cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2grgtj
title: CCDC 2286678: Experimental Crystal Structure Determination

description: Related Article: Xiong Sun, Zhuoyi Xie, Shuyi Li, Hanfei Cao, Yeli Fan, Pinggui Li, Lianghua Zou|2024|Polyhedron|249|116773|doi:10.1016/j.poly.2023.116773
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2grgvk
title: CCDC 2286679: Experimental Crystal Structure Determination

description: Related Article: Xiong Sun, Zhuoyi Xie, Shuyi Li, Hanfei Cao, Yeli Fan, Pinggui Li, Lianghua Zou|2024|Polyhedron|249|116773|doi:10.1016/j.poly.2023.116773
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gs7q7
title: CCDC 2287419: Experimental Crystal Structure Determination

description: Related Article: A.A. Ulantikov, K.D. Podolets, T.S. Sukhikh, Y.V. Mironov, K.A. Brylev, Y.M. Gayfulin|2024|Polyhedron|247|116737|doi:10.1016/j.poly.2023.116737
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gs7r8
title: CCDC 2287420: Experimental Crystal Structure Determination

description: Related Article: A.A. Ulantikov, K.D. Podolets, T.S. Sukhikh, Y.V. Mironov, K.A. Brylev, Y.M. Gayfulin|2024|Polyhedron|247|116737|doi:10.1016/j.poly.2023.116737
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ffm5p
title: CCDC 2247412: Experimental Crystal Structure Determination

description: Related Article: Meng-Le Yang, Hong-Tao Cui, Kai-Li Hui, Jun Ying, Ai-Xiang Tian|2024|Polyhedron|247|116742|doi:10.1016/j.poly.2023.116742
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ffm6q
title: CCDC 2247413: Experimental Crystal Structure Determination

description: Related Article: Meng-Le Yang, Hong-Tao Cui, Kai-Li Hui, Jun Ying, Ai-Xiang Tian|2024|Polyhedron|247|116742|doi:10.1016/j.poly.2023.116742
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ffn1l
title: CCDC 2247439: Experimental Crystal Structure Determination

description: Related Article: Meng-Le Yang, Hong-Tao Cui, Kai-Li Hui, Jun Ying, Ai-Xiang Tian|2024|Polyhedron|247|116742|doi:10.1016/j.poly.2023.116742
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ffw5y
title: CCDC 2247660: Experimental Crystal Structure Determination

description: Related Article: Meng-Le Yang, Hong-Tao Cui, Kai-Li Hui, Jun Ying, Ai-Xiang Tian|2024|Polyhedron|247|116742|doi:10.1016/j.poly.2023.116742
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gvb4t
title: CCDC 2289416: Experimental Crystal Structure Determination

description: Related Article: yongqiang mei|2023|CSD Communication|||
description: Related Article: Yongqiang Mei, Ying Lan, Deli Li, Jiahui Wang, Lijuan Xie, Xiaomei Peng, Jiuyan Li, Di Liu, Shi-Jian Su|2024|Chem.Eng.Journal|480|148351|doi:10.1016/j.cej.2023.148351
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h6dx1
title: CCDC 2300073: Experimental Crystal Structure Determination

description: Related Article: Mathew D. Anker, Matthew J. Evans, Scott A. Cameron, Geoffry Laufersky|2023|Polyhedron|247|116741|doi:10.1016/j.poly.2023.116741
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h6dy2
title: CCDC 2300074: Experimental Crystal Structure Determination

description: Related Article: Mathew D. Anker, Matthew J. Evans, Scott A. Cameron, Geoffry Laufersky|2023|Polyhedron|247|116741|doi:10.1016/j.poly.2023.116741
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h6dz3
title: CCDC 2300075: Experimental Crystal Structure Determination

description: Related Article: Mathew D. Anker, Matthew J. Evans, Scott A. Cameron, Geoffry Laufersky|2023|Polyhedron|247|116741|doi:10.1016/j.poly.2023.116741
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h6f05
title: CCDC 2300076: Experimental Crystal Structure Determination

