cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10094990
title: VEBA Test Dataset

description: # Testing Data
The following fastq files are subsets of the original SRA sequences designed for getting assemblies that have prokaryotic, eukaryotic, and viral genomes.
| id_sample | source_sra  | format | type | num_seqs | min_len | avg_len | max_len | GC(%) ||-----------|-------------|--------|------|----------|---------|---------|---------|-------|| S1        | SRR17458614 | FASTQ  | DNA  | 1474203  | 75      | 150.5   | 151     | 46.91 || S2        | SRR17458615 | FASTQ  | DNA  | 1638398  | 75      | 150.5   | 151     | 46.92 || S3        | SRR17458630 | FASTQ  | DNA  | 2389989  | 75      | 150.4   | 151     | 56.38 || S4        | SRR17458638 | FASTQ  | DNA  | 3142566  | 75      | 150.5   | 151     | 46.34 |
 
Also includes the following: 

Metagenomic assemblies using metaSPAdes with sorted BAM files from Bowtie2
Genomes, gene models, etc.
Taxonomy classifications at the genome and genome cluster level
Annotations for genes and protein clusters
Biosynthetic gene clusters
Clusters for genomes and proteins
DOI: 10.5281/zenodo.7943343
title: VEBA Test Dataset

description: # Testing Data
The following fastq files are subsets of the original SRA sequences designed for getting assemblies that have prokaryotic, eukaryotic, and viral genomes.
| id_sample | source_sra  | format | type | num_seqs | min_len | avg_len | max_len | GC(%) ||-----------|-------------|--------|------|----------|---------|---------|---------|-------|| S1        | SRR17458614 | FASTQ  | DNA  | 1474203  | 75      | 150.5   | 151     | 46.91 || S2        | SRR17458615 | FASTQ  | DNA  | 1638398  | 75      | 150.5   | 151     | 46.92 || S3        | SRR17458630 | FASTQ  | DNA  | 2389989  | 75      | 150.4   | 151     | 56.38 || S4        | SRR17458638 | FASTQ  | DNA  | 3142566  | 75      | 150.5   | 151     | 46.34 |
 
Also includes the following: 

Metagenomic assemblies using metaSPAdes with sorted BAM files from Bowtie2
Genomes, gene models, etc.
Taxonomy classifications at the genome and genome cluster level
Annotations for genes and protein clusters
Biosynthetic gene clusters
Clusters for genomes and proteins
DOI: 10.5281/zenodo.7943344
title: VEBA Test Fastq

description: Fastq read subset from the following SRA: SRR17458614 S1<br> SRR17458615 S2<br> SRR17458630 S3<br> SRR17458638 S4 <br>
DOI: 10.5281/zenodo.7946802
title: VEBA Test Fastq

description: # Testing Data The following fastq files are subsets of the original SRA sequences designed for getting assemblies that have prokaryotic, eukaryotic, and viral genomes. | id_sample | source_sra | format | type | num_seqs | min_len | avg_len | max_len | GC(%) |<br> |-----------|-------------|--------|------|----------|---------|---------|---------|-------|<br> | S1 | SRR17458614 | FASTQ | DNA | 1474203 | 75 | 150.5 | 151 | 46.91 |<br> | S2 | SRR17458615 | FASTQ | DNA | 1638398 | 75 | 150.5 | 151 | 46.92 |<br> | S3 | SRR17458630 | FASTQ | DNA | 2389989 | 75 | 150.4 | 151 | 56.38 |<br> | S4 | SRR17458638 | FASTQ | DNA | 3142566 | 75 | 150.5 | 151 | 46.34 |
DOI: 10.57995/jvsx-sj29
title: Chapter 5: adipose tissue histology comparison between grey seal and human

description: Seals accumulate large amount of fat in the subcutaneous adipose tissue, which undergoes massive changes during their life cycle. This study aims to describe the differences in subcutaneous adipose tissue structure between adult female grey seals and adult female humans in terms of adipocyte morphology and collagen.

