cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20418216
title: Additional file 4 of Target residence of Cas9-sgRNA influences DNA double-strand break repair pathway choices in CRISPR/Cas9 genome editing

description: Additional file 4: Table S3. Junction sequences of sister chromatid fusion products in U2OS cells by PCR targeted amplicon sequencing.
DOI: 10.6084/m9.figshare.23040204
title: CircRNA <i>CDR1as</i>: a novel diagnostic and prognostic biomarker for gastric cancer

description: Circular RNA (circRNA) <i>CDR1as</i> is emerging as a vital tumour regulator. This study aimed to investigate its diagnostic and prognostic value and molecular mechanisms for gastric cancer (GC). <i>CDR1as</i> expression in GC and adjacent normal tissues (n = 82), paired plasma (n = 65) and plasma exosome samples (n = 68) from GC patients and healthy controls were determined by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Correlations between <i>CDR1as</i> level and clinicopathological factors of GC patients were analysed. Its diagnostic and prognostic value was evaluated by receiver operating characteristic (ROC) curves and Cox regression analysis combined with Kaplan-Meier plots. <i>CDR1as-</i>regulated proteins and signalling pathways were identified by quantitative proteomics and bioinformatic analysis. <i>CDR1as</i> was downregulated in GC tissues and associated with tumour size and neural invasion. Plasma- and exosome-derived <i>CDR1as</i> was upregulated in GC patients while plasma-derived <i>CDR1as</i> level was related to lymphatic metastasis. Area under ROC curve (AUC) of tissue-, plasma- and exosome-derived <i>CDR1as</i> was 0.782, 0.641, 0.536 while combination of plasma <i>CDR1as</i>, serum CEA and CA19-9 increased AUC to 0.786. Distal metastasis, TNM stage and tissue-derived <i>CDR1as</i> level were independent predictors for overall survival (OS) of patients. MiRNA signalling networks and glycine, serine and threonine metabolism were regulated by CDR1as and HSPE1 might be a key protein. <i>CDR1as</i> is a crucial regulator and promising biomarker for GC diagnosis and prognosis. <i>CDR1as</i> level in tumour tissues and plasma of GC patients was associated with tumour progression. The findings indicate that <i>CDR1as</i> is involved in GC progression and is a potential diagnostic and prognostic biomarker.
DOI: 10.6084/m9.figshare.14651090
title: Additional file 5 of Integrative analysis of transcriptome and proteome revealed nectary and nectar traits in the plant-pollinator interaction of Nitraria tangutorum Bobrov

description: Additional file 5: Dataset 2. Differentially expressed genes during flower development. The gene expression level at each stage is the average of three replicates
DOI: 10.6084/m9.figshare.14651093.v1
title: Additional file 6 of Integrative analysis of transcriptome and proteome revealed nectary and nectar traits in the plant-pollinator interaction of Nitraria tangutorum Bobrov

description: Additional file 6: Supplemental Table 1. Sample description and RNA-seq reads number
DOI: 10.6084/m9.figshare.23040204.v1
title: CircRNA <i>CDR1as</i>: a novel diagnostic and prognostic biomarker for gastric cancer

description: Circular RNA (circRNA) <i>CDR1as</i> is emerging as a vital tumour regulator. This study aimed to investigate its diagnostic and prognostic value and molecular mechanisms for gastric cancer (GC). <i>CDR1as</i> expression in GC and adjacent normal tissues (n = 82), paired plasma (n = 65) and plasma exosome samples (n = 68) from GC patients and healthy controls were determined by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Correlations between <i>CDR1as</i> level and clinicopathological factors of GC patients were analysed. Its diagnostic and prognostic value was evaluated by receiver operating characteristic (ROC) curves and Cox regression analysis combined with Kaplan-Meier plots. <i>CDR1as-</i>regulated proteins and signalling pathways were identified by quantitative proteomics and bioinformatic analysis. <i>CDR1as</i> was downregulated in GC tissues and associated with tumour size and neural invasion. Plasma- and exosome-derived <i>CDR1as</i> was upregulated in GC patients while plasma-derived <i>CDR1as</i> level was related to lymphatic metastasis. Area under ROC curve (AUC) of tissue-, plasma- and exosome-derived <i>CDR1as</i> was 0.782, 0.641, 0.536 while combination of plasma <i>CDR1as</i>, serum CEA and CA19-9 increased AUC to 0.786. Distal metastasis, TNM stage and tissue-derived <i>CDR1as</i> level were independent predictors for overall survival (OS) of patients. MiRNA signalling networks and glycine, serine and threonine metabolism were regulated by CDR1as and HSPE1 might be a key protein. <i>CDR1as</i> is a crucial regulator and promising biomarker for GC diagnosis and prognosis. <i>CDR1as</i> level in tumour tissues and plasma of GC patients was associated with tumour progression. The findings indicate that <i>CDR1as</i> is involved in GC progression and is a potential diagnostic and prognostic biomarker.
DOI: 10.6084/m9.figshare.20418213
title: Additional file 3 of Target residence of Cas9-sgRNA influences DNA double-strand break repair pathway choices in CRISPR/Cas9 genome editing

