cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7068368
title: RIP-CHIP_egrfiles from <i>mmi1</i> and <i>rep2</i> mRNAs are novel RNA targets of the Mei2 RNA binding protein during early meiosis in <i>Schizosaccharomyces pombe</i>

description: The RNA-binding protein Mei2 is crucial for meiosis in <i>Schizosaccharomyces pombe.</i> In <i>mei2</i> mutants, pre-meiotic S-phase is blocked, along with meiosis. Mei2 binds a long non-coding RNA (lncRNA) called meiRNA, which is a ‘sponge RNA’ for the meiotic inhibitor protein Mmi1. The interaction between Mei2, meiRNA and Mmi1 protein is essential for meiosis. But <i>mei2</i> mutants have stronger and different phenotypes than meiRNA mutants, since <i>mei2Δ</i> arrests before pre-meiotic S, while the meiRNA mutant arrests after pre-meiotic S but before meiosis. This suggests Mei2 may bind additional RNAs. To identify novel RNA targets of Mei2, which might explain how Mei2 regulates pre-meiotic S, we used RNA Immunoprecipitation and Cross-linking Immunoprecipitation. In addition to meiRNA, we found the mRNAs for <i>mmi1</i> (which encodes Mmi1) and for the S-phase transcription factor <i>rep2</i>. There were also three other RNAs of uncertain relevance. We suggest that at meiotic initiation, Mei2 may sequester <i>rep2</i> mRNA to help allow pre-meiotic S, and then may bind both meiRNA and <i>mmi1</i> mRNA to inactivate Mmi1 at two levels, the protein level (as previously known), and also the mRNA level, allowing meiosis. We call Mei2–meiRNA a ‘double sponge’ (i.e. binding both an mRNA, and its encoded protein).
DOI: 10.6084/m9.figshare.7068362.v1
title: Supplementary Table 4 - Strains and primers from <i>mmi1</i> and <i>rep2</i> mRNAs are novel RNA targets of the Mei2 RNA binding protein during early meiosis in <i>Schizosaccharomyces pombe</i>

description: The RNA-binding protein Mei2 is crucial for meiosis in <i>Schizosaccharomyces pombe.</i> In <i>mei2</i> mutants, pre-meiotic S-phase is blocked, along with meiosis. Mei2 binds a long non-coding RNA (lncRNA) called meiRNA, which is a ‘sponge RNA’ for the meiotic inhibitor protein Mmi1. The interaction between Mei2, meiRNA and Mmi1 protein is essential for meiosis. But <i>mei2</i> mutants have stronger and different phenotypes than meiRNA mutants, since <i>mei2Δ</i> arrests before pre-meiotic S, while the meiRNA mutant arrests after pre-meiotic S but before meiosis. This suggests Mei2 may bind additional RNAs. To identify novel RNA targets of Mei2, which might explain how Mei2 regulates pre-meiotic S, we used RNA Immunoprecipitation and Cross-linking Immunoprecipitation. In addition to meiRNA, we found the mRNAs for <i>mmi1</i> (which encodes Mmi1) and for the S-phase transcription factor <i>rep2</i>. There were also three other RNAs of uncertain relevance. We suggest that at meiotic initiation, Mei2 may sequester <i>rep2</i> mRNA to help allow pre-meiotic S, and then may bind both meiRNA and <i>mmi1</i> mRNA to inactivate Mmi1 at two levels, the protein level (as previously known), and also the mRNA level, allowing meiosis. We call Mei2–meiRNA a ‘double sponge’ (i.e. binding both an mRNA, and its encoded protein).
DOI: 10.6084/m9.figshare.7068368.v1
title: RIP-CHIP_egrfiles from <i>mmi1</i> and <i>rep2</i> mRNAs are novel RNA targets of the Mei2 RNA binding protein during early meiosis in <i>Schizosaccharomyces pombe</i>

