cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive3448.20170425.1
title: Cystobacter violaceus (ex Kühlwein and Gallwitz 1958) Reichenbach 2007

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.6084/m9.figshare.17086862
title: Data on dissolved organic matter, sea ice and environment in surface water of Antarctic Ocean

description: On behalf of my coauthors, I am pleased to submit a manuscript entitled “Sea ice melting is a factor driving dissolved organic matter change in surface waters of Antarctic Ocean close to the Prydz Bay”. The South Ocean (or Antarctic Ocean) is the largest sink for atmospheric CO2, and is sensitive to current global warming, characterized by rapid changes in sea ice. Here we measured the concentration and composition of dissolved organic matter (DOM) in surface waters from Antarctic Ocean close to the Prydz Bay, and tried to understand their changes in relation to sea ice melting processes. Our data based on optical spectra and high-resolution mass spectra revealed distinct differences in concentration and composition of DOM during sea ice melting and post-melting periods. Overall, with continuous sea ice melting, the underlying surface water had higher DOM concentration, lower chromophoric DOM concentration, and more protein-like labile components that were attributed to significant contributions of sea ice algae DOM, whereas the water during post-sea ice melting period had lower DOM concentration, higher chromophoric DOM concentration and more humid-like refractory components that were derived from microbial transformation of labile DOM. <br>
DOI: 10.26180/17086868.v1
title: Collocated soundings

description: Collocated soundings
DOI: 10.26180/17086868
title: Collocated soundings

description: Collocated soundings
DOI: 10.6084/m9.figshare.17086873
title: Post-transcriptional regulation of <i>ATG1</i> is a critical node that modulates autophagy during distinct nutrient stresses

description: Macroautophagy/autophagy is a highly conserved nutrient-recycling pathway that eukaryotes utilize to combat diverse stresses including nutrient depletion. Dysregulation of autophagy disrupts cellular homeostasis leading to starvation susceptibility in yeast and disease development in humans. In yeast, the robust autophagy response to starvation is controlled by the upregulation of <i>ATG</i> genes, via regulatory processes involving multiple levels of gene expression. Despite the identification of several regulators through genetic studies, the predominant mechanism of regulation modulating the autophagy response to subtle differences in nutrient status remains undefined. Here, we report the unexpected finding that subtle changes in nutrient availability can cause large differences in autophagy flux, governed by hitherto unknown post-transcriptional regulatory mechanisms affecting the expression of the key autophagyinducing kinase Atg1 (ULK1/ULK2 in mammals). We have identified two novel post-transcriptional regulators of <i>ATG1</i> expression, the kinase Rad53 and the RNA-binding protein Ded1 (DDX3 in mammals). Furthermore, we show that DDX3 regulates <i>ULK1</i> expression post-transcriptionally, establishing mechanistic conservation and highlighting the power of yeast biology in uncovering regulatory mechanisms that can inform therapeutic approaches.
DOI: 10.6084/m9.figshare.17086873.v1
title: Post-transcriptional regulation of <i>ATG1</i> is a critical node that modulates autophagy during distinct nutrient stresses

description: Macroautophagy/autophagy is a highly conserved nutrient-recycling pathway that eukaryotes utilize to combat diverse stresses including nutrient depletion. Dysregulation of autophagy disrupts cellular homeostasis leading to starvation susceptibility in yeast and disease development in humans. In yeast, the robust autophagy response to starvation is controlled by the upregulation of <i>ATG</i> genes, via regulatory processes involving multiple levels of gene expression. Despite the identification of several regulators through genetic studies, the predominant mechanism of regulation modulating the autophagy response to subtle differences in nutrient status remains undefined. Here, we report the unexpected finding that subtle changes in nutrient availability can cause large differences in autophagy flux, governed by hitherto unknown post-transcriptional regulatory mechanisms affecting the expression of the key autophagyinducing kinase Atg1 (ULK1/ULK2 in mammals). We have identified two novel post-transcriptional regulators of <i>ATG1</i> expression, the kinase Rad53 and the RNA-binding protein Ded1 (DDX3 in mammals). Furthermore, we show that DDX3 regulates <i>ULK1</i> expression post-transcriptionally, establishing mechanistic conservation and highlighting the power of yeast biology in uncovering regulatory mechanisms that can inform therapeutic approaches.
DOI: 10.6084/m9.figshare.17086877
title: Dependent Modeling of Temporal Sequences of Random Partitions