description: Additional file 3: Table S2. Junction sequences of sister chromatid fusion products in mESC by PCR targeted amplicon sequencing.
DOI: 10.6084/m9.figshare.20418216.v1
title: Additional file 4 of Target residence of Cas9-sgRNA influences DNA double-strand break repair pathway choices in CRISPR/Cas9 genome editing

description: Additional file 4: Table S3. Junction sequences of sister chromatid fusion products in U2OS cells by PCR targeted amplicon sequencing.
DOI: 10.6084/m9.figshare.19793438
title: Additional file 1 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 1: Table S1. Summary of sparsity across 20 spatial transcriptomics datasets used in the present study.
DOI: 10.6084/m9.figshare.19793438.v1
title: Additional file 1 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 1: Table S1. Summary of sparsity across 20 spatial transcriptomics datasets used in the present study.
DOI: 10.6084/m9.figshare.19793444
title: Additional file 3 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 3: Table S3. scRNA data used as reference for deconvolution in CARD.
DOI: 10.6084/m9.figshare.19793441
title: Additional file 2 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 2: Table S2. Summary of likelihood ratio test results across datasets.
DOI: 10.6084/m9.figshare.19793441.v1
title: Additional file 2 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 2: Table S2. Summary of likelihood ratio test results across datasets.
DOI: 10.6084/m9.figshare.19793450
title: Additional file 5 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 5: Table S5. Location clustering information for each dataset.
DOI: 10.6084/m9.figshare.19793450.v1
title: Additional file 5 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 5: Table S5. Location clustering information for each dataset.
DOI: 10.6084/m9.figshare.19793444.v1
title: Additional file 3 of Modeling zero inflation is not necessary for spatial transcriptomics

description: Additional file 3: Table S3. scRNA data used as reference for deconvolution in CARD.
DOI: 10.6084/m9.figshare.13078916
title: Metadata record for the manuscript: On-treatment measurements of circulating tumor DNA during FOLFOX therapy in patients with colorectal cancer

description: <b>Summary</b>

This
metadata record provides details of the data supporting the claims of the
related manuscript: “On-treatment measurements of
circulating tumor DNA during FOLFOX therapy in patients with colorectal cancer”.

The
related study addressed how circulating tumor DNA (ctDNA) levels change during
chemotherapy by serially monitoring ctDNA in patients with colorectal cancer
during the 48-hour application of FOLFOX.

 

<b>Data
access</b>

The
sequencing raw data sets have been deposited at the <i>European Genome-phenome
Archive</i> (EGA; http://www.ebi.ac.uk/ega/) under study accession number https://identifiers.org/ega.study:EGAS00001004213.
This study contains the following four datasets: 1: sWGS of CRC patients (https://identifiers.org/ega.dataset:EGAD00001006101),
2: Mutation analysis data (AVENIO ctDNA Targeted Kit: https://identifiers.org/ega.dataset:EGAD00001006103,
SiMSen-seq approach: https://identifiers.org/ega.dataset:EGAD00001006104,
Deep sequencing: https://identifiers.org/ega.dataset:EGAD00001006105).
Data access requests can be made to the appropriate Data Access Committee via
the EGA landing page for each dataset.<br>

In addition to the
sequencing data, the following data underlie the supplementary figures and tables
of the related manuscript. Summary_file2.xlsx
underlies Supplementary table 1 and Supplementary
figures 8 and 10, and is available from the <i>figshare
</i>repository at https://doi.org/10.6084/m9.figshare.13067348.v2.
41586_2019_1272_MOESM2_ESM.xlsx underlies Supplementary
figure 11, and is available in the Supplementary Tables of Cristiano et al.
(2019): https://doi.org/10.1038/s41586-019-1272-6.


