cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4236125
title: Distribution of the tryptophan pathway-derived defensive secondary metabolites gramine and benzoxazinones in Poaceae

description: The Poaceae is a large taxonomic group consisting of approximately 12,000 species and is classified into 12 subfamilies. Gramine and benzoxazinones (Bxs), which are biosynthesized from the tryptophan pathway, are well-known defensive secondary metabolites in the Poaceae. We analyzed the presence or absence of garamine and Bxs in 64 species in the Poaceae by LC-MS/MS. We found that <i>Hordeum brachyantherum</i> and <i>Hakonechloa macra</i> accumulated gramine, but the presence of gramine was limited to small groups of species. We also detected Bxs in four species in the Pooideae and six species in the Panicoideae. In particular, four species in the Paniceae tribe in Panicoideae accumulaed Bxs, indicating that this tribe is a center of the Bx distribution. Bxs were absent in the subfamilies other than Pooideae and Panicoideae. These findings provide an overview of biased distribution of gramine and Bxs in Poaceae species. The analysis of defensive secondary metabolites, gramine and benzoxazinones, in the Poaceae provided an overview of their biased distribution.
DOI: 10.6084/m9.figshare.4236125.v1
title: Distribution of the tryptophan pathway-derived defensive secondary metabolites gramine and benzoxazinones in Poaceae

description: The Poaceae is a large taxonomic group consisting of approximately 12,000 species and is classified into 12 subfamilies. Gramine and benzoxazinones (Bxs), which are biosynthesized from the tryptophan pathway, are well-known defensive secondary metabolites in the Poaceae. We analyzed the presence or absence of garamine and Bxs in 64 species in the Poaceae by LC-MS/MS. We found that <i>Hordeum brachyantherum</i> and <i>Hakonechloa macra</i> accumulated gramine, but the presence of gramine was limited to small groups of species. We also detected Bxs in four species in the Pooideae and six species in the Panicoideae. In particular, four species in the Paniceae tribe in Panicoideae accumulaed Bxs, indicating that this tribe is a center of the Bx distribution. Bxs were absent in the subfamilies other than Pooideae and Panicoideae. These findings provide an overview of biased distribution of gramine and Bxs in Poaceae species. The analysis of defensive secondary metabolites, gramine and benzoxazinones, in the Poaceae provided an overview of their biased distribution.
DOI: 10.6084/m9.figshare.4236056
title: New draft item

description: Genome annotation for Gsub and Nsub, two symbionts from cold seep sponge.
DOI: 10.17633/rd.brunel.4236050
title: Isabelle files for verification of a pessimistic STM algorithm

description: This page contains the Isabelle theory files that show refinement between Matveev and Shavit's pessimistic transactional memory algorithm (MSPessTM) and the TMS2 specification. Leveraging Lesani et al's results, these proofs establish opacity of MSPessTM. The tarball consists of the following: Main files TMS2.thy - contains the IOA specification of TMS2 MSPessTM.thy contains the I/O automata encoding of the MSPessTM algorithm, invariants and supporting lemmas MSPessTMCorrect.thy contains the simulation relation and all associated proofs proof Supporting files Transitions.thy and Interface.thy provide tools for uniformly constructing automata that represent STM implementations. Utilities.thy and RWMemory.thy define some concepts that are shared between the other theories. The proofs require Isabelle 2016. If you encounter a problem loading Seq.thy, please make sure imports is set to "../HOLCF". This is a problem with the new Isabelle distribution.
DOI: 10.6084/m9.figshare.4236056.v1
title: New draft item

description: Genome annotation for Gsub and Nsub, two symbionts from cold seep sponge.
DOI: 10.6084/m9.figshare.4235828
title: Carbon accumulation in Amazonian floodplain lakes: A significant component of Amazon budgets?