description: We consider modeling a dependent sequence of random partitions. It is well known in Bayesian nonparametrics that a random measure of discrete type induces a distribution over random partitions. The community has therefore assumed that the best approach to obtain a dependent sequence of random partitions is through modeling dependent random measures. We argue that this approach is problematic and show that the random partition model induced by dependent Bayesian nonparametric priors exhibits counter-intuitive dependence among partitions even though the dependence for the sequence of random probability measures is intuitive. Because of this, we suggest directly modeling the sequence of random partitions when clustering is of principal interest. To this end, we develop a class of dependent random partition models that explicitly models dependence in a sequence of partitions. We derive conditional and marginal properties of the joint partition model and devise computational strategies when employing the method in Bayesian modeling. In the case of temporal dependence, we demonstrate through simulation how the methodology produces partitions that evolve gently and naturally over time. We further illustrate the utility of the method by applying it to an environmental dataset that exhibits spatio-temporal dependence. Supplemental files for this article are available online.
DOI: 10.6084/m9.figshare.17086877.v1
title: Dependent Modeling of Temporal Sequences of Random Partitions

description: We consider modeling a dependent sequence of random partitions. It is well known in Bayesian nonparametrics that a random measure of discrete type induces a distribution over random partitions. The community has therefore assumed that the best approach to obtain a dependent sequence of random partitions is through modeling dependent random measures. We argue that this approach is problematic and show that the random partition model induced by dependent Bayesian nonparametric priors exhibits counter-intuitive dependence among partitions even though the dependence for the sequence of random probability measures is intuitive. Because of this, we suggest directly modeling the sequence of random partitions when clustering is of principal interest. To this end, we develop a class of dependent random partition models that explicitly models dependence in a sequence of partitions. We derive conditional and marginal properties of the joint partition model and devise computational strategies when employing the method in Bayesian modeling. In the case of temporal dependence, we demonstrate through simulation how the methodology produces partitions that evolve gently and naturally over time. We further illustrate the utility of the method by applying it to an environmental dataset that exhibits spatio-temporal dependence. Supplemental files for this article are available online.
DOI: 10.15468/w972tw
title: Primulina silaniae sp. nov. (Gesneriaceae) from the limestone area of Guizhou Province, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zhang, Jin-Quan, Huang, Hong, Li, Mei-Jun, Huang, Mei, Li, Quan-Yuan, Zhou, Yu-Lu, Chen, Yi, Wen, Fang, Bai, Xin-Xiang (2021): Primulina silaniae sp. nov. (Gesneriaceae) from the limestone area of Guizhou Province, China. PhytoKeys 185: 123-130, DOI: http://dx.doi.org/10.3897/phytokeys.185.72099, URL: http://dx.doi.org/10.3897/phytokeys.185.72099
DOI: 10.6084/m9.figshare.17086967
title: Additional file 3 of Behaviour, temperature and terrain slope impact estimates of energy expenditure using oxygen and dynamic body acceleration

description: Additional file 3. Respirometry measurements including individual body weight, temperature, DBA, walking speed and measurement type.
DOI: 10.6084/m9.figshare.17086967.v1
title: Additional file 3 of Behaviour, temperature and terrain slope impact estimates of energy expenditure using oxygen and dynamic body acceleration

