cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35077/add-cut
title: Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 914826774

description: Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 914826774', GeneralModality:'cell morphology', Technique:'Patch-seq' SPECIMEN METADATA: LocalID:'914826774', Species:'human', NCBITaxonomy:'NCBI:txid9606', SampleLocalID:'914826774', Locations:'FroL' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'0.114', stepSizeY:'0.114'
DOI: 10.35077/add-day
title: Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 941707648

description: Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 941707648', GeneralModality:'cell morphology', Technique:'Patch-seq' SPECIMEN METADATA: LocalID:'941707648', Species:'human', NCBITaxonomy:'NCBI:txid9606', SampleLocalID:'941707648', Locations:'TemL' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'0.114', stepSizeY:'0.114'
DOI: 10.35077/add-den
title: Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 941862585

description: Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 941862585', GeneralModality:'cell morphology', Technique:'Patch-seq' SPECIMEN METADATA: LocalID:'941862585', Species:'human', NCBITaxonomy:'NCBI:txid9606', SampleLocalID:'941862585', Locations:'TemL' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'0.114', stepSizeY:'0.114'
DOI: 10.35077/add-did
title: Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 941919377

description: Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 941919377', GeneralModality:'cell morphology', Technique:'Patch-seq' SPECIMEN METADATA: LocalID:'941919377', Species:'human', NCBITaxonomy:'NCBI:txid9606', SampleLocalID:'941919377', Locations:'TemL' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'0.114', stepSizeY:'0.114'
DOI: 10.35077/add-dig
title: Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 960790148

description: Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 960790148', GeneralModality:'cell morphology', Technique:'Patch-seq' SPECIMEN METADATA: LocalID:'960790148', Species:'human', NCBITaxonomy:'NCBI:txid9606', SampleLocalID:'960790148', Locations:'MFG' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'0.114', stepSizeY:'0.114'
DOI: 10.35077/add-dim
title: Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 966905488

description: Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This collection may contain image stacks (TIFF), reconstruction files in image space (.swc, µm), a transformed file (.swc, µm) oriented so that the y axis extends vertically towards the pia surface, and a marker file (.marker, µm) indicating nodes where dendrites were truncated (10), reconstruction was not continued (20), or surface of tissue was closest to soma (30).
description: manual tracing
description: DATASET METADATA: title:'Neuron Morphology data in .swc format from Patch-seq experiments in human neocortex, Cell ID 966905488', GeneralModality:'cell morphology', Technique:'Patch-seq' SPECIMEN METADATA: LocalID:'966905488', Species:'human', NCBITaxonomy:'NCBI:txid9606', SampleLocalID:'966905488', Locations:'OccL' INSTRUMENT METADATA: MicroscopeType:'NA', MicroscopeManufacturerAndModel:'NA' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'0.114', stepSizeY:'0.114'
DOI: 10.5281/zenodo.7865297
title: Data for: Approaches for handling missing values and their impacts on biological inferences: a molecular rate case study

description: These data files are associated with the manuscript entitled: "Approaches for handling missing values and their impacts on biological inferences: a molecular rate case study" by Jacqueline A. May, Zeny Feng, and Sarah J. Adamowicz. This project entailed an evaluation of missing data handling approach on inferences using a molecular evolution case study. A target mixed-type dataset was first imputed using a real data-driven strategy for imputation method selection. Both trait-only (non-phylogenetic) and phylogenetic imputation methods were used to impute the dataset. Phylogenetic generalized least squares (PGLS) analyses were then applied to the complete-case and imputed datasets, specifying the traits as predictors and molecular evolutionary rates as the response variable. Those traits that associate significantly with molecular rates were identified and PGLS models compared to determine how the approach for handling missing data impacts biological inferences and conclusions. The files stored here are the trees built for phylogenetic imputation (RAxML tree and ultrametric tree versions) and the corresponding GenBank accession numbers.
DOI: 10.5281/zenodo.7865296
title: Data for: Approaches for handling missing values and their impacts on biological inferences: a molecular rate case study

