cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1451280
title: Supplementary Table 1

description: Sample information: Fish # refers to the number of the fish within a Code. Code refers to a unique sampling attempt. Location refers to geographic location (as such there are groups with the same location, but a different code, indicating more than one sampling attempt at one location). RAD library indicates which of the 6 libraries each fish was sequenced in. Plate Morph indicates whether the fish is nonplated, lowplated, or full plated. Plate number is an actual plate count, performed for most freshwater fish, and in Notes it is noted whether this particular fish was excluded from certain analyses.
DOI: 10.6084/m9.figshare.1451285.v1
title: Forecasting Financial Extremes: A Network Degree Measure

description: This is the data file supporting the research in the following paper: W. Yan and E. van Tuyll, Forecasting Financial Extremes: A Network Degree Measure
DOI: 10.6084/m9.figshare.1451279
title: PLoS_dataset

description: minimal data for PLoS submission
DOI: 10.6084/m9.figshare.1451280.v1
title: Supplementary Table 1

description: Sample information: Fish # refers to the number of the fish within a Code. Code refers to a unique sampling attempt. Location refers to geographic location (as such there are groups with the same location, but a different code, indicating more than one sampling attempt at one location). RAD library indicates which of the 6 libraries each fish was sequenced in. Plate Morph indicates whether the fish is nonplated, lowplated, or full plated. Plate number is an actual plate count, performed for most freshwater fish, and in Notes it is noted whether this particular fish was excluded from certain analyses.
DOI: 10.17632/6wrtv5fgmf.2
title: Structured Versus Unstructured Questions for Formative Assessment in Physiology: A comparative study among Phase 1 MBBS students.

description: Medical education has opened up to accept many changing concepts in the field of education. Physiology question papers in our university so far have been open ended and not structured ones. Answers for open-ended questions are also a subject to bias during evaluation. This also has a greatly influenced their study pattern and also their performance in the exams. Objectives: 1.To assess of performance of Phase 1 MBBS students with structured questions to conventional questions in formative assessment. 2. To compare perception of Phase 1 MBBS students towards structured questions versus conventional questions in formative assessment. Methodology: Six formative assessments were done on Phase 1 MBBS students. Only those students present on the day of exam were considered. They were divided into 2 groups, one group received structured questions and the other received unstructured questions for the assessments. Each of the assessment was of one hour duration and carried 40 marks. Perception was taken at the end for both the formats of assessments. Results: The performance is compared by Independent t test. Overall mean marks scored by students with structured questions is 14.29 ±5.57 and with unstructured questions is 14.643 ±6.07. Similar performance is seen in all the six assessments and there is no significant difference in the marks scored by the students. A significant number of the student disagreed that structured questions helped score better. Conclusion: This study shows that there is no difference in performance of students with respect to structured or unstructured questions for formative assessment. Keywords: Structured questions, unstructured questions, formative assessment.
DOI: 10.6084/m9.figshare.1451244
title: Inferring neuronal dynamics from calcium imaging data using biophysical models and Bayesian inference

description: Zip file containing experimental (calcium imaging and electrophysiological) data which we used in our paper (Rahmati et al. 2016) published in PLOS Computational Biology:http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004736In this paper, we developed a novel method for analyzing calcium imaging data called CaBBI (Calcium imaging analysis using Biophysical models and Bayesian Inference). The Matlab code implementing CaBBI is publicly available as a part of VBA toolbox. Please see this link:http://mbb-team.github.io/VBA-toolbox/wiki/CaBBI/
DOI: 10.6084/m9.figshare.1451244.v1
title: Inferring neuronal dynamics from calcium imaging data using biophysical models and Bayesian inference

description: Zip file containing experimental (calcium imaging and electrophysiological) data which we used in our paper (Rahmati et al. 2016) published in PLOS Computational Biology:http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004736In this paper, we developed a novel method for analyzing calcium imaging data called CaBBI (Calcium imaging analysis using Biophysical models and Bayesian Inference). The Matlab code implementing CaBBI is publicly available as a part of VBA toolbox. Please see this link:http://mbb-team.github.io/VBA-toolbox/wiki/CaBBI/
DOI: 10.6084/m9.figshare.1451230
title: Models, tools and codes for FSPN