description: The RNA-binding protein Mei2 is crucial for meiosis in <i>Schizosaccharomyces pombe.</i> In <i>mei2</i> mutants, pre-meiotic S-phase is blocked, along with meiosis. Mei2 binds a long non-coding RNA (lncRNA) called meiRNA, which is a ‘sponge RNA’ for the meiotic inhibitor protein Mmi1. The interaction between Mei2, meiRNA and Mmi1 protein is essential for meiosis. But <i>mei2</i> mutants have stronger and different phenotypes than meiRNA mutants, since <i>mei2Δ</i> arrests before pre-meiotic S, while the meiRNA mutant arrests after pre-meiotic S but before meiosis. This suggests Mei2 may bind additional RNAs. To identify novel RNA targets of Mei2, which might explain how Mei2 regulates pre-meiotic S, we used RNA Immunoprecipitation and Cross-linking Immunoprecipitation. In addition to meiRNA, we found the mRNAs for <i>mmi1</i> (which encodes Mmi1) and for the S-phase transcription factor <i>rep2</i>. There were also three other RNAs of uncertain relevance. We suggest that at meiotic initiation, Mei2 may sequester <i>rep2</i> mRNA to help allow pre-meiotic S, and then may bind both meiRNA and <i>mmi1</i> mRNA to inactivate Mmi1 at two levels, the protein level (as previously known), and also the mRNA level, allowing meiosis. We call Mei2–meiRNA a ‘double sponge’ (i.e. binding both an mRNA, and its encoded protein).
DOI: 10.6084/m9.figshare.7068332
title: RGB-orthomosaic Dietersheimer Brenne

description: Processed orthomosaic generalized to a spatial resolution of 1m RGB.
DOI: 10.6084/m9.figshare.7068332.v1
title: RGB-orthomosaic Dietersheimer Brenne

description: Processed orthomosaic generalized to a spatial resolution of 1m RGB.
DOI: 10.6084/m9.figshare.7068320
title: Age, petrologic significance and provenance analysis of the Hamedan low-pressure migmatites; Sanandaj-Sirjan Zone, west Iran

description: Meta-pelitic rocks with interlayers of meta-psammites within the inner thermal aureole of the Alvand plutonic complex (Sanandaj-Sirjan Zone (SaSZ), western Iran) underwent partial melting; generating various types of migmatites. The mesosome of the Hamedan migmatites is classified into two groups: (1) cordierite-rich and Al-silicate-poor mesosomes and (2) cordierite-poor, Al-silicate-rich groups. Leucosomes are also variable, ranging from plagioclase-rich to K-feldspar-rich leucosomes. Mineral-chemical studies and thermobarometric estimations indicate temperature and pressure of 640–700°C and 3–5 kbar, respectively, for the formation of mesosomes. U–Pb zircon geochronology on 214 grains from the mesosome of migmatites indicates ages of 160–180 Ma (ca ~170 Ma) for zircon metamorphic rims and variable ages of 190–2590 Ma for the inherited detrital zircon cores. Inherited core ages show various age populations, but age populations at 200–600 Ma are more frequent. The age populations of the detrital zircons clarify that the provenance of the younger zircon grains (200–500 Ma) was more likely the Iranian plate, whereas the older grains (600 Ma to &gt;2.5 Ga) may be sourced from both northern Gondwana (such as Arabian-Nubian Shield) and the neighbouring, old cratons like as Africa. We suggest that magmatic activities, especially mafic plutonism at ~167 Ma, are the main triggers for the heat source of metamorphism, partial melting, and migmatization. In contrast to a presumed idea for a Cretaceous regional metamorphic event in the NW parts of the SaSZ, this study attests that the metamorphism should be older and can be associated with Jurassic magmatic pulses.
DOI: 10.6084/m9.figshare.7068311
title: Wrong, but useful: regional species distribution models may not be improved by range‐wide data under biased sampling - Main figures