description: Additional file 3. Respirometry measurements including individual body weight, temperature, DBA, walking speed and measurement type.
DOI: 10.6084/m9.figshare.16859404.v1
title: Data of 3D Object Detection Combining Semantic and Geometric Features from Point Clouds

description: Data of 3D Object Detection Combining Semantic and Geometric Features from Point Clouds
DOI: 10.14457/cu.the.2013.1921
title: Minority oversampling framework for class imbalance problem
DOI: 10.14457/cu.the.2013.1922
title: Influential Factors on Intention to Use Internet Banking Among Young Adult Customers in Vietnam
DOI: 10.14457/cu.the.2013.1923
title: Influential Factors on Intention to Use Internet Banking Among Young Adult Customers in Vietnam
DOI: 10.5281/zenodo.5731017
title: TCGA Data

description: TCGA data by disease type
DOI: 10.5281/zenodo.5731016
title: TCGA Data

description: TCGA data by disease type
DOI: 10.5517/ccdc.csd.cc22b7g4
title: CCDC 1916465: Experimental Crystal Structure Determination

description: Related Article: Thomas Wildsmith, James D. Parish, Ibbi Y. Ahmet, Kieran C. Molloy, Michael S. Hill, Andrew L. Johnson|2021|Inorg.Chem.|60|17083|doi:10.1021/acs.inorgchem.1c02317
DOI: 10.5517/ccdc.csd.cc22b7h5
title: CCDC 1916466: Experimental Crystal Structure Determination

description: Related Article: Thomas Wildsmith, James D. Parish, Ibbi Y. Ahmet, Kieran C. Molloy, Michael S. Hill, Andrew L. Johnson|2021|Inorg.Chem.|60|17083|doi:10.1021/acs.inorgchem.1c02317
DOI: 10.5517/ccdc.csd.cc22b7j6
title: CCDC 1916467: Experimental Crystal Structure Determination

description: Related Article: Thomas Wildsmith, James D. Parish, Ibbi Y. Ahmet, Kieran C. Molloy, Michael S. Hill, Andrew L. Johnson|2021|Inorg.Chem.|60|17083|doi:10.1021/acs.inorgchem.1c02317
DOI: 10.5517/ccdc.csd.cc277qw3
title: CCDC 2063015: Experimental Crystal Structure Determination

description: Related Article: Deepika G. Karmalkar, Mi Sook Seo, Yong-Min Lee, Youngsuk Kim, Eunsung Lee, Ritimukta Sarangi, Shunichi Fukuzumi, Wonwoo Nam|2021|Inorg.Chem.|60|16996|doi:10.1021/acs.inorgchem.1c02119
DOI: 10.5517/ccdc.csd.cc27g5tq
title: CCDC 2069213: Experimental Crystal Structure Determination

description: Related Article: Yi-Gang Weng, Zhou-Hong Ren, Zhi-Ruo Zhang, Jie Shao, Qin-Yu Zhu, Jie Dai|2021|Inorg.Chem.|60|17074|doi:10.1021/acs.inorgchem.1c02304
DOI: 10.5517/ccdc.csd.cc2826rb
title: CCDC 2087501: Experimental Crystal Structure Determination

description: Related Article: Jianzhuang Jiang, Baoqiu Yu, Shubo Geng, Hailong Wang, Wei Zhou, Zhenjie Zhang, Banglin Chen|2021|Angew.Chem.,Int.Ed.|60|25942|doi:10.1002/anie.202110057
DOI: 10.5517/ccdc.csd.cc2826sc
title: CCDC 2087502: Experimental Crystal Structure Determination

description: Related Article: Jianzhuang Jiang, Baoqiu Yu, Shubo Geng, Hailong Wang, Wei Zhou, Zhenjie Zhang, Banglin Chen|2021|Angew.Chem.,Int.Ed.|60|25942|doi:10.1002/anie.202110057
DOI: 10.5517/ccdc.csd.cc2826td
title: CCDC 2087503: Experimental Crystal Structure Determination