 

<b>Name
of Institutional Review Board or ethics committee that approved the study </b>

The study was approved by
the Ethics Committee of the Medical University of Graz (approval number 26-288
ex 13/14 for the study part involving patients under FOLFOX treatment and
29-272 ex 16/17 for the collection and analysis of blood samples from healthy
controls) conducted according to the Declaration of Helsinki. Written informed
consent was obtained from all patients and healthy individuals, respectively.
DOI: 10.6084/m9.figshare.13078916.v1
title: Metadata record for the manuscript: On-treatment measurements of circulating tumor DNA during FOLFOX therapy in patients with colorectal cancer

description: <b>Summary</b>

This
metadata record provides details of the data supporting the claims of the
related manuscript: “On-treatment measurements of
circulating tumor DNA during FOLFOX therapy in patients with colorectal cancer”.

The
related study addressed how circulating tumor DNA (ctDNA) levels change during
chemotherapy by serially monitoring ctDNA in patients with colorectal cancer
during the 48-hour application of FOLFOX.

 

<b>Data
access</b>

The
sequencing raw data sets have been deposited at the <i>European Genome-phenome
Archive</i> (EGA; http://www.ebi.ac.uk/ega/) under study accession number https://identifiers.org/ega.study:EGAS00001004213.
This study contains the following four datasets: 1: sWGS of CRC patients (https://identifiers.org/ega.dataset:EGAD00001006101),
2: Mutation analysis data (AVENIO ctDNA Targeted Kit: https://identifiers.org/ega.dataset:EGAD00001006103,
SiMSen-seq approach: https://identifiers.org/ega.dataset:EGAD00001006104,
Deep sequencing: https://identifiers.org/ega.dataset:EGAD00001006105).
Data access requests can be made to the appropriate Data Access Committee via
the EGA landing page for each dataset.<br>

In addition to the
sequencing data, the following data underlie the supplementary figures and tables
of the related manuscript. Summary_file2.xlsx
underlies Supplementary table 1 and Supplementary
figures 8 and 10, and is available from the <i>figshare
</i>repository at https://doi.org/10.6084/m9.figshare.13067348.v2.
41586_2019_1272_MOESM2_ESM.xlsx underlies Supplementary
figure 11, and is available in the Supplementary Tables of Cristiano et al.
(2019): https://doi.org/10.1038/s41586-019-1272-6.


 

<b>Name
of Institutional Review Board or ethics committee that approved the study </b>

The study was approved by
the Ethics Committee of the Medical University of Graz (approval number 26-288
ex 13/14 for the study part involving patients under FOLFOX treatment and
29-272 ex 16/17 for the collection and analysis of blood samples from healthy
controls) conducted according to the Declaration of Helsinki. Written informed
consent was obtained from all patients and healthy individuals, respectively.
DOI: 10.48597/qng2-xyvj
title: Heavy metals at Iskrba

description: Measurement of Heavy metals at Iskrba
DOI: 10.48597/r272-ptmf
title: Heavy metals and inorganics in air and particle phase at Montseny

description: Measurement of Heavy metals and inorganics in air and particle phase at Montseny
DOI: 10.48597/rb3t-da9b
title: Cadmium and PAHs (polycyclic aromatic hydrocarbons, 16) at Iskrba

description: Measurement of Cadmium and PAHs (polycyclic aromatic hydrocarbons, 16) at Iskrba
DOI: 10.48597/rk25-js7k
title: Lithium and sulphate_total at Montseny

description: Measurement of Lithium and sulphate_total at Montseny
DOI: 10.6084/m9.figshare.7836050
title: Additional file 2: of Genome-wide identification of RNA editing in seven porcine tissues by matched DNA and RNA high-throughput sequencing

description: Table S1. Primers used in the Sanger sequencing. (XLSX 135 kb)
DOI: 10.48597/rraw-h4r5
title: Precipitation_amount at Koksijde

description: Measurement of Precipitation_amount at Koksijde
DOI: 10.48597/t343-85cv
title: Nitrogen_dioxide at Iskrba

description: Measurement of Nitrogen_dioxide at Iskrba
DOI: 10.48597/tg7g-wj57
title: Organic_carbon at Iskrba

description: Measurement of Organic_carbon at Iskrba
DOI: 10.6084/m9.figshare.7836050.v1
title: Additional file 2: of Genome-wide identification of RNA editing in seven porcine tissues by matched DNA and RNA high-throughput sequencing