description: Two models: yeast-polarization, virus infection; Tool: snoopy; Code: Matlab Codes of Simulation Algorithm
DOI: 10.6084/m9.figshare.1450835
title: PCA of 23andMe data from openSNP + HapMap

description: A simple PCA plot done with ~1400 23andMe data sets found on openSNP + the HapMap data. A list of ~100 Ancestry Informative Markers, from http://www.biomedcentral.com/1471-2156/10/39, was used for the PCA. Data mangling was done using PLINK. PCA was run with smartpca, without any optimizing for outliers. Plotting done with R + ggplot2. HapMap population keys can be found here: https://www.sanger.ac.uk/resources/downloads/human/hapmap3.html
DOI: 10.6084/m9.figshare.1450842
title: Richards Equation Inversion

description: Fluid flow in the vadose zone is governed by Richards equation and parameterized by hydraulic conductivity, which is a non-linear function of pressure head. Investigations in the vadose zone typically require identifications of distributed hydraulic properties. This is increasingly being done through a data-driven approach, using changes in saturation or pressure head to infer hydraulic parameters. Hydrogeophysics allows many more proxy measurements to be taken to help characterize these sites spatially, as well as through time. As such, the number of distributed hydraulic parameters to be estimated in a Richards equation inversion will continue to grow. In this paper, we will describe an efficient technique to invert for hydraulic properties in 3D given a realistic data set. Our algorithm does not store the Jacobian, but rather computes the effect on a vector allowing the size of the problem that we can invert to become much larger. We show our algorithm in practice for a large 3D inversion of saturated hydraulic conductivity using saturation data through time. The code to run our examples is open source, and the algorithm presented allows this inversion process to run on modest computational resources.
DOI: 10.6084/m9.figshare.1450825
title: WingsPElements_Rep1

description: These are the raw images associated with I. Dworkin and G. Gibson, “Epidermal growth factor receptor and transforming growth factor-beta signaling contributes to variation for wing shape in Drosophila melanogaster.,” Genetics, vol. 173, no. 3, pp. 1417–1431, Jul. 2006. doi:10.1534/genetics.105.053868 A subset of these were also used in doi:10.1534/genetics.110.125922 In brief 50 mutations (modified P-elements marked by a mini-white) were introduced into each of two wild type backgrounds (Samarkand and Oregon-R) via 10 generations of backcrossing. Flies were grown in a density, temperature and light controlled manner (see paper) allowed to eclose, sclerotize and then were stored in ethanol prior to dissection. Wings were dissected and then imaged. These are those images. The landmark data (for geometric morphometric analysis) can be found on DRYAD http://dx.doi.org/10.5061/dryad.8371 Please note: For simplicity I have uploaded all of the images on figshare into two seperate filesets (WingsPelements_Rep1 and WingsPelements_Rep2). You will want to have both of them! Notes on naming conventions:GeneticBackground_BloomingtonStockNumber_genotype_sex_individual Where Genetic Background is either Ore (Oregon-R) or Sam (Samarkand). The two wild-type strains the mutations were introgressed into. BloomingtonStockNumber: Is the number for the strains from the Bloomington Stock center at the time of ordering. See the NamesOfMutants.csv for all the details about gene and allele info. genotype: whether the individuals emerged had the P-element insertion (p) meaning they are mutant, or they had white (w) eyes (without the insertion) and were thus wild type for the gene in question. sex: male or female individual. The individual fly. So<br>Sam_02513_w_M_00010.jpg would be from the cross with the insertion 02513 (allele of argos) in the Samarkand background, but without the mutant allele of argos (as they are "w" for genotype) and male. As the replicates were done seperately, they were accidently not coded with rep1 and rep2 in the image names, so I kept them seperate. However, they do represent distinict individuals grown seperately. Notes on all images: I did not notice until the discs with images were copied that one of the two undergrads who digitally captured wings, would only take a single image, when two complete wings were in the image. Therefore , for some lines the numbers appear small. What I manually had to do was go through each folder and look at the thumbnails to see which images I needed to make duplicates of prior to making TPS files for morphometrics. Depending on your goals a similar approach may be necessary.
DOI: 10.6084/m9.figshare.1450842.v2
title: Richards Equation Inversion

