cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4229300.v1
title: PLOSone Article: Towards Assessing the Human Trajectory Planning Horizon

description: The data provided here is supplementary material to a Journal Article under Review with PLOSone: <br>"Towards Assessing the Human Trajectory Planning Horizon"<br><br>The data was collected from 41 subjects that were using the "Desktop Kinesthetic Feedback Device" (DeKiFeD).<br>Subjects were acting on the DeKiFeD with one arm and were supposed to move a block shaped cursor through a virtual environment.<br>The environment changed randomly based on 10 levels with obstacles entering the field blocking the direct path to the goal.<br>Each higher level raised the complexity, meaning that more moving obstacles had to be avoided.<br>During the experiment the position, velocity and gaze data of each subject was recorded.<br>This data is provided here.
DOI: 10.6084/m9.figshare.4229297.v1
title: Five metal manuscript

description: Code, intermediate data, and results for: <br>Yao, Sen, et al. "A less‐biased analysis of metalloproteins reveals novel zinc coordination geometries." <i>Proteins: Structure, Function, and Bioinformatics,</i> 2017
DOI: 10.6084/m9.figshare.4225697
title: Statistics source data

description: Data used for the bar charts in Fig. 3B, 3C and S1A
DOI: 10.6084/m9.figshare.4225694
title: Movies (LocaTOR2 recruitment)

description: Tiff files with the time-lapse microscopy images of LocaTOR2 recruitment to the various membrane compartments.<br>For details, see manuscript
DOI: 10.6084/m9.figshare.4225697.v1
title: Statistics source data

description: Data used for the bar charts in Fig. 3B, 3C and S1A
DOI: 10.6084/m9.figshare.4225688
title: Sigure S3C - LE

description: SIM image reconstruction and log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-tagged Rab7.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 1000..10000 (Rab7); 1000..10000 (mSin1).
DOI: 10.6084/m9.figshare.4225694.v1
title: Movies (LocaTOR2 recruitment)

description: Tiff files with the time-lapse microscopy images of LocaTOR2 recruitment to the various membrane compartments.<br>For details, see manuscript
DOI: 10.6084/m9.figshare.4225685
title: Figure S3C - mito

description: SIM image reconstruction and registration log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-BclX<sub>L</sub><sup>C33</sup>.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 50..10000 (BclXL); 200..7000 (mSin1).
DOI: 10.6084/m9.figshare.4225682
title: Figure S3C - PM

description: SIM image reconstruction and registration log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-KRas4B<sup>C30</sup>.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 50..7000 (PM); 1000..5000 (mSin1).
DOI: 10.6084/m9.figshare.4225682.v1
title: Figure S3C - PM

description: SIM image reconstruction and registration log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-KRas4B<sup>C30</sup>.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 50..7000 (PM); 1000..5000 (mSin1).
DOI: 10.6084/m9.figshare.4225685.v1
title: Figure S3C - mito

description: SIM image reconstruction and registration log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-BclX<sub>L</sub><sup>C33</sup>.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 50..10000 (BclXL); 200..7000 (mSin1).
DOI: 10.6084/m9.figshare.4225679
title: Figure S3C - ER

description: SIM image reconstruction and registration log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-tagged calnexin.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 500..3000 (calnexin); 500..5000 (mSin1).
DOI: 10.6084/m9.figshare.4225679.v1
title: Figure S3C - ER

description: SIM image reconstruction and registration log files and overlay image for mSin1.2-GFP (enhanced by Atto488-conjugated anti-GFP scAb) and mCherry-tagged calnexin.<br>The reconstructed SIM image file was split into 2 fluorescence channels and the contrast was adjusted across the entire image using ImageJ (Fiji built). No non-linear adjustments were made. Contrast settings: 500..3000 (calnexin); 500..5000 (mSin1).
DOI: 10.6084/m9.figshare.4225643
title: Complex versus Simple Models: ion-channel cardiac toxicity prediction

description: Presentation given at Oxford meeting which was entitled: Is there a case for model reduction
DOI: 10.6084/m9.figshare.4225643.v2
title: Complex versus Simple Models: ion-channel cardiac toxicity prediction

description: Presentation given at Oxford meeting which was entitled: Is there a case for model reduction
DOI: 10.6084/m9.figshare.4225493.v2
title: Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression

