 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 6:Table S5. List of identified locus-specific chromatin interactions at the captured erythroid SEs. Results compiled from two or three independent CAPTURE-3C-seq experiments are shown.
DOI: 10.6084/m9.figshare.11945448.v1
title: Additional file 6 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 6:Table S5. List of identified locus-specific chromatin interactions at the captured erythroid SEs. Results compiled from two or three independent CAPTURE-3C-seq experiments are shown.
DOI: 10.6084/m9.figshare.11945454
title: Additional file 7 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 7:Table S6. List of identified promoter-centric chromatin interactions in G1ER cells. The lists of locus-specific interactions identified by multiplexed CAPTURE-3C-seq analysis of 22 activated and 20 repressed promoters are shown. Results compiled from two or three independent CAPTURE-3C-seq experiments are shown.
DOI: 10.15468/gj38hk
title: Biodiversity of the families Elateridae, Drilidae, Lycidae, Lampyridae, Cantharidae, Cerambycidae, Coccinellidae (Coleoptera, Insecta) in Republic of Mordovia (Russia)

description: The research was carried out in 1972-1974, 1984, 2002-2023, and also used museum collections of previous years. Collected in a variety of ways (caught in the light and on various baits, in soil traps, etc.). The dataset contains data on 256 species of Coleoptera from 7 families living on the territory of the Republic of Mordovia: Elateridae (62 species), Drilidae (1 species), Lycidae (8 species), Lampyridae (1 species), Cantharidae (30 species), Cerambycidae (106 species), Coccinellidae (48 species); (4) Seven species are listed for the first time for the region (Malthodes flavoguttatus, Malthodes minimus (Cantharidae); Scymnus rubromaculatus (Coccinellidae); Anoplodera rufipes ventralis, Tragosoma depsarium, Xylotrechus arvicola, Xylotrechus ibex (Cerambycidae).
DOI: 10.15468/bgw4nq
title: ONF - Données issues d'études conventionnelles commandées par organismes exterieurs à l'ONF - MOA : DREAL AUvergne-ONF - DFF Import Gorges Allier-Dordogne-Rhue

description: Données DFF Gorges Allier-Dordogne-Rhue pour DREAL - Données transmises à l'ONF dans le cadre d'études commandées par MOA exterieures à l'ONF
DOI: 10.6084/m9.figshare.11945463
title: Additional file 8 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 8:Table S7. List of candidate enhancers interacting with captured promoters in G1ER cells. The chromosome coordinates of the candidate enhancers interacting with the captured promoters are shown.
DOI: 10.6084/m9.figshare.11945523.v1
title: Additional file 4 of Long non-coding RNA HUMT hypomethylation promotes lymphangiogenesis and metastasis via activating FOXK1 transcription in triple-negative breast cancer

description: Additional file 4: Figure S4. Pan-cancer analysis of TCGA datasets indicated a significant correlation between specific methylation probe signal and HUMT expression.
DOI: 10.6084/m9.figshare.11945463.v1
title: Additional file 8 of Multiplexed capture of spatial configuration and temporal dynamics of locus-specific 3D chromatin by biotinylated dCas9

description: Additional file 8:Table S7. List of candidate enhancers interacting with captured promoters in G1ER cells. The chromosome coordinates of the candidate enhancers interacting with the captured promoters are shown.
DOI: 10.6084/m9.figshare.11945523
title: Additional file 4 of Long non-coding RNA HUMT hypomethylation promotes lymphangiogenesis and metastasis via activating FOXK1 transcription in triple-negative breast cancer

description: Additional file 4: Figure S4. Pan-cancer analysis of TCGA datasets indicated a significant correlation between specific methylation probe signal and HUMT expression.
DOI: 10.6084/m9.figshare.11945541
title: Additional file 7 of Long non-coding RNA HUMT hypomethylation promotes lymphangiogenesis and metastasis via activating FOXK1 transcription in triple-negative breast cancer

description: Additional file 7:. Figure S7. Kaplan-Meier analysis showed HUMT predicted a poorer OS and RFS outcomes in specific cancers using KM plotter tools.
DOI: 10.6084/m9.figshare.11945541.v1
title: Additional file 7 of Long non-coding RNA HUMT hypomethylation promotes lymphangiogenesis and metastasis via activating FOXK1 transcription in triple-negative breast cancer