description: The Amazon floodplains cover approximately 10% of the Amazon Basin and are composed of predominantly anoxic sediments that may store large amounts of carbon. Our study combines <sup>210</sup>Pb derived sedimentation rates from four recently analyzed sediment cores (n=4) with previously published organic carbon (OC) burial estimates (n=18) to provide a broad, first order estimate of carbon accumulation in Amazon floodplain lakes. The OC burial rates were of 266 ± 57 g C m<sup>-2</sup> year<sup>-1</sup>. This rate is several fold greater than those reported for lakes in arctic, boreal, temperate and tropical regions. The large amount and spatial variation of OC burial rates in these floodplain lakes highlights the need for increased sampling efforts to better measure these potentially important components of the Amazon Basin carbon budget.
DOI: 10.6084/m9.figshare.4235828.v2
title: Carbon accumulation in Amazonian floodplain lakes: A significant component of Amazon budgets?

description: The Amazon floodplains cover approximately 10% of the Amazon Basin and are composed of predominantly anoxic sediments that may store large amounts of carbon. Our study combines <sup>210</sup>Pb derived sedimentation rates from four recently analyzed sediment cores (n=4) with previously published organic carbon (OC) burial estimates (n=18) to provide a broad, first order estimate of carbon accumulation in Amazon floodplain lakes. The OC burial rates were of 266 ± 57 g C m<sup>-2</sup> year<sup>-1</sup>. This rate is several fold greater than those reported for lakes in arctic, boreal, temperate and tropical regions. The large amount and spatial variation of OC burial rates in these floodplain lakes highlights the need for increased sampling efforts to better measure these potentially important components of the Amazon Basin carbon budget.
DOI: 10.6084/m9.figshare.4235828.v1
title: Carbon accumulation in Amazonian floodplain lakes: A significant component of Amazon budgets?

description: The Amazon floodplains cover approximately 10% of the Amazon Basin and are composed of predominantly anoxic sediments that may store large amounts of carbon. Our study combines <sup>210</sup>Pb derived sedimentation rates from four recently analyzed sediment cores (n=4) with previously published organic carbon (OC) burial estimates (n=18) to provide a broad, first order estimate of carbon accumulation in Amazon floodplain lakes. The OC burial rates were of 266 ± 57 g C m<sup>-2</sup> year<sup>-1</sup>. This rate is several fold greater than those reported for lakes in arctic, boreal, temperate and tropical regions. The large amount and spatial variation of OC burial rates in these floodplain lakes highlights the need for increased sampling efforts to better measure these potentially important components of the Amazon Basin carbon budget.
DOI: 10.6084/m9.figshare.4235732
title: STRING-ENSG-ENSP_map

description: the mapping between ENSG and ENSP from STRING v10
DOI: 10.6084/m9.figshare.4235714
title: gencodev19

description: the reference genome for mapping RNA-seq reads
DOI: 10.6084/m9.figshare.4235714.v1
title: gencodev19

description: the reference genome for mapping RNA-seq reads
DOI: 10.6084/m9.figshare.4235636
title: Test set of clinical meta-data for HPV Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235627
title: Training set of clinical meta-data for HPV Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235636.v1
title: Test set of clinical meta-data

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235627.v1
title: Training set of clinical meta-data

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235636.v3
title: Test set of clinical meta-data for HPV Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235636.v2
title: Test set of clinical meta-data for HPV Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235627.v2
title: Training set of clinical meta-data for HPV Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (136 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 152 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the HPV status blinded.
DOI: 10.6084/m9.figshare.4235564
title: LOC_ID coding in deployment files

description: Details of coding used in SPACECAP input files. In input files LOC_IDs must be represented as sequential numbers. This file shows which LOC_IDs correspond to which camera station numbers.
DOI: 10.6084/m9.figshare.4235561
title: ANIMAL_ID coding in capture files

description: Details of coding used in SPACECAP input files. In input files ANIMAL_IDs must be represented as sequential numbers. This file shows which ANIMAL_IDs correspond to which individual animals.