description: These data files are associated with the manuscript entitled: "Approaches for handling missing values and their impacts on biological inferences: a molecular rate case study" by Jacqueline A. May, Zeny Feng, and Sarah J. Adamowicz. This project entailed an evaluation of missing data handling approach on inferences using a molecular evolution case study. A target mixed-type dataset was first imputed using a real data-driven strategy for imputation method selection. Both trait-only (non-phylogenetic) and phylogenetic imputation methods were used to impute the dataset. Phylogenetic generalized least squares (PGLS) analyses were then applied to the complete-case and imputed datasets, specifying the traits as predictors and molecular evolutionary rates as the response variable. Those traits that associate significantly with molecular rates were identified and PGLS models compared to determine how the approach for handling missing data impacts biological inferences and conclusions. The files stored here are the trees built for phylogenetic imputation (RAxML tree and ultrametric tree versions) and the corresponding GenBank accession numbers.
DOI: 10.5281/zenodo.2308729
title: Supporting data and code for: Investigation on the sensitivity of Plasmopara viticola to amisulbrom and ametoctradin in French vineyards using bioassays and molecular tools

description: This is a small modification of the first release of the final data and code for the article entitled "Investigation on the sensitivity of Plasmopara viticola to amisulbrom and ametoctradin in French vineyards using bioassays and molecular tools" accepted for publication in Pest Management Science.
DOI: 10.5281/zenodo.16536
title: Food-Web-Modules-And-Individual-Growth-Rate: First Release

description: No description provided.
DOI: 10.5281/zenodo.572496
title: Riselya/Effect-Of-Infection-On-Migration---Meta-Analysis: First Release

description: This is the first release of data and code used for our article "How does infection later animal migration: a meta-analysis across experimental and observational studies" by Alice Risely, Marcel Klaassen and Bethany Hoye.

 

For updated analyses or new versions, please go to Github.com/Riselya
DOI: 10.5281/zenodo.11425
title: Data For: Performance Benchmarking Of Application Monitoring Frameworks

description: Application-level monitoring of continuously operating software systems provides insights into their dynamic behavior, helping to maintain their performance and availability during runtime. Such monitoring may cause a significant runtime overhead to the monitored system, depending on the number and location of used instrumentation probes. In order to improve a system’s instrumentation and to reduce the caused monitoring overhead, it is necessary to know the performance impact of each probe.<br>
While many monitoring frameworks are claiming to have minimal impact on the performance, these claims are often not backed up with a detailed performance evaluation determining the actual cost of monitoring. Benchmarks can be used as an effective and affordable way for these evaluations. However, no benchmark specifically targeting the overhead of monitoring itself exists. Furthermore, no established benchmark engineering methodology exists that provides guidelines for the design, execution, and analysis of benchmarks.<br>
This thesis introduces a benchmark approach to measure the performance overhead of application-level monitoring frameworks. The core contributions of this approach are 1) a definition of common causes of monitoring overhead, 2) a general benchmark engineering methodology, 3) the MooBench micro-benchmark to measure and quantify causes of monitoring overhead, and 4) detailed performance evaluations of three different application-level monitoring frameworks. Extensive experiments demonstrate the feasibility and practicality of the approach and validate the benchmark results. The developed benchmark is available as open source software and the results of all experiments are available for download to facilitate further validation and replication of the results.

This dataset supplements the thesis and contains the results of all experiments, including the raw result data, the results of additional experiments, and the configuration of our benchmarks.
DOI: 10.57745/rfcblc
title: DrForest_Ticks_sampling2021.tab

description: Data for the article "Lower prevalence of Lyme disease pathogens in mixed deciduous – coniferous forests"
DOI: 10.6073/pasta/bec362cd28206d3fe12eab730fcbf204
title: ASS01 Suspended sediments in streams impacted by prescribed buring, grazing and woody vegetation removal at Konza Prairie