The data were collected as part of the PhD project "Characterising fat tissue structure and function in response to hypoxia in grey seals, an animal model of extreme fat deposition and mobilisation, using novel in vivo and in vitro approaches".
DOI: 10.5281/zenodo.10103322
title: Argentina National Map of Crops 2022/2023
title: Mapa Nacional de Cultivos de Argentina Campaña 2022/2023

description: Crop type map covering the main agricultural areas of Argentina for growing season 2022/2023. This version includes two different maps for winter and summer crops. Maps were generated using supervised classification methods with samples obtained from on-road surveys and Landsat satellite images along the growing season. Files provided include a Geotiff version of each map with a resolution of 30 m and legend style files. The report includes the methodological details, map legend and accuracy assessments (in Spanish). A web visualizer can be accessed through the following link: https://deabelle.users.earthengine.app/view/mnc22-23
DOI: 10.5281/zenodo.3764691
title: deleted

description: National Olympiads are organized annually by the Ministry of Education and Training, Vietnam to identify and foster talented students at the upper secondary level.
DOI: 10.5281/zenodo.3764692
title: deleted

description: National Olympiads are organized annually by the Ministry of Education and Training, Vietnam to identify and foster talented students at the upper secondary level.
DOI: 10.5281/zenodo.10106405
title: Thermal and mechanical properties of PBSA and BIOCHAR blends
DOI: 10.5281/zenodo.10106406
title: Thermal and mechanical properties of PBSA and BIOCHAR blends
DOI: 10.5287/ora-qod6aprpg
title: Cochrane review of electronic cigarettes for smoking cessation

description: Supplementary tables 1-10 for the update to the Cochrane review of electronic cigarettes for smoking cessation. Once accepted the DOI for the publication will be: 10.1002/14651858.CD010216.pub8
DOI: 10.57995/5jaz-ez93
title: Molecular shifts induced by hypoxia in grey seal blubber: an in vitro approach

description: Seals blubber undergo oxygen availability restrictions during diving and fattening. This study aims to better understand what are the molecular pathways affected by hypoxia in an in vitro model using blubber explants and chemically induced hypoxia. 

The data were collected as part of the PhD project "Characterising fat tissue structure and function in response to hypoxia in grey seals, an animal model of extreme fat deposition and mobilisation, using novel in vivo and in vitro approaches".
DOI: 10.5281/zenodo.10050367
title: Dataset of the HazardNet: A Thermal Hazard Prediction Framework for Datacenters

description: This dataset entry showcases a comprehensive collection obtained from the Tier-0 supercomputer, Marconi A2, hosted at CINECA (https://www.hpc.cineca.it/). The dataset records inlet and outlet temperatures along with power consumption data from 3312 computing nodes, spanning from January 14, 2019, to December 31, 2019. The data is generated through ExaMon, a sophisticated monitoring datacenter infrastructure. The primary objective of this dataset is to support the research and development of HazardNet, an innovative thermal hazard prediction framework tailored specifically for datacenters. HazardNet integrates a comprehensive pipeline of machine-learning models. Researchers and enthusiasts interested in exploring our work further can find the complete set of codes and machine-learning models at our GitHub repository: https://github.com/MSKazemi/HazardNet
DOI: 10.5281/zenodo.10050368
title: Dataset of the HazardNet: A Thermal Hazard Prediction Framework for Datacenters

description: This dataset entry showcases a comprehensive collection obtained from the Tier-0 supercomputer, Marconi A2, hosted at CINECA (https://www.hpc.cineca.it/). The dataset records inlet and outlet temperatures along with power consumption data from 3312 computing nodes, spanning from January 14, 2019, to December 31, 2019. The data is generated through ExaMon, a sophisticated monitoring datacenter infrastructure. The primary objective of this dataset is to support the research and development of HazardNet, an innovative thermal hazard prediction framework tailored specifically for datacenters. HazardNet integrates a comprehensive pipeline of machine-learning models. Researchers and enthusiasts interested in exploring our work further can find the complete set of codes and machine-learning models at our GitHub repository: https://github.com/MSKazemi/HazardNet
DOI: 10.6084/m9.figshare.22709529
title: The seamless integration of dietary plant-derived natural flavonoids and gut microbiota may ameliorate non-alcoholic fatty liver disease: a network pharmacology analysis

