cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3179476.v20
title: example RDFORM

description: This is an example rdform for use with figmeta. This form allows organizational affiliations to be associated with authors on a dataset. Organizations are represented with GRID uri's
DOI: 10.6084/m9.figshare.3175639.v1
title: Using educational prescriptions to teach medical students evidence-based medicine

description: <b>Purpose</b>: To evaluate feasibility and impact of evidence-based medicine (EBM) educational prescriptions (EPs) in medical student clerkships. <b>Methods</b>: Students answered clinical questions during clerkships using EPs, which guide learners through the “four As” of EBM. Epidemiology fellows graded EPs using a rubric. Feasibility was assessed using descriptive statistics and student and fellow end-of-study questionnaires, which also measured impact. In addition, for each EP, students reported patient impact. Impact on EBM skills was assessed by change in EP scores over time and scores on an EBM objective structured clinical exam (OSCE) that were compared to controls from the prior year. <b>Results</b>: 117 students completed 402 EPs evaluated by 24 fellows. Average score was 7.34/9.00 (SD 1.58). 69 students (59%) and 21 fellows (88%) completed questionnaires. Most students thought EPs improved “Acquiring” and “Appraising”. Almost half thought EPs improved “Asking” and “Applying”. Fellows did not value grading EPs. For 18% of EPs, students reported a “change” or “potential change” in treatment. 56% “confirmed” treatment. EP scores increased by 1.27 (95% CI: 0.81–1.72). There were no differences in OSCE scores between cohorts. <b>Conclusions</b>: Integrating EPs into clerkships is feasible and has impact, yet OSCEs were unchanged, and research fellows had limitations as evaluators.
DOI: 10.6084/m9.figshare.3175606
title: NYC Open Datasets (Data Polygamy)

description: This contains the 300 datasets from NYC Open Data used in the following paper:<br><i>Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016</i><br>Note that these datasets have been cleaned and modified to serve as input for the Data Polygamy framework.
DOI: 10.6084/m9.figshare.3179476.v22
title: example RDFORM

description: This is an example rdform for use with figmeta. This form allows organizational affiliations to be associated with authors on a dataset. Organizations are represented with GRID uri's
DOI: 10.6084/m9.figshare.3179476.v21
title: example RDFORM

description: This is an example rdform for use with figmeta. This form allows organizational affiliations to be associated with authors on a dataset. Organizations are represented with GRID uri's
DOI: 10.6084/m9.figshare.3175588
title: Shirai and Imura_data_infant-specific gaze patterns to FOR.xlsx

description: Data for our manuscript "Infant-specific gaze patterns in response to radial optic flow".<br>
DOI: 10.6084/m9.figshare.3175606.v2
title: NYC Open Datasets (Data Polygamy)

description: This contains the 300 datasets from NYC Open Data used in the following paper:<br><i>Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016</i><br>Note that these datasets have been cleaned and modified to serve as input for the Data Polygamy framework.
DOI: 10.6084/m9.figshare.3175588.v1
title: Shirai and Imura_data_infant-specific gaze patterns to FOR.xlsx

description: Data for our manuscript "Infant-specific gaze patterns in response to radial optic flow".<br>
DOI: 10.6084/m9.figshare.3175606.v1
title: NYC Open Datasets (Data Polygamy)

description: This contains the 300 datasets from NYC Open Data used in the following paper:<br><i>Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016</i><br>Note that these datasets have been cleaned and modified to serve as input for the Data Polygamy framework.
DOI: 10.6084/m9.figshare.3175579
title: Shirai and Imura_data_infant-specific gaze patterns to FOR.xlsx

description: Data for the manuscript "Infant-specific gaze patterns in response to radial optic flow".<br>
DOI: 10.6084/m9.figshare.3175570
title: Traffic Speed Dataset

description: This is the Traffic Speed dataset used in the following paper:<br><i>Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016</i><br>The dataset includes records of the average speed in the streets of Manhattan, from 2009 to 2012, and was derived from the following paper:<br><i>Exploring Traffic Dynamics in Urban Environments using Vector-Valued Functions, Jorge Poco, Harish Doraiswamy, Huy. T. Vo, João L. D. Comba, Juliana Freire, and Cláudio. T. Silva. In Proceedings of the 2015 Eurographics Conference on Visualization (EuroVis '15). Eurographics Association, Aire-la-Ville, Switzerland, Switzerland, 161-170.</i>
DOI: 10.6084/m9.figshare.3175573
title: Citi Bike Dataset

description: This is a version of the Citi Bike trips dataset used in the following paper:<br><i>Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016</i><br>The dataset includes records of the trip data from NYC’s bike sharing system, from 2013 to 2014.<br>The original data is available at the Citi Bike website: https://www.citibikenyc.com/system-data
DOI: 10.6084/m9.figshare.3175561
title: Kenya Long-term Exclosure Experiment (KLEE) Vegetation Data 1999-2013