description: Table S1. Primers used in the Sanger sequencing. (XLSX 135 kb)
DOI: 10.48597/thhm-gtw5
title: Aerosol_absorption_coefficient at Ispra

description: Measurement of Aerosol_absorption_coefficient at Ispra
DOI: 10.48597/tj6q-8jv4
title: Nitrogen_dioxide at Rucava

description: Measurement of Nitrogen_dioxide at Rucava
DOI: 10.48597/tn7f-6mur
title: Aerosol_absorption_coefficient at Jungfraujoch

description: Measurement of Aerosol_absorption_coefficient at Jungfraujoch
DOI: 10.48597/ttvh-9zh2
title: PAHs (polycyclic aromatic hydrocarbons, 16) at Virolahti II

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Virolahti II
DOI: 10.48597/tuzu-kgfx
title: Heavy metals at Storhofdi

description: Measurement of Heavy metals at Storhofdi
DOI: 10.48597/ubjh-xrj8
title: Aerosol_optical_depth at Bratts Lake

description: Measurement of Aerosol_optical_depth at Bratts Lake
DOI: 10.48597/ur8y-5vbv
title: Inorganics in precipitation at Koksijde

description: Measurement of Inorganics in precipitation at Koksijde
DOI: 10.48597/v2e4-2n3b
title: Aerosol_light_scattering_coefficient at Mt Cimone

description: Measurement of Aerosol_light_scattering_coefficient at Mt Cimone
DOI: 10.48597/vcdk-s848
title: Particle_number_size_distribution at Bösel

description: Measurement of Particle_number_size_distribution at Bösel
DOI: 10.48597/vd2t-dp2j
title: Benzo_a_pyrene at Virolahti II

description: Measurement of Benzo_a_pyrene at Virolahti II
DOI: 10.48597/vw6c-rz8d
title: Aerosol_optical_depth at Jungfraujoch

description: Measurement of Aerosol_optical_depth at Jungfraujoch
DOI: 10.48597/w97k-rfq2
title: PAHs (polycyclic aromatic hydrocarbons) at Zingst

description: Measurement of PAHs (polycyclic aromatic hydrocarbons) at Zingst
DOI: 10.48597/wjqf-kd98
title: Inorganics in precipitation at Vavihill

description: Measurement of Inorganics in precipitation at Vavihill
DOI: 10.48597/x8jq-ur2z
title: Heavy metals and inorganics in air and particle phase at Montseny

description: Measurement of Heavy metals and inorganics in air and particle phase at Montseny
DOI: 10.6084/m9.figshare.7836056
title: Additional file 3: of Genome-wide identification of RNA editing in seven porcine tissues by matched DNA and RNA high-throughput sequencing

description: Table S2. RNA editing sites identified in this study. (XLSX 6798 kb)
DOI: 10.48597/x8rq-u65j
title: Elemental_carbon and PAHs (polycyclic aromatic hydrocarbons, 16) at Iskrba

description: Measurement of Elemental_carbon and PAHs (polycyclic aromatic hydrocarbons, 16) at Iskrba
DOI: 10.48597/xv8q-j57n
title: Particle_number_size_distribution at Ispra

description: Measurement of Particle_number_size_distribution at Ispra
DOI: 10.48597/y5qj-9vgp
title: Aerosol light scattering at Jungfraujoch

description: Measurement of Aerosol light scattering at Jungfraujoch
DOI: 10.6084/m9.figshare.7836056.v1
title: Additional file 3: of Genome-wide identification of RNA editing in seven porcine tissues by matched DNA and RNA high-throughput sequencing

description: Table S2. RNA editing sites identified in this study. (XLSX 6798 kb)
DOI: 10.48597/zskb-suum
title: Heavy metals at Virolahti II

description: Measurement of Heavy metals at Virolahti II
DOI: 10.48597/zszu-pann
title: Aerosol light scattering at Barrow

description: Measurement of Aerosol light scattering at Barrow
DOI: 10.48597/46xb-n3fd
title: Measurement of Pm10_mass at Víznar

description: Measurement of Pm10_mass at Víznar
DOI: 10.48597/47ep-9xtm
title: Measurement of Inorganics in air and particle phase at O Saviñao

description: Measurement of Inorganics in air and particle phase at O Saviñao
DOI: 10.48597/6455-vcfy
title: Measurement of Inorganics in air and particle phase at O Saviñao