description: Additional file 7:. Figure S7. Kaplan-Meier analysis showed HUMT predicted a poorer OS and RFS outcomes in specific cancers using KM plotter tools.
DOI: 10.15468/s4ksk2
title: ONF - Données issues d'études conventionnelles commandées par organismes exterieurs à l'ONF - MOA : DRAA-ONF - DFF données Olivier Rose Etudes concurrentielles pour DRAA

description: Données transmises à l'ONF dans le cadre d'études commandées par MOA exterieures à l'ONF
DOI: 10.15468/9r2s2w
title: ONF - Données issues d'études conventionnelles commandées par organismes exterieurs à l'ONF - MOA : IRSTEA-ONF - DFF Import Parmain Saint-Palais

description: Projet créé pour importation de la base DFF Parmain Saint-Palais (fév. 2013) - Données transmises à l'ONF dans le cadre d'études commandées par MOA exterieures à l'ONF
DOI: 10.5281/zenodo.8406484
title: Raw dataset for Bodipy-quinone-dyad publication

description: Experimental and computation data for bodipy-quinone manuscript
description: The authors gratefully acknowledge the Deutsche Forschungsgemeinschaft DFG for financial support (projects TRR 234 "CataLight", projects A1, A4, project no: 364549901; SPP2102, "Light-controlled reactivity of metal complexes", project no: 359737763, 494988281). S.K. gratefully acknowledges a LGFG PhD fellowship by the State of Baden-Württemberg.
DOI: 10.5281/zenodo.8406483
title: Raw dataset for Bodipy-quinone-dyad publication

description: Experimental and computation data for bodipy-quinone manuscript
description: The authors gratefully acknowledge the Deutsche Forschungsgemeinschaft DFG for financial support (projects TRR 234 "CataLight", projects A1, A4, project no: 364549901; SPP2102, "Light-controlled reactivity of metal complexes", project no: 359737763, 494988281). S.K. gratefully acknowledges a LGFG PhD fellowship by the State of Baden-Württemberg.
DOI: 10.15468/txr892
title: ONF - Données issues d'études conventionnelles commandées par organismes exterieurs à l'ONF - MOA : DREAL Franche-Comté-ONF - DFF Import Bresse jurassienne

description: Données DFF Bresse jurassienne pour DREAL - Données transmises à l'ONF dans le cadre d'études commandées par MOA exterieures à l'ONF
DOI: 10.6084/m9.figshare.12994179
title: Identification of the origin of brain metastases based on the relative methylation orderings of CpG sites

description: Accurate diagnosis of the origin of brain metastases (BMs) is crucial for tailoring an effective therapy to improve patients’ prognosis. BMs of unknown origin account for approximately 2–14% of patients with BMs. Hence, the aim of this study was to identify the original cancer type of BMs based on their DNA methylation profiles. The DNA methylation profiles of glioma (GM), BM, and seven other types of primary cancers were collected. In comparison with GM, the reversal CpG site pairs were identified for each of the seven other types of primary cancers based on the within-sample relative methylation orderings (RMOs) of the CpG sites. Then, using the reversal CpG site pairs, GMs were distinguished from BMs and the seven other types of primary cancers. All 61 of the GM samples were correctly identified as GM. The cancer type was also identified for the non-GM samples. For the seven other types of primary cancers, greater than 93% of samples of each cancer type were correctly identified as their corresponding cancer type, except for breast cancer, which had an 88% accuracy. For 133 BM samples, 132 BM samples were identified as non-GM, and 95% of the 133 BM samples were correctly classified into their corresponding original cancer types. The RMO-based method can accurately identify the origin of BMs, which is important for precision treatment.
DOI: 10.6084/m9.figshare.12994179.v2
title: Identification of the origin of brain metastases based on the relative methylation orderings of CpG sites