description: Fluid flow in the vadose zone is governed by Richards equation and parameterized by hydraulic conductivity, which is a non-linear function of pressure head. Investigations in the vadose zone typically require identifications of distributed hydraulic properties. This is increasingly being done through a data-driven approach, using changes in saturation or pressure head to infer hydraulic parameters. Hydrogeophysics allows many more proxy measurements to be taken to help characterize these sites spatially, as well as through time. As such, the number of distributed hydraulic parameters to be estimated in a Richards equation inversion will continue to grow. In this paper, we will describe an efficient technique to invert for hydraulic properties in 3D given a realistic data set. Our algorithm does not store the Jacobian, but rather computes the effect on a vector allowing the size of the problem that we can invert to become much larger. We show our algorithm in practice for a large 3D inversion of saturated hydraulic conductivity using saturation data through time. The code to run our examples is open source, and the algorithm presented allows this inversion process to run on modest computational resources.
DOI: 10.6084/m9.figshare.1450842.v1
title: Richards Equation Inversion

description: Fluid flow in the vadose zone is governed by Richards equation and parameterized by hydraulic conductivity, which is a non-linear function of pressure head. Investigations in the vadose zone typically require identifications of distributed hydraulic properties. This is increasingly being done through a data-driven approach, using changes in saturation or pressure head to infer hydraulic parameters. Hydrogeophysics allows many more proxy measurements to be taken to help characterize these sites spatially, as well as through time. As such, the number of distributed hydraulic parameters to be estimated in a Richards equation inversion will continue to grow. In this paper, we will describe an efficient technique to invert for hydraulic properties in 3D given a realistic data set. Our algorithm does not store the Jacobian, but rather computes the effect on a vector allowing the size of the problem that we can invert to become much larger. We show our algorithm in practice for a large 3D inversion of saturated hydraulic conductivity using saturation data through time. The code to run our examples is open source, and the algorithm presented allows this inversion process to run on modest computational resources.
DOI: 10.6084/m9.figshare.1450825.v2
title: WingsPElements_Rep1

description: These are the raw images associated with I. Dworkin and G. Gibson, “Epidermal growth factor receptor and transforming growth factor-beta signaling contributes to variation for wing shape in Drosophila melanogaster.,” Genetics, vol. 173, no. 3, pp. 1417–1431, Jul. 2006. doi:10.1534/genetics.105.053868 A subset of these were also used in doi:10.1534/genetics.110.125922 In brief 50 mutations (modified P-elements marked by a mini-white) were introduced into each of two wild type backgrounds (Samarkand and Oregon-R) via 10 generations of backcrossing. Flies were grown in a density, temperature and light controlled manner (see paper) allowed to eclose, sclerotize and then were stored in ethanol prior to dissection. Wings were dissected and then imaged. These are those images. The landmark data (for geometric morphometric analysis) can be found on DRYAD http://dx.doi.org/10.5061/dryad.8371 Please note: For simplicity I have uploaded all of the images on figshare into two seperate filesets (WingsPelements_Rep1 and WingsPelements_Rep2). You will want to have both of them! Notes on naming conventions:GeneticBackground_BloomingtonStockNumber_genotype_sex_individual Where Genetic Background is either Ore (Oregon-R) or Sam (Samarkand). The two wild-type strains the mutations were introgressed into. BloomingtonStockNumber: Is the number for the strains from the Bloomington Stock center at the time of ordering. See the NamesOfMutants.csv for all the details about gene and allele info. genotype: whether the individuals emerged had the P-element insertion (p) meaning they are mutant, or they had white (w) eyes (without the insertion) and were thus wild type for the gene in question. sex: male or female individual. The individual fly. So<br>Sam_02513_w_M_00010.jpg would be from the cross with the insertion 02513 (allele of argos) in the Samarkand background, but without the mutant allele of argos (as they are "w" for genotype) and male. As the replicates were done seperately, they were accidently not coded with rep1 and rep2 in the image names, so I kept them seperate. However, they do represent distinict individuals grown seperately. Notes on all images: I did not notice until the discs with images were copied that one of the two undergrads who digitally captured wings, would only take a single image, when two complete wings were in the image. Therefore , for some lines the numbers appear small. What I manually had to do was go through each folder and look at the thumbnails to see which images I needed to make duplicates of prior to making TPS files for morphometrics. Depending on your goals a similar approach may be necessary.
DOI: 10.6084/m9.figshare.1450825.v1
title: WingsPElements_Rep1