description: Related Article: Jianzhuang Jiang, Baoqiu Yu, Shubo Geng, Hailong Wang, Wei Zhou, Zhenjie Zhang, Banglin Chen|2021|Angew.Chem.,Int.Ed.|60|25942|doi:10.1002/anie.202110057
DOI: 10.5281/zenodo.5731229
title: Dataset#1 and Dataset#2 for Making drawings speak through mathematical metrics

description: Dataset 1 and Dataset 2 for the paper Making drawings speak through mathematical metrics Figurative drawing is a skill that takes time to learn, and evolves during different childhood phases that begin with scribbling and end with representational drawing. Between these phases, it is difficult to assess when and how children demonstrate intentions and representativeness in their drawings. The marks produced are increasingly goal-oriented and efficient as the child’s skills progress from scribbles to figurative drawings. Pre-figurative activities provide an opportunity to focus on drawing processes. We applied fourteen metrics to two different datasets (N=65 and N=345) to better understand the intentional and representational processes behind drawing, and combined these metrics using principal component analysis (PCA) in different biologically significant dimensions. Three dimensions were identified: efficiency based on spatial metrics, diversity with colour metrics, and temporal sequentiality. The metrics at play in each dimension are similar for both datasets, and PCA explains 77% of the variance in both datasets. These analyses differentiate scribbles by children from those drawn by adults. The three dimensions highlighted by this study provide a better understanding of the emergence of intentions and representativeness in drawings. We have already discussed the perspectives of such findings in Comparative Psychology and Evolutionary Anthropology.
DOI: 10.5281/zenodo.5387519
title: Dataset#1 and Dataset#2 for Making drawings speak through mathematical metrics

description: Dataset 1 and Dataset 2 for the paper Making drawings speak through mathematical metrics Figurative drawing is a skill that takes time to learn, and evolves during different childhood phases that begin with scribbling and end with representational drawing. Between these phases, it is difficult to assess when and how children demonstrate intentions and representativeness in their drawings. The marks produced are increasingly goal-oriented and efficient as the child’s skills progress from scribbles to figurative drawings. Pre-figurative activities provide an opportunity to focus on drawing processes. We applied fourteen metrics to two different datasets (N=65 and N=345) to better understand the intentional and representational processes behind drawing, and combined these metrics using principal component analysis (PCA) in different biologically significant dimensions. Three dimensions were identified: efficiency based on spatial metrics, diversity with colour metrics, and temporal sequentiality. The metrics at play in each dimension are similar for both datasets, and PCA explains 77% of the variance in both datasets. These analyses differentiate scribbles by children from those drawn by adults. The three dimensions highlighted by this study provide a better understanding of the emergence of intentions and representativeness in drawings. We have already discussed the perspectives of such findings in Comparative Psychology and Evolutionary Anthropology.
DOI: 10.5281/zenodo.5731233
title: Supplementary Tables for Trp Exp

description: Supplemental Table S1, S2, S3, S4, S5, S6
DOI: 10.5281/zenodo.5731232
title: Supplementary Tables for Trp Exp

description: Supplemental Table S1, S2, S3, S4, S5, S6
DOI: 10.15151/esrf-es-536299724
title: Austrian Crystallographic Diffraction Consortium

description: This proposed Austrian Crystallographic Diffraction Consortium (ACDC) BAG is to support various macromolecular structural biology groups across Austria (totally 15 research groups at 8 institutions in 5 cities). We employ mainly the technique of X-ray crystallography to characterize macromolecular biological complexes. Approval of this BAG will be absolutely essential for researchers in all these groups to carry out their structural studies on various health-related subjects, which are targeted at characterizing large molecular assemblies or proteins currently under-represented in the PDB, including membrane proteins. Corresponding high-resolution diffraction data are only obtainable through the use of synchrotron radiation sources. Thus regular synchrotron access is highly desirable to maintain a competitive advantage in our individual research fields.
DOI: 10.15151/esrf-es-541146591
title: IBS BAG