description: To determine effects of rotational burning and riparian vegetation removal on suspended solid concentrations in streams. Two sites are burned with a frequency of 2 (N02B) and 4 (N04D) years and grazed by bison. In 2011, N02B will have woody riparian vegetation removed along the entire stream length. The Shane Creek site (SHAN) is currently ungrazed and burned most years. In 2011 the treatment will be switched to grazing and burning of 1/3 of the watershed every year. The data include before and during-treatment sampling for both experiments.
DOI: 10.5281/zenodo.55088
title: Fragbinpacking-Results V1.0

description: Results for the Fragmentable Items Bin Packing Problem
DOI: 10.5281/zenodo.55089
title: Fragbinpacking-Problems V1.0

description: Problem Sets for the Fragmentable Items Bin Packing Problem
DOI: 10.5281/zenodo.1472235
title: Yeast 1-hybrid screens for upstream regulators of A. thaliana AGO1, AGO7, and AGO10: ranked tables of candidate direct upstream TFs

description: This Excel file supplements a paper by Hoyer et al. (2019): https://doi.org/10.1002/pld3.102

The file includes lists of TFs from twelve automated Y1H screens, for user convenience. The first sheet describes the columns. A separate Zenodo record (1345229) includes the raw data and code showing how the data were processed to generate these twelve tables.
DOI: 10.17909/zstj-7q06
title: HST data for the paper Stellar populations in a z~3.25 Ly-alpha emitting group associated to a damped Ly-alpha absorber. 

description: F160W imaging observations targeting a Ly-alpha nebula associated associated with DLA 15-H3 from Fumagalli et al. 2017. Note that exposure idk001imq is bad due to a failed guide star re-acquisition.
DOI: 10.5287/bodleian:zr0var78q
title: 'Hepitopes': A Database of HLA Class I Epitopes in Hepatitis B Virus (HBV)

description: Chronic infection with hepatitis b virus (HBV) is a global health problem estimated to affect 240 million people worldwide. A successful prophylactic vaccine has contributed to lowering the incidence, but individuals with established infection often remain committed to life-long antiviral therapy. For these reasons, increased clinical and scientific scrutiny is being applied to develop new therapeutic approaches with an ultimate goal of achieving cure. The adaptive immune response is recognized to play a crucial role in containment and clearance of chronic viral infections. Defining the optimum natural immune responses that hinge on HLA-class I mediated epitope presentation to CD8+ cytotoxic T lymphocytes may help to inform novel immunotherapeutic strategies. We therefore performed a systematic literature review to identify all published HLA Class I epitopes in HBV. We also collected information regarding the methods used to define the epitope, and any reported associations between an immune response to this epitope and disease outcome. The resulting database, 'Hepitopes', is available at http://www.expmedndm.ox.ac.uk/hepitopes. This database will be maintained as a live open access resource that is refined and updated over time. This database represents a unique new resource, and is an important foundation for ongoing investigations into the nature and impact of the HLA Class I mediated CD8+ T cell response to HBV infection.
This work was funded by a Wellcome Trust fellowship.
DOI: 10.6084/m9.figshare.4015824
title: 'Hepitopes': A Database of HLA Class I Epitopes in Hepatitis B Virus