description: We comprised metabolites of gut microbiota (GM; endogenous species) and dietary plant-derived natural flavonoids (DPDNFs; exogenous species) were known as potent effectors against non-alcoholic fatty liver disease (NAFLD) <i>via</i> network pharmacology (NP). The crucial targets against NAFLD were identified <i>via</i> GM and DPDNFs. The protein interaction (PPI), bubble chart and networks of GM or natural products- metabolites-targets-key signalling (GNMTK) pathway were described <i>via</i> R Package. Furthermore, the molecular docking test (MDT) to verify the affinity was performed between metabolite(s) and target(s) on a key signalling pathway. On the networks of GNMTK, <i>Enterococcus sp. 45</i>, <i>Escherichia sp.12</i>, <i>Escherichia sp.33</i> and <i>Bacterium MRG-PMF-1</i> as key microbiota; flavonoid-rich products as key natural resources; luteolin and myricetin as key metabolites (or dietary flavonoids); AKT Serine/Threonine Kinase 1 (AKT1), CF Transmembrane conductance Regulator (CFTR) and PhosphoInositide-3-Kinase, Regulatory subunit 1 (PIK3R1) as key targets are promising components to treat NAFLD, by suppressing cyclic Adenosine MonoPhosphate (cAMP) signalling pathway. This study shows that components (microbiota, metabolites, targets and a key signalling pathway) and DPDNFs can exert combinatorial pharmacological effects against NAFLD. Overall, the integrated pharmacological approach sheds light on the relationships between GM and DPDNFs.
DOI: 10.6084/m9.figshare.22709529.v1
title: The seamless integration of dietary plant-derived natural flavonoids and gut microbiota may ameliorate non-alcoholic fatty liver disease: a network pharmacology analysis

description: We comprised metabolites of gut microbiota (GM; endogenous species) and dietary plant-derived natural flavonoids (DPDNFs; exogenous species) were known as potent effectors against non-alcoholic fatty liver disease (NAFLD) <i>via</i> network pharmacology (NP). The crucial targets against NAFLD were identified <i>via</i> GM and DPDNFs. The protein interaction (PPI), bubble chart and networks of GM or natural products- metabolites-targets-key signalling (GNMTK) pathway were described <i>via</i> R Package. Furthermore, the molecular docking test (MDT) to verify the affinity was performed between metabolite(s) and target(s) on a key signalling pathway. On the networks of GNMTK, <i>Enterococcus sp. 45</i>, <i>Escherichia sp.12</i>, <i>Escherichia sp.33</i> and <i>Bacterium MRG-PMF-1</i> as key microbiota; flavonoid-rich products as key natural resources; luteolin and myricetin as key metabolites (or dietary flavonoids); AKT Serine/Threonine Kinase 1 (AKT1), CF Transmembrane conductance Regulator (CFTR) and PhosphoInositide-3-Kinase, Regulatory subunit 1 (PIK3R1) as key targets are promising components to treat NAFLD, by suppressing cyclic Adenosine MonoPhosphate (cAMP) signalling pathway. This study shows that components (microbiota, metabolites, targets and a key signalling pathway) and DPDNFs can exert combinatorial pharmacological effects against NAFLD. Overall, the integrated pharmacological approach sheds light on the relationships between GM and DPDNFs.
DOI: 10.6084/m9.figshare.22894283
title: Therapeutic ultrasound treatment for the prevention of chronic kidney disease-associated muscle wasting in mice

description: Low-intensity pulsed ultrasound (LIPUS) is a kind of therapeutic ultrasound. It can help improve bone fracture repair and soft tissue healing. Our previous study found that LIPUS treatment could halt the chronic kidney disease (CKD) progression in mice; unexpectedly, we observed the improvement of CKD-reduced muscle weights by LIPUS treatment. Here, we further tested the protective potential of LIPUS on CKD-associated muscle wasting/sarcopenia using the CKD mouse models. Mouse models of both unilateral renal ischemia/reperfusion injury (IRI) with nephrectomy and adenine administration were used to induce CKD. LIPUS with condition of 3 MHz, 100 mW/cm<sup>2</sup>, 20 min/day was applied to the kidney of CKD mice. LIPUS treatment significantly reversed the increased serum BUN/creatinine levels in CKD mice. LIPUS effectively prevented the decrease in grip strength, muscle weight (soleus, tibialis anterior, and gastrocnemius muscles), cross-section areas of muscle fibres, and muscular phosphorylated Akt protein expression by immunohistochemistry, and the increase in muscular atrogenes Atrogin1 and MuRF1 protein expression by immunohistochemistry in CKD mice. These results indicated that LIPUS could help improve weak muscle strength, muscle mass loss, muscle atrophy-related protein expression, and Akt inactivation. LIPUS application may be an alternative non-invasive therapeutic intervention on the management of CKD-associated muscle wasting.
DOI: 10.6084/m9.figshare.24132711
title: New insight into gut microbiota-derived metabolites to enhance liver regeneration via network pharmacology study