description: We propose an algorithm, semismooth Newton coordinate descent (SNCD), for the elastic-net penalized Huber loss regression and quantile regression in high dimensional settings. Unlike existing coordinate descent type algorithms, the SNCD updates a regression coefficient and its corresponding subgradient simultaneously in each iteration. It combines the strengths of the coordinate descent and the semismooth Newton algorithm, and effectively solves the computational challenges posed by dimensionality and nonsmoothness. We establish the convergence properties of the algorithm. In addition, we present an adaptive version of the “strong rule” for screening predictors to gain extra efficiency. Through numerical experiments, we demonstrate that the proposed algorithm is very efficient and scalable to ultrahigh dimensions. We illustrate the application via a real data example. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.4225493.v1
title: Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression

description: We propose an algorithm, semismooth Newton coordinate descent (SNCD), for the elastic-net penalized Huber loss regression and quantile regression in high dimensional settings. Unlike existing coordinate descent type algorithms, the SNCD updates a regression coefficient and its corresponding subgradient simultaneously in each iteration. It combines the strengths of the coordinate descent and the semismooth Newton algorithm, and effectively solves the computational challenges posed by dimensionality and nonsmoothness. We establish the convergence properties of the algorithm. In addition, we present an adaptive version of the “strong rule” for screening predictors to gain extra efficiency. Through numerical experiments, we demonstrate that the proposed algorithm is very efficient and scalable to ultrahigh dimensions. We illustrate the application via a real data example. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.4225460
title: Formal Hypothesis Tests for Additive Structure in Random Forests

description: While statistical learning methods have proved powerful tools for predictive modeling, the black-box nature of the models they produce can severely limit their interpretability and the ability to conduct formal inference. However, the natural structure of ensemble learners like bagged trees and random forests has been shown to admit desirable asymptotic properties when base learners are built with proper subsamples. In this work, we demonstrate that by defining an appropriate grid structure on the covariate space, we may carry out formal hypothesis tests for both variable importance and underlying additive model structure. To our knowledge, these tests represent the first statistical tools for investigating the underlying regression structure in a context such as random forests. We develop notions of total and partial additivity and further demonstrate that testing can be carried out at no additional computational cost by estimating the variance within the process of constructing the ensemble. Furthermore, we propose a novel extension of these testing procedures using random projections to allow for computationally efficient testing procedures that retain high power even when the grid size is much larger than that of the training set.
DOI: 10.6084/m9.figshare.4225460.v1
title: Formal Hypothesis Tests for Additive Structure in Random Forests

description: While statistical learning methods have proved powerful tools for predictive modeling, the black-box nature of the models they produce can severely limit their interpretability and the ability to conduct formal inference. However, the natural structure of ensemble learners like bagged trees and random forests has been shown to admit desirable asymptotic properties when base learners are built with proper subsamples. In this work, we demonstrate that by defining an appropriate grid structure on the covariate space, we may carry out formal hypothesis tests for both variable importance and underlying additive model structure. To our knowledge, these tests represent the first statistical tools for investigating the underlying regression structure in a context such as random forests. We develop notions of total and partial additivity and further demonstrate that testing can be carried out at no additional computational cost by estimating the variance within the process of constructing the ensemble. Furthermore, we propose a novel extension of these testing procedures using random projections to allow for computationally efficient testing procedures that retain high power even when the grid size is much larger than that of the training set.
DOI: 10.6084/m9.figshare.4225427
title: Conserved small mRNA with an unique, extended Shine-Dalgarno sequence

description: Up to now, very small protein-coding genes have remained unrecognized in sequenced genomes. We identified an mRNA of 165 nucleotides (nt), which is conserved in <i>Bradyrhizobiaceae</i> and encodes a polypeptide with 14 amino acid residues (aa). The small mRNA harboring a unique Shine-Dalgarno sequence (SD) with a length of 17 nt was localized predominantly in the ribosome-containing P100 fraction of <i>Bradyrhizobium japonicum</i> USDA 110. Strong interaction between the mRNA and 30S ribosomal subunits was demonstrated by their co-sedimentation in sucrose density gradient. Using translational fusions with <i>egfp</i>, we detected weak translation and found that it is impeded by both the extended SD and the GTG start codon (instead of ATG). Biophysical characterization (CD- and NMR-spectroscopy) showed that synthesized polypeptide remained unstructured in physiological puffer. Replacement of the start codon by a stop codon increased the stability of the transcript, strongly suggesting additional posttranscriptional regulation at the ribosome. Therefore, the small gene was named <i>rreB</i> (ribosome-regulated expression in <i>Bradyrhizobiaceae</i>). Assuming that the unique ribosome binding site (RBS) is a hallmark of <i>rreB</i> homologs or similarly regulated genes, we looked for similar putative RBS in bacterial genomes and detected regions with at least 16 nt complementarity to the 3′-end of 16S rRNA upstream of sORFs in <i>Caulobacterales, Rhizobiales, Rhodobacterales</i> and <i>Rhodospirillales</i>. In the <i>Rhodobacter/Roseobacter</i> lineage of Alphaproteobacteria the corresponding gene (<i>rreR</i>) is conserved and encodes an 18 aa protein. This shows how specific RBS features can be used to identify new genes with presumably similar control of expression at the RNA level.
DOI: 10.6084/m9.figshare.4225427.v1
title: Conserved small mRNA with an unique, extended Shine-Dalgarno sequence