description: Related Article: Mathew D. Anker, Matthew J. Evans, Scott A. Cameron, Geoffry Laufersky|2023|Polyhedron|247|116741|doi:10.1016/j.poly.2023.116741
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h6f16
title: CCDC 2300077: Experimental Crystal Structure Determination

description: Related Article: Mathew D. Anker, Matthew J. Evans, Scott A. Cameron, Geoffry Laufersky|2023|Polyhedron|247|116741|doi:10.1016/j.poly.2023.116741
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hbtsg
title: CCDC 2304316: Experimental Crystal Structure Determination

description: Related Article: Gabrielle Audsley, Ambre Carpentier, Anne-Frédérique Pécharman, James Wright, Thomas M. Roseveare, Ewan R. Clark, Stuart A. Macgregor, Ian M. Riddlestone|2024|Chem.Commun.|60|874|doi:10.1039/D3CC05369E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hbtth
title: CCDC 2304317: Experimental Crystal Structure Determination

description: Related Article: Gabrielle Audsley, Ambre Carpentier, Anne-Frédérique Pécharman, James Wright, Thomas M. Roseveare, Ewan R. Clark, Stuart A. Macgregor, Ian M. Riddlestone|2024|Chem.Commun.|60|874|doi:10.1039/D3CC05369E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hcw6z
title: CCDC 2305321: Experimental Crystal Structure Determination

description: Related Article: Arulraj Ramalingam, Chinnaraja Duraisamy, Hitler Louis, Rajalakshmi Ramarajan, Anna Imojara, Sivakumar Sambandam, Innocent Benjamin|2024|J.Mol.Struct.|1299|137031|doi:10.1016/j.molstruc.2023.137031
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28wh6w
title: CCDC 2111788: Experimental Crystal Structure Determination

description: Related Article: Liang-Liang Yan, Vivian Wing-Wah Yam|2023|J.Am.Chem.Soc.|146|609|doi:10.1021/jacs.3c10381
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.24845742
title: Dataset: Scattered tree death contributes to substantial forest loss in California

description: Tree mortality maps derived from aerial photos (NAIP) of 2020 in California for the paper titled Scattered tree death contributes to substantial forest loss in California. The dataset includes dead tree count per ha (100 m), median dead crown size per ha (100 m), percentage of dead canopy area per ha (100 m), percentage of brown-stage mortality per ha (100 m), eccentricity map (500 m), and percentage of tree mortality (240 m). The spatial coverage is the vegetated area (woody vegetation) in California. The projection system is EPSG:5072.Publication: <i>Cheng, Y.</i> <i>et al.</i> Scattered tree death contributes to substantial forest loss in California. <i>Nat. Commun. </i>(2024). https://doi.org/10.1038/s41467-024-44991-z<br>
DOI: 10.6084/m9.figshare.24845742.v2
title: Dataset: Scattered tree death contributes to substantial forest loss in California

description: Tree mortality maps derived from aerial photos (NAIP) of 2020 in California for the paper titled Scattered tree death contributes to substantial forest loss in California.The dataset includes dead tree count per ha (100 m), median dead crown size per ha (100 m), percentage of dead canopy area per ha (100 m), percentage of brown-stage mortality per ha (100 m), eccentricity map (500 m), and percentage of tree mortality (240 m). The spatial coverage is the vegetated area (woody vegetation) in California. The projection system is EPSG:5072.
DOI: 10.15161/oar.it/143342
title: Carta Geologica d'Italia alla scala 1:50.000, F. 641 Augusta

description: Foglio geologico alla scala 1:50.000 basato su rilevamenti alla scala 1:10.000 (eseguiti tra il 2006 e il 2008) comprensivo di legenda, schemi a cornice, sezioni geologiche.
DOI: 10.15161/oar.it/143343
title: Carta Geologica d'Italia alla scala 1:50.000, F. 641 Augusta

description: Foglio geologico alla scala 1:50.000 basato su rilevamenti alla scala 1:10.000 (eseguiti tra il 2006 e il 2008) comprensivo di legenda, schemi a cornice, sezioni geologiche.
DOI: 10.5281/zenodo.10532579
title: Dataset related to article "The prognostic power of [11C]methionine PET in IDH-wildtype diffuse gliomas with lower-grade histological features: venturing beyond WHO classification"

description: This record contains raw data related to article “The prognostic power of [11C]methionine PET in IDH-wildtype diffuse gliomas with lower-grade histological features: venturing beyond WHO classification"