description: We intended to identify favourable metabolite(s) and pharmacological mechanism(s) of gut microbiota (GM) for liver regeneration (LR) through network pharmacology. We utilized the gutMGene database to obtain metabolites of GM, and targets associated with metabolites as well as LR-related targets were identified using public databases. Furthermore, we performed a molecular docking assay on the active metabolite(s) and target(s) to verify the network pharmacological concept. We mined a total of 208 metabolites in the gutMGene database and selected 668 targets from the SEA (1,256 targets) and STP (947 targets) databases. Finally, 13 targets were identified between 61 targets and the gutMGene database (243 targets). Protein–protein interaction network analysis showed that AKT1 is a hub target correlated with 12 additional targets. In this study, we describe the potential microbe from the microbiota (<i>E. coli</i>), chemokine signalling pathway, AKT1 and myricetin that accelerate LR, providing scientific evidence for further clinical trials.
DOI: 10.6084/m9.figshare.24132711.v1
title: New insight into gut microbiota-derived metabolites to enhance liver regeneration via network pharmacology study

description: We intended to identify favourable metabolite(s) and pharmacological mechanism(s) of gut microbiota (GM) for liver regeneration (LR) through network pharmacology. We utilized the gutMGene database to obtain metabolites of GM, and targets associated with metabolites as well as LR-related targets were identified using public databases. Furthermore, we performed a molecular docking assay on the active metabolite(s) and target(s) to verify the network pharmacological concept. We mined a total of 208 metabolites in the gutMGene database and selected 668 targets from the SEA (1,256 targets) and STP (947 targets) databases. Finally, 13 targets were identified between 61 targets and the gutMGene database (243 targets). Protein–protein interaction network analysis showed that AKT1 is a hub target correlated with 12 additional targets. In this study, we describe the potential microbe from the microbiota (<i>E. coli</i>), chemokine signalling pathway, AKT1 and myricetin that accelerate LR, providing scientific evidence for further clinical trials.
DOI: 10.6084/m9.figshare.22894283.v1
title: Therapeutic ultrasound treatment for the prevention of chronic kidney disease-associated muscle wasting in mice

description: Low-intensity pulsed ultrasound (LIPUS) is a kind of therapeutic ultrasound. It can help improve bone fracture repair and soft tissue healing. Our previous study found that LIPUS treatment could halt the chronic kidney disease (CKD) progression in mice; unexpectedly, we observed the improvement of CKD-reduced muscle weights by LIPUS treatment. Here, we further tested the protective potential of LIPUS on CKD-associated muscle wasting/sarcopenia using the CKD mouse models. Mouse models of both unilateral renal ischemia/reperfusion injury (IRI) with nephrectomy and adenine administration were used to induce CKD. LIPUS with condition of 3 MHz, 100 mW/cm<sup>2</sup>, 20 min/day was applied to the kidney of CKD mice. LIPUS treatment significantly reversed the increased serum BUN/creatinine levels in CKD mice. LIPUS effectively prevented the decrease in grip strength, muscle weight (soleus, tibialis anterior, and gastrocnemius muscles), cross-section areas of muscle fibres, and muscular phosphorylated Akt protein expression by immunohistochemistry, and the increase in muscular atrogenes Atrogin1 and MuRF1 protein expression by immunohistochemistry in CKD mice. These results indicated that LIPUS could help improve weak muscle strength, muscle mass loss, muscle atrophy-related protein expression, and Akt inactivation. LIPUS application may be an alternative non-invasive therapeutic intervention on the management of CKD-associated muscle wasting.
DOI: 10.5281/zenodo.10103767
title: Reactome modified for tracing ArangoDB version