description: This is a spreadsheet containing the results of a systematic literature review to identify and curate all known and putative HLA Class I epitopes in hepatitis B virus (HBV). We performed our literature review in January 2016, searching Medline and Embase via the OVID search interface made available by the University of Oxford. No date restrictions were imposed; Medline was searched from 1946-2016 and Embase from 1974-2016. The relevant subject headings for Epitopes, HLA Antigens, CD8 Antigens and Hepatitis B from the thesauri (MESH and EMTREE) were exploded and searched. In addition the terms epitope* (to pick up singular and plural) and Hepatitis B and HBV were searched in the title and abstract fields. We also identified additional references by searching the bibliographies of relevant articles. As well as details of each citation, we recorded the HBV protein and sequence-numbered location of each epitope (based on a published reference strain; Liu WC, et al. Aligning to the sample-specific reference sequence to optimize the accuracy of next-generation sequencing analysis for hepatitis B virus. <i>Hepatol Int</i> 2016;10:147-157). Each citation was reviewed by a primary reviewer and then again by a second expert to ensure the records are as accurate as possible. Over time, we aim to update and refine the dataset such that it becomes a growing resource for virologists, immunologists and those in the field of vaccine design.A live interactive version can be viewed at http://www.expmedndm.ox.ac.uk/hepitopes.The visualisation code can be viewed at https://github.com/ox-it/hepitopes. As the database is updated and refined, we will submit updated versions to Figshare. In parallel, we have uploaded a static version to Oxford Research Archive (ORA) at the point of initial publication; DOI: 10.5287/bodleian:zr0VAr78q
DOI: 10.5281/zenodo.34433
title: Hubbardbenchmarks_Data: Version 1.0

description: This is the main directory for the 2D Hubbard benchmark data.

Please see the README file for the full description.
DOI: 10.6084/m9.figshare.20383390
title: Estimating Knee Movement Patterns of Recreational Runners Across Training Sessions Using Multilevel Functional Regression Models

description: Modern wearable monitors and laboratory equipment allow the recording of high-frequency data that can be used to quantify human movement. However, currently, data analysis approaches in these domains remain limited. This article proposes a new framework to analyze biomechanical patterns in sport training data recorded across multiple training sessions using multilevel functional models. We apply the methods to subsecond-level data of knee location trajectories collected in 19 recreational runners during a medium-intensity continuous run (MICR) and a high-intensity interval training (HIIT) session, with multiple steps recorded in each participant-session. We estimate functional intra-class correlation coefficient to evaluate the reliability of recorded measurements across multiple sessions of the same training type. Furthermore, we obtained a vectorial representation of the three hierarchical levels of the data and visualize them in a low-dimensional space. Finally, we quantified the differences between genders and between two training types using functional multilevel regression models that incorporate covariate information. We provide an overview of the relevant methods and make both data and the R code for all analyses freely available online on GitHub. Thus, this work can serve as a helpful reference for practitioners and guide for a broader audience of researchers interested in modeling repeated functional measures at different resolution levels in the context of biomechanics and sports science applications.
DOI: 10.6084/m9.figshare.20383390.v2
title: Estimating Knee Movement Patterns of Recreational Runners Across Training Sessions Using Multilevel Functional Regression Models

description: Modern wearable monitors and laboratory equipment allow the recording of high-frequency data that can be used to quantify human movement. However, currently, data analysis approaches in these domains remain limited. This article proposes a new framework to analyze biomechanical patterns in sport training data recorded across multiple training sessions using multilevel functional models. We apply the methods to subsecond-level data of knee location trajectories collected in 19 recreational runners during a medium-intensity continuous run (MICR) and a high-intensity interval training (HIIT) session, with multiple steps recorded in each participant-session. We estimate functional intra-class correlation coefficient to evaluate the reliability of recorded measurements across multiple sessions of the same training type. Furthermore, we obtained a vectorial representation of the three hierarchical levels of the data and visualize them in a low-dimensional space. Finally, we quantified the differences between genders and between two training types using functional multilevel regression models that incorporate covariate information. We provide an overview of the relevant methods and make both data and the R code for all analyses freely available online on GitHub. Thus, this work can serve as a helpful reference for practitioners and guide for a broader audience of researchers interested in modeling repeated functional measures at different resolution levels in the context of biomechanics and sports science applications.
DOI: 10.5281/zenodo.7860652
title: Inferring the Astrophysical Population of Gravitational Wave Sources in the Presence of Noise Transients Data Release

description: Data release for paper "Inferring the Astrophysical Population of Gravitational Wave Sources in the Presence of Noise Transients." To read in one of the result files and obtain the posterior samples, type <pre><code class="language-python">import bilby result = bilby.core.result.read_in_result(filename="contaminant_0_result.json") samples = result.posterior</code></pre>