description: Measurement of Inorganics in air and particle phase at O Saviñao
DOI: 10.48597/6gsu-ss4q
title: Measurement of Inorganics in precipitation at O Saviñao

description: Measurement of Inorganics in precipitation at O Saviñao
DOI: 10.48597/6hee-r342
title: Measurement of PM mass at Chaumont

description: Measurement of PM mass at Chaumont
DOI: 10.48597/6y66-kbc8
title: Measurement of Heavy metals at Illmitz

description: Measurement of Heavy metals at Illmitz
DOI: 10.48597/78f5-kca9
title: Measurement of Pm10_mass at Víznar

description: Measurement of Pm10_mass at Víznar
DOI: 10.48597/7mke-7vdp
title: Measurement of VOC (OVOCs) at Waldhof

description: Measurement of VOC (OVOCs) at Waldhof
DOI: 10.48597/89x4-y5w4
title: Measurement of VOC (OVOCs) at Schmücke

description: Measurement of VOC (OVOCs) at Schmücke
DOI: 10.48597/8cu4-w86s
title: Measurement of VOC (OVOCs) at Schmücke

description: Measurement of VOC (OVOCs) at Schmücke
DOI: 10.48597/8gpe-tqsx
title: Measurement of Inorganics in air and particle phase at O Saviñao

description: Measurement of Inorganics in air and particle phase at O Saviñao
DOI: 10.48597/8rse-dr7w
title: Measurement of Pm10_mass at Niembro

description: Measurement of Pm10_mass at Niembro
DOI: 10.48597/8v7p-cm95
title: Measurement of Inorganics in air and particle phase at Víznar

description: Measurement of Inorganics in air and particle phase at Víznar
DOI: 10.5281/zenodo.10714822
title: The Turku UAS DeepSeaSalama - GAN dataset 1 (TDSS-G1)

description: The Turku UAS DeepSeaSalama-GAN dataset 1 (TDSS-G1) is a comprehensive image dataset obtained from a maritime environment. This dataset was assembled in the southwest Finnish archipelago area at Taalintehdas, using two stationary RGB fisheye cameras in the month of August 2022. The technical setup is described in the section “Sensor Platform design” in report “Development of Applied Research Platforms for Autonomous and Remotely Operated Systems” (https://www.theseus.fi/handle/10024/815628).

The data collection and annotation process was carried out in the Autonomous and Intelligent Systems laboratory at Turku University of Applied Sciences. The dataset is a blend of original images captured by our cameras and synthetic data generated by a Generative Adversarial Network (GAN), simulating 18 distinct weather conditions.

The TDSS-G1 dataset comprises 199 original images and a substantial addition of 3582 synthetic images, culminating in a total of 3781 annotated images. These images provide a diverse representation of various maritime objects, including motorboats, sailing boats, and seamarks.

The creation of TDSS-G1 involved extracting images from videos recorded in MPEG format, with a resolution of 720p at 30 frames per second (FPS). An image was extracted every 100 milliseconds.

The distribution of labels within TDSS-G1 is as follows: motorboats (62.1%), sailing boats (16.8%), and seamarks (21.1%).

This distribution highlights a class imbalance, with motorboats being the most represented class and sailing boats being the least. This imbalance is an important factor to consider during the model training process, as it could influence the model’s ability to accurately recognize underrepresented classes. In the future synthetic datasets, vision Transformers will be used to tackle this problem.

 

The TDSS-G1 dataset is organized into three distinct subsets for the purpose of training and evaluating machine learning models. These subsets are as follows:



Training Set: Located in dataset/train/images, this set is used to train the model. It learns to recognize the different classes of maritime objects from this data.

Validation Set: Stored in dataset/valid/images, this set is used to tune the model parameters and to prevent overfitting during the training process.

Test Set: Found in dataset/test/images, this set is used to evaluate the final performance of the model. It provides an unbiased assessment of how the model will perform on unseen data.


The dataset comprises three classes (nc: 3), each representing a different type of maritime object. The classes are as follows:



Motor Boat (motor_boat)

Sailing Boat (sailing_boat)

Seamark (seamark)


These labels correspond to the annotated objects in the images. The model trained on this dataset will be capable of identifying these three types of maritime objects. As mentioned earlier, the distribution of these classes is imbalanced, which is an important factor to consider during the training process.