description: <b>Figure 1:</b> The distribution of <i>Asellia tridens </i>at spatial (a) and environmental (b) space. The map a shows the species‐specific global extent of this species, with dots representing the spatial distribution at global (blue) and regional (black) scales. Panel b shows a scatterplot of the first two PCA axes of all available environmental covariates within the entire study area. The first two axes account for 94.2% of the environmental variation. Blue and black dots are presence locations of the species outside and inside Egypt, respectively; light gray points are pixels without any sightings at global scale; dark gray points represent the available environmental space in Egypt. Figure S1 shows equivalent plot for all study species together.<br><br><b>Figure 2:</b> Mean permutation importance of environmental variables used at global (left) and regional (right) models (from Maxent). Dots and error bars represent the overall mean and standard deviation of the average permutation importance of the seventeen study species, respectively. Blue dots/bars represent environment‐only models; red dots/bars represent comparable models with accessibility bias variables incorporated as predictors. When included, bias predictors have a high contribution (particularly distance to main cities at both scales, and distance to roads in Egypt), compared to many environmental variables. For more details on the environmental variables used, see Table S2.<br><br><b>Figure 3:</b> Boxplots for the geographical congruence (Schoener's D) between mean predictions of global and regional models for Egypt (with no priors). Schoener's D ranges from zero to one, representing situations of no to full congruence, respectively. “Env‐only” are models calibrated only with environmental variables. “Bias‐predictor” models add accessibility bias variables as predictors to the model. “Bias‐corrected” models also use bias variables to set bias to zero during prediction (i.e., bias factored-out).<br><br><b>Figure 4: </b>Boxplots for the mean AUC values (on cross‐validation) calculated for different options of modeling algorithms, bias manipulations, and priors. (a) A comparison between mean AUC values of no‐prior regional models and equivalent models that use different options of priors (without regional bias incorporated as predictors). (b) Same as a, with regional bias variables included as predictors.<br><br><b>Figure 5:</b> Geographical congruence between the predictions of regional SDMs calibrated without priors and the three versions of regional models that used a prior variable. Bias variables were not incorporated as predictors in the regional SDMs. There were three options of prior options: “Env‐only” are predictions of global SDMs without incorporating sampling bias; “Bias‐predictor” priors incorporate global accessibility bias variables as predictors in the model; and “Bias‐corrected” priors incorporate bias‐corrected (set to zero) predictions from global models for Egypt.<br>
DOI: 10.6084/m9.figshare.7068320.v1
title: Age, petrologic significance and provenance analysis of the Hamedan low-pressure migmatites; Sanandaj-Sirjan Zone, west Iran

description: Meta-pelitic rocks with interlayers of meta-psammites within the inner thermal aureole of the Alvand plutonic complex (Sanandaj-Sirjan Zone (SaSZ), western Iran) underwent partial melting; generating various types of migmatites. The mesosome of the Hamedan migmatites is classified into two groups: (1) cordierite-rich and Al-silicate-poor mesosomes and (2) cordierite-poor, Al-silicate-rich groups. Leucosomes are also variable, ranging from plagioclase-rich to K-feldspar-rich leucosomes. Mineral-chemical studies and thermobarometric estimations indicate temperature and pressure of 640–700°C and 3–5 kbar, respectively, for the formation of mesosomes. U–Pb zircon geochronology on 214 grains from the mesosome of migmatites indicates ages of 160–180 Ma (ca ~170 Ma) for zircon metamorphic rims and variable ages of 190–2590 Ma for the inherited detrital zircon cores. Inherited core ages show various age populations, but age populations at 200–600 Ma are more frequent. The age populations of the detrital zircons clarify that the provenance of the younger zircon grains (200–500 Ma) was more likely the Iranian plate, whereas the older grains (600 Ma to &gt;2.5 Ga) may be sourced from both northern Gondwana (such as Arabian-Nubian Shield) and the neighbouring, old cratons like as Africa. We suggest that magmatic activities, especially mafic plutonism at ~167 Ma, are the main triggers for the heat source of metamorphism, partial melting, and migmatization. In contrast to a presumed idea for a Cretaceous regional metamorphic event in the NW parts of the SaSZ, this study attests that the metamorphism should be older and can be associated with Jurassic magmatic pulses.
DOI: 10.6084/m9.figshare.7068305
title: Virtual Observatory Data (CHAMP and Swarm) version 0101

description: Virtual Observatory datasets based on CHAMP and Swarm magnetospheric data. Produced by Chris Finlay and Magnus Hammer from Technical University of Denmark (DTU) and published with their permission.
DOI: 10.6084/m9.figshare.7068251
title: GWAS of typical vs limbic-predominant AD subtype

description: Summary statistics from GWAS of 498 unrelated Caucasian subjects from ADNI, described in Young, Scelsi et al. (manuscript in preparation). Binary phenotype was assignment to one of two major data-driven Alzheimer's disease subtypes: typical vs limbic-predominant.<br>Covariates: sex, age, years of education, number of APOE4 alleles, MRI scanner field strength, diagnosis, 2 principal components of CEU population substructure.<br><br>Fields are: CHR, SNP, BP, A1, TEST, NMISS, OR, SE, L95, U95, STAT, P.
DOI: 10.6084/m9.figshare.7068251.v1
title: GWAS of typical vs limbic-predominant AD subtype