description: Reactome database download and customization
The Reactome database [1,2] was downloaded as a neo4j graph database (https://reactome.org/download-data version 75), which is covered by the Creative Commons Attribution 4.0 International (CC BY 4.0) license. A series of database queries was used to generate a database version suitable for graph data science which can be followed in detail in the attached Jupyter notebook (Or at GDS-Public/notebooks/reactome/Reactome GDS.ipynb at main · SBRG/GDS-Public (github.com)). 
Nodes, labels and relationships not required for graph algorithmic analyses were removed. For instance, this included nodes like person, affiliation, and taxa as well as all nodes representing entities of organisms other than Homo sapiens. Subcellular locations (compartments) of biological entities were set as node properties. To allow for improved graph traversal, selected relationships were reversed or added. Because currency metabolites, e.g. ATP, NAD(P)H and H+, can artificially connect metabolic reactions and pathways in network analyses [3,4], we labelled such compounds plus the regulatory protein ubiquitin accordingly and thereby excluded them from all analyses. Finally, the database was transformed into an ArangoDB graph database consisting of 1,703,054 nodes and 3,368,926 edges. 
References
1.  Gillespie, M. et al. The reactome pathway knowledgebase 2022. Nucleic Acids Research 50, D687–D692 (2022).
2.  Fabregat, A. et al. Reactome graph database: Efficient access to complex pathway data. PLoS Computational Biology 14, (2018).
3.  Ma, H. & Zeng, A.-P. Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms. BIOINFORMATICS vol. 19 https://academic.oup.com/bioinformatics/article/19/2/270/372721 (2003).
4.  Martínez, V. S. et al. The topology of genome-scale metabolic reconstructions unravels independent modules and high network flexibility. PLoS Computational Biology 18, (2022).
DOI: 10.5281/zenodo.10103768
title: Reactome modified for tracing ArangoDB version

description: Reactome database download and customization
The Reactome database [1,2] was downloaded as a neo4j graph database (https://reactome.org/download-data version 75), which is covered by the Creative Commons Attribution 4.0 International (CC BY 4.0) license. A series of database queries was used to generate a database version suitable for graph data science which can be followed in detail in the attached Jupyter notebook (Or at GDS-Public/notebooks/reactome/Reactome GDS.ipynb at main · SBRG/GDS-Public (github.com)). 
Nodes, labels and relationships not required for graph algorithmic analyses were removed. For instance, this included nodes like person, affiliation, and taxa as well as all nodes representing entities of organisms other than Homo sapiens. Subcellular locations (compartments) of biological entities were set as node properties. To allow for improved graph traversal, selected relationships were reversed or added. Because currency metabolites, e.g. ATP, NAD(P)H and H+, can artificially connect metabolic reactions and pathways in network analyses [3,4], we labelled such compounds plus the regulatory protein ubiquitin accordingly and thereby excluded them from all analyses. Finally, the database was transformed into an ArangoDB graph database consisting of 1,703,054 nodes and 3,368,926 edges. 
References
1.  Gillespie, M. et al. The reactome pathway knowledgebase 2022. Nucleic Acids Research 50, D687–D692 (2022).
2.  Fabregat, A. et al. Reactome graph database: Efficient access to complex pathway data. PLoS Computational Biology 14, (2018).
3.  Ma, H. & Zeng, A.-P. Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms. BIOINFORMATICS vol. 19 https://academic.oup.com/bioinformatics/article/19/2/270/372721 (2003).
4.  Martínez, V. S. et al. The topology of genome-scale metabolic reconstructions unravels independent modules and high network flexibility. PLoS Computational Biology 18, (2022).
DOI: 10.5255/ukda-sn-856427
title: Good Employment Learning Lab Project Data, 2021-2022

description: The Good Employment Learning Lab trialed short interventions that develop the people management skills of line managers to find out ‘what works, for whom, and why?’. We wanted to know how line management development can create efficient teams and good work for staff and managers. Our findings culminated in the GELL Framework for Developing the People Management Skills of Line Managers. We had two Learning Labs: • The Greater Manchester Good Employment Learning Lab worked with the Greater Manchester Good Employment Charter and local authorities to make sense of the challenge of raising people management skills in a particular place. • The Adult Social Care Good Employment Learning Lab worked with Skills for Care, the NHS and local authorities to make sense of the challenge of raising people management skills in a particular sector. Both Learning Labs were also supported by the CIPD, ACAS, the Federation of Small Businesses and the TUC.
DOI: 10.34740/kaggle/dsv/6939381
title: OECD General government deficit
DOI: 10.5281/zenodo.10106950
title: cacatua_galerita_zanfona_1.fasta.gz

description: cacatua_galerita_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.10106951
title: cacatua_galerita_zanfona_1.fasta.gz

description: cacatua_galerita_zanfona_1.fasta.gz