cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21252378.v1
title: Supplementary Material for: Mechanism of glycitein in the treatment of colon cancer based on network pharmacology and molecular docking

description: Introduction: The prevalence of colon cancer remains high across the world. The early diagnosis of colon cancer is challenging. Moreover, patients with colon cancer frequently suffer from poor prognoses. Methods: Differentially expressed genes (DEGs) in colon cancer were acquired based on TCGA-COAD dataset screening. DEGs were input into the Connectivity Map (CMap) database to screen small molecule compounds with the potential to reverse colon cancer pathological function. Glycitein ranked first among the screened small molecule compounds. We downloaded the main targets of glycitein from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database and constructed protein-protein interaction (PPI) networks of those which were closely related to targets by Search Tool for the Retrieval of Interaction Gene/Proteins (STRING). Five potential targets of glycitein for treating colon cancer were identified (CCNA2, ESR1, ESR2, MAPK14, and PTGS2). These targets were used as seeds for random walk with restart (RWR) analysis of PPI networks. Then, the interaction network of glycitein-colon cancer-related genes was constructed based on the top 50 genes in affinity coefficients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the potential genes targeted by glycitein in colon cancer treatment and those were closely bound up with targets. Results: GO analysis demonstrated that the enrichment of these genes was primarily discovered in biological functions including regulation of fibroblast proliferation, response to oxygen levels, and epithelial cell proliferation. KEGG analysis results illustrated that the signaling pathways where these genes were mostly involved consisted of the mitogen-activated protein kinases signaling pathway, the phosphatidylinositol-3-kinase-Akt signaling pathway, and the p53 signaling pathway. Finally, stable binding of glycitein to five potential targets in colon cancer was verified by molecular docking. Conclusion: This study elucidated the key targets and main pathways of glycitein on the basis of network pharmacology and preliminarily analyzed molecular mechanisms in the treatment of colon cancer. A scientific basis is provided for glycitein application in treating colon cancer.
DOI: 10.6084/m9.figshare.21548601.v3
title: DRAVP:a comprehensive database of antiviral peptides and proteins

description: DRAVP is a comprehensive database of antiviral peptides and proteins. All data were manually collected from published literatures.
DOI: 10.6084/m9.figshare.21618806
title: etcomp_preprocessed_VP26

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618809
title: etcomp_preprocessed_VP3

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618812.v1
title: etcomp_preprocessed_VP4

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618803
title: etcomp_preprocessed_VP25

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618803.v1
title: etcomp_preprocessed_VP25

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618812
title: etcomp_preprocessed_VP4

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618800
title: etcomp_preprocessed_VP24

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618800.v1
title: etcomp_preprocessed_VP24

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618788
title: etcomp_preprocessed_VP22

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618797
title: etcomp_preprocessed_VP23

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618797.v1
title: etcomp_preprocessed_VP23

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618782
title: etcomp_preprocessed_VP2

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618782.v1
title: etcomp_preprocessed_VP2

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618785
title: etcomp_preprocessed_VP20

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618785.v1
title: etcomp_preprocessed_VP20

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618776
title: etcomp_preprocessed_VP15

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618776.v1
title: etcomp_preprocessed_VP15

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618779
title: etcomp_preprocessed_VP19

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618779.v1
title: etcomp_preprocessed_VP19

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618770.v1
title: etcomp_preprocessed_VP12

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618773
title: etcomp_preprocessed_VP14

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618806.v1
title: etcomp_preprocessed_VP26

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618764
title: etcomp_preprocessed_VP1

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618764.v1
title: etcomp_preprocessed_VP1

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618767
title: etcomp_preprocessed_VP11

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618770
title: etcomp_preprocessed_VP12

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618773.v1
title: etcomp_preprocessed_VP14

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21618767.v1
title: etcomp_preprocessed_VP11