Abstract



 Purpose:  IDH-wildtype (IDH-wt) diffuse gliomas with histological features of lower-grade gliomas (LGGs) are rare and heterogeneous primary brain tumours. [11C]Methionine (MET) positron emission tomography (PET) is commonly used to evaluate glial neoplasms at diagnosis. The present study aimed to assess the prognostic value of MET PET in newly diagnosed, treatment naïve IDH-wt gliomas with histological features of LGGs.

 Methods:  Patients with a histological diagnosis of IDH-wt LGG who underwent preoperative (< 100 days) MET PET/CT and surgery were retrospectively included. Qualitative and semi-quantitative analyses of MET PET images were performed. Progression-free survival (PFS) and overall survival (OS) were analysed by Kaplan-Meier curves. Cox proportional-hazards regression was used to test the association of imaging and clinical data to PFS and OS.

 Results:  We included 48 patients (M:F = 25:23; median age 55). 39 lesions were positive and 9 negative at MET PET. Positive MET PET was significantly associated with shorter median PFS (15.7 months vs. not reached, p = 0.0146) and OS time (32.6 months vs. not reached, p = 0.0253). Incomplete surgical resection and higher TBRmean values were independent predictors of shorter PFS on multivariate analysis (p < 0.001 for both). Higher tumour grade and incomplete surgical resection were independent predictors of OS at multivariate analysis (p = 0.027 and p = 0.01, respectively).

 Conclusion:  MET PET is useful for the prognostic stratification of patients with IDH-wt glial neoplasms with histological LGGs features. Considering their huge biological heterogeneity, the combination of MET PET and molecular analyses may help to improve the prognostic accuracy in these diffuse gliomas subset and influence therapeutic choices accordingly.
DOI: 10.5281/zenodo.10532580
title: Dataset related to article "The prognostic power of [11C]methionine PET in IDH-wildtype diffuse gliomas with lower-grade histological features: venturing beyond WHO classification"

description: This record contains raw data related to article “The prognostic power of [11C]methionine PET in IDH-wildtype diffuse gliomas with lower-grade histological features: venturing beyond WHO classification"

Abstract



 Purpose:  IDH-wildtype (IDH-wt) diffuse gliomas with histological features of lower-grade gliomas (LGGs) are rare and heterogeneous primary brain tumours. [11C]Methionine (MET) positron emission tomography (PET) is commonly used to evaluate glial neoplasms at diagnosis. The present study aimed to assess the prognostic value of MET PET in newly diagnosed, treatment naïve IDH-wt gliomas with histological features of LGGs.

 Methods:  Patients with a histological diagnosis of IDH-wt LGG who underwent preoperative (< 100 days) MET PET/CT and surgery were retrospectively included. Qualitative and semi-quantitative analyses of MET PET images were performed. Progression-free survival (PFS) and overall survival (OS) were analysed by Kaplan-Meier curves. Cox proportional-hazards regression was used to test the association of imaging and clinical data to PFS and OS.

 Results:  We included 48 patients (M:F = 25:23; median age 55). 39 lesions were positive and 9 negative at MET PET. Positive MET PET was significantly associated with shorter median PFS (15.7 months vs. not reached, p = 0.0146) and OS time (32.6 months vs. not reached, p = 0.0253). Incomplete surgical resection and higher TBRmean values were independent predictors of shorter PFS on multivariate analysis (p < 0.001 for both). Higher tumour grade and incomplete surgical resection were independent predictors of OS at multivariate analysis (p = 0.027 and p = 0.01, respectively).