description: Up to now, very small protein-coding genes have remained unrecognized in sequenced genomes. We identified an mRNA of 165 nucleotides (nt), which is conserved in <i>Bradyrhizobiaceae</i> and encodes a polypeptide with 14 amino acid residues (aa). The small mRNA harboring a unique Shine-Dalgarno sequence (SD) with a length of 17 nt was localized predominantly in the ribosome-containing P100 fraction of <i>Bradyrhizobium japonicum</i> USDA 110. Strong interaction between the mRNA and 30S ribosomal subunits was demonstrated by their co-sedimentation in sucrose density gradient. Using translational fusions with <i>egfp</i>, we detected weak translation and found that it is impeded by both the extended SD and the GTG start codon (instead of ATG). Biophysical characterization (CD- and NMR-spectroscopy) showed that synthesized polypeptide remained unstructured in physiological puffer. Replacement of the start codon by a stop codon increased the stability of the transcript, strongly suggesting additional posttranscriptional regulation at the ribosome. Therefore, the small gene was named <i>rreB</i> (ribosome-regulated expression in <i>Bradyrhizobiaceae</i>). Assuming that the unique ribosome binding site (RBS) is a hallmark of <i>rreB</i> homologs or similarly regulated genes, we looked for similar putative RBS in bacterial genomes and detected regions with at least 16 nt complementarity to the 3′-end of 16S rRNA upstream of sORFs in <i>Caulobacterales, Rhizobiales, Rhodobacterales</i> and <i>Rhodospirillales</i>. In the <i>Rhodobacter/Roseobacter</i> lineage of Alphaproteobacteria the corresponding gene (<i>rreR</i>) is conserved and encodes an 18 aa protein. This shows how specific RBS features can be used to identify new genes with presumably similar control of expression at the RNA level.
DOI: 10.6084/m9.figshare.4225334
title: Data files for article: Caribbean Spiny Lobster Fishery is Underpinned by Trophic Subsidies from Chemosynthetic Primary Production

description: These data accompany the publication:Higgs ND, Newton J and Attrill MJ (2016) Caribbean Spiny Lobster Fishery is Underpinned by Trophic Subsidies from Chemosynthetic Primary Production. Current Biology, <br>These data allow the replication of analyses reported in the publication and are provided in tabulated form as individual .csv files for interrogation and as a folder of data files and script formatted for use in the SIMMR package in the R software environment.<br>Sampling Date (ISO standard): 2014-08Sampling Location (Marine Regions): Great Bahama Bank<br>File “Lobster_isotope_values.csv” contains bulk stable isotope values of Nitrogen, Carbon and Sulphur for muscle tissue samples taken from individual lobsters (Panulirus argus) collected in a numbered sampling location.<br>File “Prey_group_isotope_values” contains mean and standard deviations of the bulk stable isotope values of Nitrogen, Carbon and Sulphur for groups of samples of lobster prey species. The mean concentration of each element in the samples is also included for each group. This data is reported in Table S2 in the publication. Group names and full details of species included in each group are detailed in the publication.<br>File “Trophic_enrichment_factors” contain values of corrections applied to prey isotope values in the stable isotope mixing model, to account for isotopic enrichment when prey are assimilated into the lobster tissue.<br>The zip file “R Data Files” contains a folder with an R Script file and associated data files for running the stable isotope mixing model (SIMMR) as described in the publication<br><br><br>
DOI: 10.6084/m9.figshare.4224353
title: DMPTuuli user survey raw data 2016