description: These are the raw images associated with I. Dworkin and G. Gibson, “Epidermal growth factor receptor and transforming growth factor-beta signaling contributes to variation for wing shape in Drosophila melanogaster.,” Genetics, vol. 173, no. 3, pp. 1417–1431, Jul. 2006. doi:10.1534/genetics.105.053868 A subset of these were also used in doi:10.1534/genetics.110.125922 In brief 50 mutations (modified P-elements marked by a mini-white) were introduced into each of two wild type backgrounds (Samarkand and Oregon-R) via 10 generations of backcrossing. Flies were grown in a density, temperature and light controlled manner (see paper) allowed to eclose, sclerotize and then were stored in ethanol prior to dissection. Wings were dissected and then imaged. These are those images. The landmark data (for geometric morphometric analysis) can be found on DRYAD http://dx.doi.org/10.5061/dryad.8371
DOI: 10.6084/m9.figshare.1450783
title: HymHub v0.1.0: a data resource supporting social insect comparative genomics research

description: The file <strong>summary-stats.tar.bz2</strong> contains tables of summary statistics describing various genomic features from 16 Hymenopteran species and outgroups. The other files contain the sequence and annotation files from which the summary statistics were computed, organized by species. See the links below for more details. This version v0.1.0, released on June 16, 2015, is an update to v0.0.1, released on February 12, 2015.
DOI: 10.6084/m9.figshare.1450783.v1
title: HymHub v0.1.0: a data resource supporting social insect comparative genomics research

description: The file <strong>summary-stats.tar.bz2</strong> contains tables of summary statistics describing various genomic features from 16 Hymenopteran species and outgroups. The other files contain the sequence and annotation files from which the summary statistics were computed, organized by species. See the links below for more details. This version v0.1.0, released on June 16, 2015, is an update to v0.0.1, released on February 12, 2015.
DOI: 10.6084/m9.figshare.1450709
title: Data from “Environmental correlates of species rank – abundance distributions in global drylands”

description: Data from Ulrich, W., S. Soliveres, A. Thomas, A. Dougill & F. T. Maestre. Environmental correlates of species rank – abundance distributions in global drylands. <i>Perspectives in Plant Ecology, Evolution and Systematics</i>, doi:10.1016/j.ppees.2016.04.004<br><br>There are two spreadsheets with data. The spreadsheet "Data" contains the data used in the manuscript. The spreadsheet "Metadata" contains the associated metadata, where a description of all the variables and units can be found. All the methodological details can be found in the article.<br>
DOI: 10.17632/dcfhvrrkb5.1
title: Dermal invasion of SUM in each nail subunit and correlation with Breslow depth, the total involvement score, and disease free survival

description: Abbreviations: H0, No hyponychium invasion; H1, Hyponychium invasion; NB0, No nail bed invasion; NB1, nail bed invasion; DNM0, no distal nail matrix invasion; DNM1, distal nail matrix invasion; PNM0, no proximal nail matrix invasion; PNM1, proximal nail matrix invasion; PNF0, no invasion in dorsal roof of proximal nail fold; PNF1, invasion in dorsal roof of proximal nail fold * indicates significant differences according to the Mann-Whitney U test with p &lt;0.05 † indicates significant differences in survival curve according to the log-rank test with p-value&lt;0.05
DOI: 10.6084/m9.figshare.1450582
title: Gaussian Job Archive for C70H114N2Si4(3)

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.6084/m9.figshare.1450582.v1
title: Gaussian Job Archive for C70H114N2Si4(3)

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.17632/mvr7m6mcgp.2
title: Ambient-Loaded Citrus in Refrigerated Containers - Effect of Package Design

description: This data is from a submitted (currently under review) research paper titled: "Cooling of Ambient-Loaded Citrus in Refrigerated Containers: What Impact Do Packaging and Loading Temperature play?" The experimental design and setup for the collection of this data are listed in detail in this paper.
DOI: 10.6084/m9.figshare.1449296
title: BEP simulation results

description: Cancer evolution simulations based on the BEP model were performed for different combinations of 4 parameter values: s (stem cell hierarchy), r (mutation rate), d (number of driver genes) and f (strength of driver mutations).<br>From 20 independent simulation instances, averaged 6 statistics were obtained: ε (population entropy), μ (founder mutation count), ρ (average mutation count), λ (population fitness), τ (growth time) and θ (self-similarity). The results can be interactively explored at our web site: http://bep.hgc.jp
DOI: 10.6084/m9.figshare.1449297
title: Access to art scholarship in Latin America