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.5517/ccdc.csd.cc25x0hm
title: CCDC 2022920: Experimental Crystal Structure Determination

description: Related Article: Lihai Zhai, Zhaohua Zhang, Lihong Guo, Huaimin Dong, Junhou Yu, Guimin Zhang|2022|J.Pharm.Sci.|111|3224|doi:10.1016/j.xphs.2022.09.031
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.21548601.v4
title: DRAVP:a comprehensive database of antiviral peptides and proteins

description: DRAVP is a comprehensive database of antiviral peptides and proteins. All data were manually collected from published literatures.
DOI: 10.5517/ccdc.csd.cc283jgd
title: CCDC 2088763: Experimental Crystal Structure Determination

description: Related Article: Akachukwu D. Obi, Lucas A. Freeman, Samuel J. Coates, Andrew J. H. Alexis, Nathan C. Frey, Diane A. Dickie, Charles Edwin Webster, Robert J. Gilliard, Jr.|2022|Organometallics|41|3064|doi:10.1021/acs.organomet.2c00464
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.cc283jhf
title: CCDC 2088764: Experimental Crystal Structure Determination

description: Related Article: Akachukwu D. Obi, Lucas A. Freeman, Samuel J. Coates, Andrew J. H. Alexis, Nathan C. Frey, Diane A. Dickie, Charles Edwin Webster, Robert J. Gilliard, Jr.|2022|Organometallics|41|3064|doi:10.1021/acs.organomet.2c00464
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.cc283jjg
title: CCDC 2088765: Experimental Crystal Structure Determination

description: Related Article: Akachukwu D. Obi, Lucas A. Freeman, Samuel J. Coates, Andrew J. H. Alexis, Nathan C. Frey, Diane A. Dickie, Charles Edwin Webster, Robert J. Gilliard, Jr.|2022|Organometallics|41|3064|doi:10.1021/acs.organomet.2c00464
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.cc283jkh
title: CCDC 2088766: Experimental Crystal Structure Determination

description: Related Article: Akachukwu D. Obi, Lucas A. Freeman, Samuel J. Coates, Andrew J. H. Alexis, Nathan C. Frey, Diane A. Dickie, Charles Edwin Webster, Robert J. Gilliard, Jr.|2022|Organometallics|41|3064|doi:10.1021/acs.organomet.2c00464
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: 10.5281/zenodo.7357826
title: ES-PT, Advanced Driving, Automated Shuttle

description: Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Automated shuttle remote driving across borders</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency” User story: Automated shuttle remote driving across borders This use case is focussed in the deployment of last mile EV Automated shuttle vehicles in different environments:<br> - Cross Border environment: The shuttle will cover a route between Spain and Portugal connecting the cities of Tui and Valença through the old international bridge.<br> · Urban environment: The shuttle will cover a route in the city of Vigo. Scenario: Cooperative automated operation: In this scenario, the EV Autonomous shuttle is able to receive information coming from other actors (like a Vulnerable Road User) and adapt its behaviour according to specific needs.
DOI: 10.5281/zenodo.7357825
title: ES-PT, Advanced Driving, Automated Shuttle

description: Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Automated shuttle remote driving across borders</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency” User story: Automated shuttle remote driving across borders This use case is focussed in the deployment of last mile EV Automated shuttle vehicles in different environments:<br> - Cross Border environment: The shuttle will cover a route between Spain and Portugal connecting the cities of Tui and Valença through the old international bridge.<br> · Urban environment: The shuttle will cover a route in the city of Vigo. Scenario: Cooperative automated operation: In this scenario, the EV Autonomous shuttle is able to receive information coming from other actors (like a Vulnerable Road User) and adapt its behaviour according to specific needs.
DOI: 10.6084/m9.figshare.21548601.v5
title: DRAVP:a comprehensive database of antiviral peptides and proteins

description: DRAVP is a comprehensive database of antiviral peptides and proteins. All data were manually collected from published literatures.
DOI: 10.48670/moi-00277
title: Global ocean acidification - mean sea water pH trend map from Multi-Observations Reprocessing
DOI: 10.6084/m9.figshare.21629627
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.6084/m9.figshare.21629627.v2
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.6084/m9.figshare.21629627.v1
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.5281/zenodo.7371346
title: Office dataset - UdG

description: This document contains sensor data collected from an office environment. The office is located in Girona, Spain, and has a surface of 72 m<sup>2 </sup>.The dataset contains 10 min sample data of energy consumption, temperature (internal and external), humidity, precipitation, wind speed, noise, and state of doors and windows
DOI: 10.5281/zenodo.7371347
title: Office dataset - UdG

description: This document contains sensor data collected from an office environment. The office is located in Girona, Spain, and has a surface of 72 m<sup>2 </sup>.The dataset contains 10 min sample data of energy consumption, temperature (internal and external), humidity, precipitation, wind speed, noise, and state of doors and windows
DOI: 10.5281/zenodo.7371389
title: University campus buildings electrical and thermal demand and generation.