description: Summary statistics from GWAS of 498 unrelated Caucasian subjects from ADNI, described in Young, Scelsi et al. (manuscript in preparation). Binary phenotype was assignment to one of two major data-driven Alzheimer's disease subtypes: typical vs limbic-predominant.<br>Covariates: sex, age, years of education, number of APOE4 alleles, MRI scanner field strength, diagnosis, 2 principal components of CEU population substructure.<br><br>Fields are: CHR, SNP, BP, A1, TEST, NMISS, OR, SE, L95, U95, STAT, P.
DOI: 10.6084/m9.figshare.7068212
title: Creating Science Gateways using Advanced GenApp Capabilities

description: GenApp is a framework for rapidly building and deploying graphical front ends for underlying computational modules. GenApp builds full featured applications on an extensi- ble variety of web and local GUI-based targets. GenApp works by reading a collection of definition files which guide the assembly of code fragments to output the application. In particular, GenApp can build fully functioning science gateways with a rich set of features. Science gateways built with GenApp can utilize OAuth2 for users to register and log on with XSEDE, Google or other credentials. Underlying jobs can run on a variety of resources including direct execution via ssh, elastically via OpenStack, and on queue-managed resources via Apache Airavata. GenApp is currently being successfully used as the generator of multiple production science gateways. This 90 minute tutorial will cover practical usage of advanced user interface methods.
DOI: 10.6084/m9.figshare.7068212.v2
title: Creating Science Gateways using Advanced GenApp Capabilities

description: GenApp is a framework for rapidly building and deploying graphical front ends for underlying computational modules. GenApp builds full featured applications on an extensi- ble variety of web and local GUI-based targets. GenApp works by reading a collection of definition files which guide the assembly of code fragments to output the application. In particular, GenApp can build fully functioning science gateways with a rich set of features. Science gateways built with GenApp can utilize OAuth2 for users to register and log on with XSEDE, Google or other credentials. Underlying jobs can run on a variety of resources including direct execution via ssh, elastically via OpenStack, and on queue-managed resources via Apache Airavata. GenApp is currently being successfully used as the generator of multiple production science gateways. This 90 minute tutorial will cover practical usage of advanced user interface methods.
DOI: 10.6084/m9.figshare.7068179
title: Clustering Download Events to Identify Classrooms

description: The Network for Computational Nanotechnology's (NCN) [1] nanoHUB site uses the HUBzero® platform [2] to offer a variety of content, simulation tools, and collaboration methods to an international community of students, teachers and professionals. Understanding and identifying educational usage of nanoHUB to form communities around nanotechnology education and improve education content is a long term objective of nanoHUB. While certain users log into nanoHUB, providing us with an identity with which to associate their usage, the majority of activity is from unidentified users who download content and come to the site from outside references such as search engine results. This paper describes a method to detect classroom usage from content download events with no additional information, identifying classroom usage by any user of nanoHUB material and providing insights into content usage.
DOI: 10.6084/m9.figshare.7068179.v2
title: Clustering Download Events to Identify Classrooms

description: The Network for Computational Nanotechnology's (NCN) [1] nanoHUB site uses the HUBzero® platform [2] to offer a variety of content, simulation tools, and collaboration methods to an international community of students, teachers and professionals. Understanding and identifying educational usage of nanoHUB to form communities around nanotechnology education and improve education content is a long term objective of nanoHUB. While certain users log into nanoHUB, providing us with an identity with which to associate their usage, the majority of activity is from unidentified users who download content and come to the site from outside references such as search engine results. This paper describes a method to detect classroom usage from content download events with no additional information, identifying classroom usage by any user of nanoHUB material and providing insights into content usage.
DOI: 10.6084/m9.figshare.7068179.v1
title: Clustering Download Events to Identify Classrooms

description: The Network for Computational Nanotechnology's (NCN) [1] nanoHUB site uses the HUBzero® platform [2] to offer a variety of content, simulation tools, and collaboration methods to an international community of students, teachers and professionals. Understanding and identifying educational usage of nanoHUB to form communities around nanotechnology education and improve education content is a long term objective of nanoHUB. While certain users log into nanoHUB, providing us with an identity with which to associate their usage, the majority of activity is from unidentified users who download content and come to the site from outside references such as search engine results. This paper describes a method to detect classroom usage from content download events with no additional information, identifying classroom usage by any user of nanoHUB material and providing insights into content usage.
DOI: 10.6084/m9.figshare.7068164
title: Data from Bonobos voluntarily hand food to others but not toys or tools