description: The IBS BAG currently includes 24 IBS teams and 4 external groups from CERMAV and iRTSV/CEA (Grenoble), CEA-Cadarache (St Paul lez Durance) and IRBA (Brétigny-sur-Orge). We study structure-function relationships of proteins emphasizing in human health, biotechnology and methodology. Most of the projects can be grouped in different topics as follows: host-pathogen interaction, immunology, new drug targets, fundamental cellular mechanisms, membrane proteins, intrinsically disordered proteins, biotechnological applications and methodology. Some of these projects use integrative approaches (X-ray crystallography, SAXS, NMR (and cryo-EM), together with other biophysical studies) with the aim to fully understand the complexity of the biological macromolecular systems on study. Some other teams are dedicated to serial crystallography and its developments, for which the new ESRF-EBS might be the perfect tool.
DOI: 10.15151/esrf-es-541456480
title: Stockholm BAG

description: The Stockholm BAG is a constellation of seven research groups, whose PIs are affiliated to Karolinska Institutet (Adnane Achour, Jesper Haeggström, Luca Jovine and Robert Schnell) or Stockholm University (David Drew, Martin Hogböm, Pål Stenmark). Together, these groups are responsible for the large majority of the macromolecular crystallography research taking place in the Swedish capital. The scientific interests of the BAG encompass a broad variety of topics that include structural immunology, bacterial adhesion and toxicity, membrane proteins involved in inflammation and transport, fertilization, and enzymatic catalysis relevant to antibiotic production, green chemistry and cancer.
DOI: 10.15151/esrf-es-542597936
title: Structural Biology of Macromolecules and Macromolecular complexes from India

description: Structural biology research groups located in India constitute the INDIA-BAG and will utilize MX, SAXS and CryoEM to study different biological macromolecules. Together, these groups address multiple pathways in animals, plants, bacteria and fungi. These studies will provide fundamental mechanistic insight regarding different processes critical for the survival and propagation of the relevant organism. Many groups in the BAG study proteins from pathogens to identify novel intervention points that can be the targeted with small molecule inhibitors to inhibit the growth of the corresponding infectious agents. There are more than 50 groups that are part of this BAG and the allocated beamtime will be available for over 500 young researchers. A brief description of all the research groups is provided in the global summary and a summary of the research contributions involving data collected at ESRF is provided in the last BAG report.
DOI: 10.15151/esrf-es-578179140
title: Sound velocities in the Fe-Si-C alloys at extreme conditions: Si and C in the core

description: The experiment aims to investigate the elastic and thermodynamic properties of Fe-Si-C alloy at pressures above 200 GPa and temperatures of thousands of degrees by means of the Nuclear Inelastic Scattering (NIS) technique and powder X-ray diffraction. NIS is a powerful tool for the study of lattice dynamics that provides a full thermodynamic sample characterization. The measured phonon density of states provides the Debye phonon average velocity (VD), which together with density and bulk modulus, determined by complementary X-ray diffraction measurements, are the necessary parameters for calculating the compressional velocity (VP) and shear velocity (VS) of the material. Our measurements will allow refining the amount of Si and C required to explain the observed seismic profile of the Earth’s core.
DOI: 10.6084/m9.figshare.17032088.v2
title: Geogenic controls on the high levels of uranium in alluvial aquifers of the Ganga Basin

description: The data set presented here include hydrochemistry and trace element analysis results of shallow groundwater and surface water collected from central part of the Indo-Gangetic Basin located in the industrial region of Kanpur and adjoining rural region. The data set is used to discern the dominant spatial variability, possible sources and factors controlling the occurrence, distribution and sources of radiotoxic element uranium in the densely populated region of central IGP.
DOI: 10.5517/ccdc.csd.cc2826vf
title: CCDC 2087504: Experimental Crystal Structure Determination