description: UVTgv has agreed to share data for both generation and consumption profile of their buildings. The load data is provided as one .csv per building and year with 8760 rows each one representing one hourly consumption of the building. The load datasets comprise 2019 and 2020 load data for electricity and heat demand, for the following buildings: ABR, C, ICSTM. The generation profiles provided are for 3 PV installations (generation profile), one solar thermal plant (capacity factor), and a mini-wind turbine (generation profile).
DOI: 10.5281/zenodo.7371390
title: University campus buildings electrical and thermal demand and generation.

description: UVTgv has agreed to share data for both generation and consumption profile of their buildings. The load data is provided as one .csv per building and year with 8760 rows each one representing one hourly consumption of the building. The load datasets comprise 2019 and 2020 load data for electricity and heat demand, for the following buildings: ABR, C, ICSTM. The generation profiles provided are for 3 PV installations (generation profile), one solar thermal plant (capacity factor), and a mini-wind turbine (generation profile).
DOI: 10.6084/m9.figshare.21629639.v1
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.6084/m9.figshare.21548601.v6
title: DRAVP:a comprehensive database of antiviral peptides and proteins

description: DRAVP is a comprehensive database of antiviral peptides and proteins. All data were manually collected from published literatures.
DOI: 10.6084/m9.figshare.21618788.v1
title: etcomp_preprocessed_VP22

description: Preprocessed data of Ehinger*,Groß*,Ibs,König 2019
DOI: 10.6084/m9.figshare.21629639
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.6084/m9.figshare.21629639.v3
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.6084/m9.figshare.21629639.v2
title: Supplemental Data for MPAN

description: Our proposed MPAN of the paper "Multi-phase Attention Network for Face Super-Resolution" builds on integrated residual attention groups (IRAG) and a concatenated attention module (CAM). The IRAG consists of residual channel attention blocks (RCAB) and an integrated attention module (IAM). My dataset contains supplemental data for this paper. These data include the structure of our proposed network, the quantitative results of algorithms and comparisons of algorithms on our face dataset.
DOI: 10.25402/cer.21629609
title: Health economic outcomes of switching to alemtuzumab from other disease-modifying therapies in people with multiple sclerosis in the USA: supplementary materials

description: Aim: Describe demographics, clinical characteristics, healthcare resource utilization (HCRU) and costs in people with multiple sclerosis (pwMS) switching to alemtuzumab from other disease-modifying therapies (DMTs). Patients & methods: Retrospective, observational study of IBM R ? MarketScan R ? claims database. PwMS previously treated with DMTs and initiating alemtuzumab (1 January 2013 to 31 December 2019) were identified. “Index” was date of alemtuzumab initiation (prescription filled). Results: The study cohort (n = 341) was primarily female (72%) with (mean ± standard deviation) age 45.1 ± 9.5 years. At index, duration of MS was 5.3 ± 2.8 years. HCRU (inpatient/outpatient services), outpatient costs (including MS-specific MRI and emergency room visits) and annualized relapse rate significantly reduced over the 2 years following initiation of alemtuzumab. DMT costs reduced over the same period. Conclusion: Health economic and clinical benefits were seen following switching to alemtuzumab from other DMTs for treatment of MS, in this cohort from the USA.
DOI: 10.25402/cer.21629609.v1
title: Health economic outcomes of switching to alemtuzumab from other disease-modifying therapies in people with multiple sclerosis in the USA: supplementary materials

description: Aim: Describe demographics, clinical characteristics, healthcare resource utilization (HCRU) and costs in people with multiple sclerosis (pwMS) switching to alemtuzumab from other disease-modifying therapies (DMTs). Patients & methods: Retrospective, observational study of IBM R ? MarketScan R ? claims database. PwMS previously treated with DMTs and initiating alemtuzumab (1 January 2013 to 31 December 2019) were identified. “Index” was date of alemtuzumab initiation (prescription filled). Results: The study cohort (n = 341) was primarily female (72%) with (mean ± standard deviation) age 45.1 ± 9.5 years. At index, duration of MS was 5.3 ± 2.8 years. HCRU (inpatient/outpatient services), outpatient costs (including MS-specific MRI and emergency room visits) and annualized relapse rate significantly reduced over the 2 years following initiation of alemtuzumab. DMT costs reduced over the same period. Conclusion: Health economic and clinical benefits were seen following switching to alemtuzumab from other DMTs for treatment of MS, in this cohort from the USA.