description: Accurate diagnosis of the origin of brain metastases (BMs) is crucial for tailoring an effective therapy to improve patients’ prognosis. BMs of unknown origin account for approximately 2–14% of patients with BMs. Hence, the aim of this study was to identify the original cancer type of BMs based on their DNA methylation profiles. The DNA methylation profiles of glioma (GM), BM, and seven other types of primary cancers were collected. In comparison with GM, the reversal CpG site pairs were identified for each of the seven other types of primary cancers based on the within-sample relative methylation orderings (RMOs) of the CpG sites. Then, using the reversal CpG site pairs, GMs were distinguished from BMs and the seven other types of primary cancers. All 61 of the GM samples were correctly identified as GM. The cancer type was also identified for the non-GM samples. For the seven other types of primary cancers, greater than 93% of samples of each cancer type were correctly identified as their corresponding cancer type, except for breast cancer, which had an 88% accuracy. For 133 BM samples, 132 BM samples were identified as non-GM, and 95% of the 133 BM samples were correctly classified into their corresponding original cancer types. The RMO-based method can accurately identify the origin of BMs, which is important for precision treatment.
DOI: 10.6084/m9.figshare.12994182
title: Identification of spliceosome components pivotal to breast cancer survival

description: Cancer cells employ alternative splicing (AS) to acquire splicing isoforms favouring their survival. However, the causes of aberrant AS in breast cancer are poorly understood. In this study, the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) data were analysed with univariate feature selection. Of 122 analysed spliceosome components, <i>U2SURP, PUF60, DDX41, HNRNPAB, EIF4A3</i>, and <i>PPIL3</i> were significantly associated with breast cancer survival. The top 4 four genes, <i>U2SURP, PUF60, DDX41</i>, and <i>HNRNPAB</i>, were chosen for further analyses. Their expression was significantly associated with cancer molecular subtype, tumour stage, tumour grade, overall survival (OS), and cancer-specific survival in the METABRIC data. These results were verifiable using other cohorts. The Cancer Genome Atlas data unveiled the elevated expression of <i>PUF60, DDX41</i>, and <i>HNRNPAB</i> in tumours compared with the normal tissue and confirmed the differential expression of the four genes among cancer molecular subtypes, as well as the associations of <i>U2SURP, PUF60</i>, and <i>DDX41</i> expression with tumour stage. A meta-analysis data verified the associations of <i>U2SURP, PUF60</i>, and <i>HNRNPAB</i> expression with tumour grade, the associations of <i>PUF60, DDX41</i>, and <i>HNRNPAB</i> expression with OS and distant metastasis-free survival, and the associations of <i>U2SURP</i> and <i>HNRNPAB</i> expression with relapse-free survival. Experimentally, we demonstrated that inhibiting the expression of the four genes separately suppressed cell colony formation and slowed down cell growth considerably in breast cancer cells, but not in immortal breast epithelial cells. In conclusion, we have identified <i>U2SURP, PUF60, DDX41</i>, and <i>HNRNPAB</i> are spliceosome-related genes pivotal for breast cancer survival.
DOI: 10.6084/m9.figshare.12994182.v1
title: Identification of spliceosome components pivotal to breast cancer survival