description: Data on the availability to two art history journals at 60 Latin American universities.
DOI: 10.6084/m9.figshare.1449297.v1
title: Access to art scholarship in Latin America

description: Data on the availability to two art history journals at 60 Latin American universities.
DOI: 10.6084/m9.figshare.1449286
title: Soil microbial communities Barro Colorado

description: Sequence information (16S for bacteria and ITS1 for fungi) from soil samples collected in Barro Colorado Island (BCI).
DOI: 10.6084/m9.figshare.1449296.v1
title: results of BEP simulation

description: Cancer evolution simulations based on the BEP model were performed for different combinations of 4 parameter values: s (stem cell hierarchy), r (mutation rate), d (number of driver genes) and f (strength of driver mutations).<br>From 20 independent simulation instances, averaged 6 statistics were obtained: ε (population entropy), μ (founder mutation count), ρ (average mutation count), λ (population fitness), τ (growth time) and θ (self-similarity).
DOI: 10.17632/hjg4d9c843.1
title: TopoAna: A generic tool for the event type analysis of inclusive Monte-Carlo samples in high energy physics experiments

description: Inclusive Monte-Carlo samples are indispensable for signal selection and background suppression in many high energy physics experiments. A clear knowledge of the physics processes involved in the samples, including the types of processes and the number of processes in each type, is a great help to investigating signals and backgrounds. To help analysts obtain the physics process information from the truth information of the samples, we develop a physics process analysis program, TopoAna, with C++, ROOT, and LaTeX. The program implements the functionalities of component analysis and signal identification with many kinds of fine, customizable classification and matching algorithms. It tags physics processes in individual events accurately in the output root files, and exports the physics process information at the sample level clearly to the output plain text, tex source, and pdf files. Independent of specific software frameworks, the program is applicable to many experiments. At present, it has come into use in three e^+ e^- colliding experiments: the BESIII, Belle, and Belle II experiments. The use of the program in other similar experiments is also prospective.
DOI: 10.6084/m9.figshare.1449281
title: Sphingosine-1-phosphate lyase deficient cells as a tool to study protein lipid interactions

description: Orginal and unmodified datafiles used in the publication: Sphingosine-1-phosphate lyase deficient cells as a tool to study protein lipid interactions Mathias J. Gerl1*, Verena Bittl1, Susanne Kirchner1, Timo Sachsenheimer1, Hanna L. Brunner1, Christian Lüchtenborg1, Cagakan Özbalci1, Hannah Wiedemann1, Sabine Wegehingel1, Walter Nickel1, Per Haberkant2, Carsten Schultz2, Marcus Krüger3 and Britta Brügger1* 1 Heidelberg University Biochemistry Center, Heidelberg, Germany. 2 European Molecular Biology Laboratory, Heidelberg, Germany. 3 CECAD, Cologne, Germany. *Corresponding authors Email: Mathias.Gerl@bzh.uni-heidelberg.de (MJG); britta.bruegger@bzh.uni-heidelberg.de (BB)
DOI: 10.6084/m9.figshare.1449281.v1
title: Sphingosine-1-phosphate lyase deficient cells as a tool to study protein lipid interactions

description: Orginal and unmodified datafiles used in the publication: Sphingosine-1-phosphate lyase deficient cells as a tool to study protein lipid interactions Mathias J. Gerl1*, Verena Bittl1, Susanne Kirchner1, Timo Sachsenheimer1, Hanna L. Brunner1, Christian Lüchtenborg1, Cagakan Özbalci1, Hannah Wiedemann1, Sabine Wegehingel1, Walter Nickel1, Per Haberkant2, Carsten Schultz2, Marcus Krüger3 and Britta Brügger1* 1 Heidelberg University Biochemistry Center, Heidelberg, Germany. 2 European Molecular Biology Laboratory, Heidelberg, Germany. 3 CECAD, Cologne, Germany. *Corresponding authors Email: Mathias.Gerl@bzh.uni-heidelberg.de (MJG); britta.bruegger@bzh.uni-heidelberg.de (BB)