description: This is the anonymized raw data from the DMPTuuli user survey in October, 2016, organized by the Tuuli Project, University of Helsinki. The survey was sent to registered DMPTuuli users. The aim of the survey was to gather feedback, comments and suggestions from users for the further development of the tool in 2016 and 2017. DMPTuuli is a tool for researchers and research organizations for creating data management plans (DMPs) implemented for pilot phase use in 2016. It is produced by the national Tuuli Project. the aim of DMPTuuli is to assist in data management planning at all stages of research. DMPTuuli includes generic DMP guidance and additional guidance provided by funders, organizations, and disciplines.DMPTuuli is based on the DMPonline code, developed by the Digital Curation Centre in the UK.<br>Please note that the variables used are listed and explained under the data on the first interleaf of the dataset.
DOI: 10.6084/m9.figshare.4224350
title: SI B3LYP-gaussianoutputs for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)"

description: Gaussian output files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224353.v1
title: DMPTuuli_user_ survey_raw_data_2016-11-11.xlsx

description: This is the anonymized raw data from the DMPTuuli user survey in October, 2016, organized by the Tuuli Project, University of Helsinki. The user survey was sent to staff in all the research organizations in Finland which have adopted the data management planning tool DMPTuuli in 2016. The aim of the survey was to gather feedback, comments and suggestions from DMPTuuli users for the further development of the tool in 2016 and 2017. DMPTuuli is a tool for researchers and research organizations for creating data management plans (DMPs) implemented for pilot phase use in 2016. It is produced by the national Tuuli Project. the aim of DMPTuuli is to assist in data management planning at all stages of research. DMPTuuli includes generic DMP guidance and additional guidance provided by funders, organizations, and disciplines.DMPTuuli is based on the DMPonline code, developed by the Digital Curation Centre in the UK.<br>Please note that the variables used are listed and explained under the data on the first interleaf of the dataset.
DOI: 10.6084/m9.figshare.4224353.v2
title: DMPTuuli user survey raw data

description: This is the anonymized raw data from the DMPTuuli user survey in October, 2016, organized by the Tuuli Project, University of Helsinki. The survey was sent to registered DMPTuuli users. The aim of the survey was to gather feedback, comments and suggestions from users for the further development of the tool in 2016 and 2017. DMPTuuli is a tool for researchers and research organizations for creating data management plans (DMPs) implemented for pilot phase use in 2016. It is produced by the national Tuuli Project. the aim of DMPTuuli is to assist in data management planning at all stages of research. DMPTuuli includes generic DMP guidance and additional guidance provided by funders, organizations, and disciplines.DMPTuuli is based on the DMPonline code, developed by the Digital Curation Centre in the UK.<br>Please note that the variables used are listed and explained under the data on the first interleaf of the dataset.
DOI: 10.6084/m9.figshare.4224353.v3
title: DMPTuuli user survey raw data 2016

description: This is the anonymized raw data from the DMPTuuli user survey in October, 2016, organized by the Tuuli Project, University of Helsinki. The survey was sent to registered DMPTuuli users. The aim of the survey was to gather feedback, comments and suggestions from users for the further development of the tool in 2016 and 2017. DMPTuuli is a tool for researchers and research organizations for creating data management plans (DMPs) implemented for pilot phase use in 2016. It is produced by the national Tuuli Project. the aim of DMPTuuli is to assist in data management planning at all stages of research. DMPTuuli includes generic DMP guidance and additional guidance provided by funders, organizations, and disciplines.DMPTuuli is based on the DMPonline code, developed by the Digital Curation Centre in the UK.<br>Please note that the variables used are listed and explained under the data on the first interleaf of the dataset.
DOI: 10.6084/m9.figshare.4224347
title: SI B3LYP-xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)"

description: B3LYP xyz structure files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"<br>
DOI: 10.6084/m9.figshare.4224350.v2
title: SI B3LYP-gaussianoutputs for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)"

description: Gaussian output files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224350.v1
title: B3LYP-gaussianoutputs.zip

description: Gaussian output files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224344
title: SI BMK-guassianoutputs for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)"

description: Gaussian output files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224347.v2
title: SI B3LYP-xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)"

description: B3LYP xyz structure files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"<br>
DOI: 10.6084/m9.figshare.4224347.v1
title: B3LYP-xyz.zip

description: B3LYP xyz structure files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"<br>
DOI: 10.6084/m9.figshare.4224341
title: SI BMK-xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)

description: BMK xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224344.v1
title: BMK-guassianoutputs.zip

description: Gaussian output files for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224341.v2
title: SI BMK-xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE)

description: BMK xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"
DOI: 10.6084/m9.figshare.4224341.v1
title: BMK-xyz.zip

description: BMK xyz structures for "Radical Reaction Control in the AdoMet Radical Enzyme CDG Synthase (QueE): Consolidate, Destabilize, Accelerate"