description: Cancer cells employ alternative splicing (AS) to acquire splicing isoforms favouring their survival. However, the causes of aberrant AS in breast cancer are poorly understood. In this study, the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) data were analysed with univariate feature selection. Of 122 analysed spliceosome components, <i>U2SURP, PUF60, DDX41, HNRNPAB, EIF4A3</i>, and <i>PPIL3</i> were significantly associated with breast cancer survival. The top 4 four genes, <i>U2SURP, PUF60, DDX41</i>, and <i>HNRNPAB</i>, were chosen for further analyses. Their expression was significantly associated with cancer molecular subtype, tumour stage, tumour grade, overall survival (OS), and cancer-specific survival in the METABRIC data. These results were verifiable using other cohorts. The Cancer Genome Atlas data unveiled the elevated expression of <i>PUF60, DDX41</i>, and <i>HNRNPAB</i> in tumours compared with the normal tissue and confirmed the differential expression of the four genes among cancer molecular subtypes, as well as the associations of <i>U2SURP, PUF60</i>, and <i>DDX41</i> expression with tumour stage. A meta-analysis data verified the associations of <i>U2SURP, PUF60</i>, and <i>HNRNPAB</i> expression with tumour grade, the associations of <i>PUF60, DDX41</i>, and <i>HNRNPAB</i> expression with OS and distant metastasis-free survival, and the associations of <i>U2SURP</i> and <i>HNRNPAB</i> expression with relapse-free survival. Experimentally, we demonstrated that inhibiting the expression of the four genes separately suppressed cell colony formation and slowed down cell growth considerably in breast cancer cells, but not in immortal breast epithelial cells. In conclusion, we have identified <i>U2SURP, PUF60, DDX41</i>, and <i>HNRNPAB</i> are spliceosome-related genes pivotal for breast cancer survival.
DOI: 10.6084/m9.figshare.21382796
title: Additional file 10 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 10: Table S5. The summary of lncRNAs exhibiting allele-specific expression in cultivated sunflower lines for edible fruit and oil identified in 12 DAP sunflower endosperm.
DOI: 10.6084/m9.figshare.21382802
title: Additional file 12 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 12: Table S7. GO Gene Ontology analysis of co-expressed protein-coding genes with lncRNAs of allelic bias toward cultivated lines for oil.
DOI: 10.6084/m9.figshare.21382796.v1
title: Additional file 10 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 10: Table S5. The summary of lncRNAs exhibiting allele-specific expression in cultivated sunflower lines for edible fruit and oil identified in 12 DAP sunflower endosperm.
DOI: 10.6084/m9.figshare.21382799
title: Additional file 11 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 11: Table S6. GO Gene Ontology analysis of co-expressed protein-coding genes with lncRNAs of allelic bias toward cultivated lines for edible fruit.
DOI: 10.6084/m9.figshare.21382802.v1
title: Additional file 12 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 12: Table S7. GO Gene Ontology analysis of co-expressed protein-coding genes with lncRNAs of allelic bias toward cultivated lines for oil.
DOI: 10.6084/m9.figshare.21382799.v1
title: Additional file 11 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 11: Table S6. GO Gene Ontology analysis of co-expressed protein-coding genes with lncRNAs of allelic bias toward cultivated lines for edible fruit.
DOI: 10.6084/m9.figshare.21382805
title: Additional file 13 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 13: Table S8. The annotation and homologs in Arabidopsis of these genes showing strong correlation with the lncRNAs were summarized in sunflower.
DOI: 10.6084/m9.figshare.21382805.v1
title: Additional file 13 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 13: Table S8. The annotation and homologs in Arabidopsis of these genes showing strong correlation with the lncRNAs were summarized in sunflower.
DOI: 10.6084/m9.figshare.21382811
title: Additional file 15 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 15. GTF File of candidate lncRNAs identified in sunflower endosperm.
DOI: 10.6084/m9.figshare.21382811.v1
title: Additional file 15 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 15. GTF File of candidate lncRNAs identified in sunflower endosperm.
DOI: 10.6084/m9.figshare.21382817
title: Additional file 2 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 2: Table S2. The genomic information of lncRNAs in sunflower endosperm at 12DAP.
DOI: 10.6084/m9.figshare.21382817.v1
title: Additional file 2 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 2: Table S2. The genomic information of lncRNAs in sunflower endosperm at 12DAP.
DOI: 10.6084/m9.figshare.21382820
title: Additional file 3 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 3: Table S3. GO Gene Ontology analysis of co-expressed protein-coding genes with all candidate lncRNAs.
DOI: 10.6084/m9.figshare.21382820.v1
title: Additional file 3 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 3: Table S3. GO Gene Ontology analysis of co-expressed protein-coding genes with all candidate lncRNAs.
DOI: 10.6084/m9.figshare.21382835
title: Additional file 8 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 8: Table S4. The summary of imprinted lncRNA identified in 12 DAP sunflower endosperm.
DOI: 10.6084/m9.figshare.21382835.v1
title: Additional file 8 of Genome-wide identification and characterization of lncRNAs in sunflower endosperm

description: Additional file 8: Table S4. The summary of imprinted lncRNA identified in 12 DAP sunflower endosperm.
DOI: 10.6084/m9.figshare.12994241
title: MetS Human Circulating EV miRNAs and mRNAs

description: EVs were collected from plasma of patients with MetS or
age-matched Lean controls (n=4 each). RNA-sequencing was performed to identify
dysregulated miRNAs and mRNAs.