 Conclusion:  MET PET is useful for the prognostic stratification of patients with IDH-wt glial neoplasms with histological LGGs features. Considering their huge biological heterogeneity, the combination of MET PET and molecular analyses may help to improve the prognostic accuracy in these diffuse gliomas subset and influence therapeutic choices accordingly.
DOI: 10.5281/zenodo.10532669
title: Microtime Machine New

description: Microtime Machine 1.02 Project new Version included
DOI: 10.5281/zenodo.10532670
title: Microtime Machine New

description: Microtime Machine 1.02 Project new Version included
DOI: 10.5281/zenodo.10458940
title: Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping
title: TCGA data with artificial confounding effect

description: TCGA pan-cancer mRNA and DNA data augmented with artificial confounders utilised in "Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping" by Zuqi Li and Sonja Katz (manuscript in preparation).

The following data curation steps were carried out: 



Step 1. Download data from TCGA



R package `TCGAbiolinks`

2547 patients (after step 2) with 6 cancer types:



BRCA (731)

THCA (408)

BLCA (387)

LUSC (297)

HNSC (412)

KIRC (312)



mRNA expression profiles

DNAm expression profiles

Clinical data:



tumor stage: i, ia, ib, ii, iia, iib, iii, iiia, iiib, iiic, iv, iva, ivb, ivc, x

age at diagnosis

race: 'white', 'black or african amarican', 'asian', 'american indian or alaska native'

gender





Step 2. Removal criteria



Patients with



NA or 'not reported' clinical data

race 'american indian or alaska native'

tumor stage x



mRNA and DNAm probes with



0 variance across all included patients

not shared across all cancer types

with missing values





 Step 3. Encode clinical vairables and save datasets



mRNA dataset: 2547 patients x 58,456 mRNAs

DNAm dataset: 2547 patients x 232,088 DNAm

clinic dataset: 2547 patients x 6 variables    1. patient ID    2. tumor stage: 1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4    3. age at diagnosis    4. race: asian(1), black or african amarican(2), white(3)    5. gender: female(0), male(1)    6. cancer type: BRCA(1), THCA(2), BLCA(3), LUSC(4), HNSC(5), KIRC(6)    



 Step 4. Pre-process the datasets



mRNA dataset: 'TCGA_mRNAs_processed.csv'



Take the 2000 mRNAs with highest variance

Rescale every feature to [0,1]

--> 2547 patients x 2000 mRNAs



DNAm dataset: 'TCGA_DNAm_processed.csv'



Take the 2000 DNAm with highest variance

Rescale every feature to [0,1]

--> 2547 patients x 2000 DNAm



clinic dataset: 'TCGA_clinic.csv'



Step 5. Simulate confounders (instructions can be found in Methods section of manuscript)



Linear confounder:



'TCGA_confounder_linear.csv' - linear confounding classes

'TCGA_DNAm_confounded_linear.csv' - linearly confounded DNAm data

'TCGA_mRNA2_confounded_linear.csv'  - linearly confounded mRNA data



Squared confounder



'TCGA_confounder.csv' - squared confounding classes

'TCGA_DNAm_confounded.csv' - squared confounded DNAm data

'TCGA_mRNA2_confounded.csv'  - squared confounded mRNA data



Categorical confounder 



'TCGA_confounder_categ2.csv' - categorical confounding classes

'TCGA_DNAm_confounded_categ2.csv' - categorically confounded DNAm data

'TCGA_mRNA2_confounded_categ2.csv'  - categorically  confounded mRNA data



Multiple confounders - combined effect (linear + squared + categorical)



'TCGA_confounder_multi.csv' - confounding classes for combined effect

'TCGA_DNAm_confounded_multi.csv' - DNAm data with combined effect

'TCGA_mRNA2_confounded_multi.csv'  - mRNA data with combined effect