description: Related Article: Jianzhuang Jiang, Baoqiu Yu, Shubo Geng, Hailong Wang, Wei Zhou, Zhenjie Zhang, Banglin Chen|2021|Angew.Chem.,Int.Ed.|60|25942|doi:10.1002/anie.202110057
DOI: 10.5517/ccdc.csd.cc2826wg
title: CCDC 2087505: Experimental Crystal Structure Determination

description: Related Article: Jianzhuang Jiang, Baoqiu Yu, Shubo Geng, Hailong Wang, Wei Zhou, Zhenjie Zhang, Banglin Chen|2021|Angew.Chem.,Int.Ed.|60|25942|doi:10.1002/anie.202110057
DOI: 10.5517/ccdc.csd.cc2826xh
title: CCDC 2087506: Experimental Crystal Structure Determination

description: Related Article: Jianzhuang Jiang, Baoqiu Yu, Shubo Geng, Hailong Wang, Wei Zhou, Zhenjie Zhang, Banglin Chen|2021|Angew.Chem.,Int.Ed.|60|25942|doi:10.1002/anie.202110057
DOI: 10.5517/ccdc.csd.cc28hdpw
title: CCDC 2100178: Experimental Crystal Structure Determination

description: Related Article: Thomas Wildsmith, James D. Parish, Ibbi Y. Ahmet, Kieran C. Molloy, Michael S. Hill, Andrew L. Johnson|2021|Inorg.Chem.|60|17083|doi:10.1021/acs.inorgchem.1c02317
DOI: 10.5517/ccdc.csd.cc28mynj
title: CCDC 2104548: Experimental Crystal Structure Determination

description: Related Article: Daniel M. Beagan, Alyssa C. Cabelof, Robert Pepin, Maren Pink, Veronica Carta, Kenneth G. Caulton|2021|Inorg.Chem.|60|17241|doi:10.1021/acs.inorgchem.1c02591
DOI: 10.5517/ccdc.csd.cc28mypk
title: CCDC 2104549: Experimental Crystal Structure Determination

description: Related Article: Daniel M. Beagan, Alyssa C. Cabelof, Robert Pepin, Maren Pink, Veronica Carta, Kenneth G. Caulton|2021|Inorg.Chem.|60|17241|doi:10.1021/acs.inorgchem.1c02591
DOI: 10.5517/ccdc.csd.cc28mysn
title: CCDC 2104552: Experimental Crystal Structure Determination

description: Related Article: Daniel M. Beagan, Alyssa C. Cabelof, Robert Pepin, Maren Pink, Veronica Carta, Kenneth G. Caulton|2021|Inorg.Chem.|60|17241|doi:10.1021/acs.inorgchem.1c02591
DOI: 10.5517/ccdc.csd.cc27g5sp
title: CCDC 2069212: Experimental Crystal Structure Determination

description: Related Article: Yi-Gang Weng, Zhou-Hong Ren, Zhi-Ruo Zhang, Jie Shao, Qin-Yu Zhu, Jie Dai|2021|Inorg.Chem.|60|17074|doi:10.1021/acs.inorgchem.1c02304
DOI: 10.5517/ccdc.csd.cc28myql
title: CCDC 2104550: Experimental Crystal Structure Determination

description: Related Article: Daniel M. Beagan, Alyssa C. Cabelof, Robert Pepin, Maren Pink, Veronica Carta, Kenneth G. Caulton|2021|Inorg.Chem.|60|17241|doi:10.1021/acs.inorgchem.1c02591
DOI: 10.5517/ccdc.csd.cc28myrm
title: CCDC 2104551: Experimental Crystal Structure Determination

description: Related Article: Daniel M. Beagan, Alyssa C. Cabelof, Robert Pepin, Maren Pink, Veronica Carta, Kenneth G. Caulton|2021|Inorg.Chem.|60|17241|doi:10.1021/acs.inorgchem.1c02591