description: A key feature of human prosociality is <i>direct transfers</i>, the most active form of sharing in which donors voluntarily hand over resources <i>in their possession</i>. Direct transfers buffer hunter-gatherers against foraging shortfalls. The emergence and elaboration of this behaviour thus likely played a key role in human evolution by promoting cooperative interdependence and ensuring that humans' growing energetic needs (e.g. for increasing brain size) were more reliably met. According to the <i>strong prosociality hypothesis</i>, among great apes only humans exhibit sufficiently strong prosocial motivations to directly transfer food. The <i>versatile prosociality hypothesis</i> suggests instead that while other apes may make transfers in constrained settings, only humans share flexibly across food and non-food contexts. In controlled experiments, chimpanzees typically transfer objects but not food, supporting both hypotheses. In this paper, we show in two experiments that bonobos directly transfer food but not non-food items. These findings show that, in some contexts, bonobos exhibit a human-like motivation for direct food transfer. However, humans share across a far wider range of contexts, lending support to the versatile prosociality hypothesis. Our species' unusual prosocial flexibility is likely built on a prosocial foundation we share through common descent with the other apes.
DOI: 10.6084/m9.figshare.7068164.v1
title: Data from Bonobos voluntarily hand food to others but not toys or tools

description: A key feature of human prosociality is <i>direct transfers</i>, the most active form of sharing in which donors voluntarily hand over resources <i>in their possession</i>. Direct transfers buffer hunter-gatherers against foraging shortfalls. The emergence and elaboration of this behaviour thus likely played a key role in human evolution by promoting cooperative interdependence and ensuring that humans' growing energetic needs (e.g. for increasing brain size) were more reliably met. According to the <i>strong prosociality hypothesis</i>, among great apes only humans exhibit sufficiently strong prosocial motivations to directly transfer food. The <i>versatile prosociality hypothesis</i> suggests instead that while other apes may make transfers in constrained settings, only humans share flexibly across food and non-food contexts. In controlled experiments, chimpanzees typically transfer objects but not food, supporting both hypotheses. In this paper, we show in two experiments that bonobos directly transfer food but not non-food items. These findings show that, in some contexts, bonobos exhibit a human-like motivation for direct food transfer. However, humans share across a far wider range of contexts, lending support to the versatile prosociality hypothesis. Our species' unusual prosocial flexibility is likely built on a prosocial foundation we share through common descent with the other apes.
DOI: 10.6084/m9.figshare.7068074
title: Plotting Advancements to the GenApp Framework

description: GenApp, a Generalized Application generation framework, is a general tool for rapid deployment of applications to an extensible set of target languages. To produce fully functional science gateways and standalone graphical user interface (GUI) applications, GenApp weaves libraries of code fragments and user defined modules as directed by simple textual definition files. Apart from the scientific code to be deployed, these definition files are the only input from the user. This conceptual simplicity makes GenApp ideally suitable for scientists (physicists, chemists etc.) with little-to-no CS expertise who wish to deploy their scientific software on the web. Currently, GenApp is used to generate multiple web-based science gateways primarily in the Small Angle Scattering field. GenApp features are frequently added as required by use cases. We will briefly cover existing basic and advanced GenApp capabilities and focus on detailed discussion of the most recently integrated GenApp features including enhancements to the user interface such as enabling robust interactive 2D and 3D data plotting.
DOI: 10.6084/m9.figshare.7068074.v3
title: Plotting Advancements to the GenApp Framework

description: GenApp, a Generalized Application generation framework, is a general tool for rapid deployment of applications to an extensible set of target languages. To produce fully functional science gateways and standalone graphical user interface (GUI) applications, GenApp weaves libraries of code fragments and user defined modules as directed by simple textual definition files. Apart from the scientific code to be deployed, these definition files are the only input from the user. This conceptual simplicity makes GenApp ideally suitable for scientists (physicists, chemists etc.) with little-to-no CS expertise who wish to deploy their scientific software on the web. Currently, GenApp is used to generate multiple web-based science gateways primarily in the Small Angle Scattering field. GenApp features are frequently added as required by use cases. We will briefly cover existing basic and advanced GenApp capabilities and focus on detailed discussion of the most recently integrated GenApp features including enhancements to the user interface such as enabling robust interactive 2D and 3D data plotting.
DOI: 10.6084/m9.figshare.7067960
title: Motion tracking coordinate data of Hyptiotes release movement

description: X-Y coordinate data of Hyptiotes through its release movement.