description: Herbaceous vegetation in all 18 KLEE plots has been sampled biannually (in February and June) or annually (in June) since 1995. Sampling periods follow rainy periods that are similar in terms of average rainfall. Due to improvements in species identification, pre-1999 surveys are not fully comparable to later data. Each of the eighteen 4 ha KLEE treatment plots contains a central hectare that is divided into a 10 x 10 m grid of 100 sampling stations. Aerial plant cover and composition are assessed at these stations by counting the number of pins hit by each species over a ten-point pin frame (with vertical pins separated by 5 cm; maximum one hit per pin per species). All 100 grid points were sampled 1999-2005, and every fifth grid point (20 per plot) was sampled from 2006 to 2013 (see Fig. 2 for current vegetation sampling layout). <br>This Excel datasheet contains vegetation data from 1999 – 2013. Later surveys have also been conducted and are available upon request. This Excel file is broken into the following sheets: o “Raw data” sheet: Scaled sum first hits data for each year (columns) organized by species, then by treatment and block. This sheet has data for all species.o “Lumped spp.” sheet: Data are lumped together for several species that we decided needed to be treated together. (e.g. Melhania spp.)♣ Standardizing species list:• Aristida spp. Aristida kenyensis• Eragrostis tenuifolia, racemosus and B lumped together• Justicia white and Justicia dichipteroides lumped together• Leucas glabrata and Leucas martinensis lumped together • Lily A and Lily B lumped together• Sedges (Cyperus, Mariscus and Kyllinga) lumped together♣ After lumping, multi-species taxa include:• Commelina spp• Eragrostis spp• Sedges• Hibiscus flavifolius/aponeurus• Leucas spp• Melhania spp• Plectranthus spp • Pseudognaphalium/Helichrysum• Fern (&lt;5%)• Justicia spp (&lt;5%)• Lily spp (&lt;5%)o 5% of surveys sheet: Binary designations for whether a species occurred or not (in each plot in each year). Then calculation of the percentage of “surveys” (plots*time) that species occurred in.o Spp &gt;5 % sheet: first hits for only those species that occurred in at least 5% of all sampled plot*time combinations. <br>
DOI: 10.6084/m9.figshare.3175549
title: Academic Tree Overview Slide

description: The Academic Family Tree tracks mentorship data for researchers in multiple fields and is a tool for discovering the influence of mentorship on the evolution of knowledge.
DOI: 10.6084/m9.figshare.3175573.v1
title: Citi Bike Dataset

description: This is a version of the Citi Bike trips dataset used in the following paper:<br><i>Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016</i><br>The dataset includes records of the trip data from NYC’s bike sharing system, from 2013 to 2014.<br>The original data is available at the Citi Bike website: https://www.citibikenyc.com/system-data
DOI: 10.6084/m9.figshare.3175579.v1
title: Shirai and Imura_data_infant-specific gaze patterns to FOR.xlsx

description: Data for the manuscript "Infant-specific gaze patterns in response to radial optic flow".<br>
DOI: 10.6084/m9.figshare.3175549.v2
title: Academic Tree Overview Slide

description: The Academic Family Tree tracks mentorship data for researchers in multiple fields and is a tool for discovering the influence of mentorship on the evolution of knowledge.
DOI: 10.6084/m9.figshare.3175579.v3
title: Shirai and Imura_data_infant-specific gaze patterns to FOR.xlsx

description: Data for the manuscript "Infant-specific gaze patterns in response to radial optic flow".<br>
DOI: 10.6084/m9.figshare.3175549.v1
title: Academic tree slide

description: The Academic Family Tree tracks mentorship data for researchers in multiple fields and is a tool for discovering the influence of mentorship on the evolution of knowledge.
DOI: 10.6084/m9.figshare.3175513
title: Male Sexual Function before and after Bariatric Surgery.xlsx

description: <b>Abstract</b> <b>Background </b>The prevalence of male sexual dysfunction in patients after bariatric surgery is not well described. <b> </b>The aim of the study is to compare the prevalence of erectile dysfunction (ED) and sexual quality of life after surgical weight loss with controls seeking bariatric surgery. <b>Aim </b>The aim of the study is to compare male sexual function and sexual quality of life after surgical weight loss with controls seeking bariatric surgery. <b>Materials and Methods </b>International Index of Erectile Function and Sexual Quality of Life–Male (SQoL-M) questionnaires were administered by e-mail to 152 men who had undergone weight-loss surgery. The control group consisted of 44 men who completed the questionnaires during their preoperative evaluation. <b>Results</b> 56% of men in the preoperative and 20% of men in the postoperative group reported erectile dysfunction (ED) [OR 5.1; 95% CI: 1.6 – 16.0, p=0.005]. The median (Q1, Q3) total IIEF score did not revealed significant difference between the preoperative (62.0 [37.5, 66.5]) and postoperative groups (67.0 [57.0, 70.0]). However, median scores in domains of erectile function (EF), sexual desire (SD), and overall satisfaction (OS) were significantly higher in the postoperative group. The median SQoL–M was significantly higher (81.8 [51.5, 89.4] vs 88.6 [84.8, 90.9]; p&lt;0.05) in the postoperative group. <b>Conclusions </b>A lower prevalence of erectile dysfunction and better sexual quality of life was observed in the patients after surgical weight loss. The improvement in male sexual function may be considered as an advantage of bariatric surgery.
DOI: 10.6084/m9.figshare.3175513.v1
title: Male Sexual Function before and after Bariatric Surgery.xlsx

description: <b>Abstract</b> <b>Background </b>The prevalence of male sexual dysfunction in patients after bariatric surgery is not well described. <b> </b>The aim of the study is to compare the prevalence of erectile dysfunction (ED) and sexual quality of life after surgical weight loss with controls seeking bariatric surgery. <b>Aim </b>The aim of the study is to compare male sexual function and sexual quality of life after surgical weight loss with controls seeking bariatric surgery. <b>Materials and Methods </b>International Index of Erectile Function and Sexual Quality of Life–Male (SQoL-M) questionnaires were administered by e-mail to 152 men who had undergone weight-loss surgery. The control group consisted of 44 men who completed the questionnaires during their preoperative evaluation. <b>Results</b> 56% of men in the preoperative and 20% of men in the postoperative group reported erectile dysfunction (ED) [OR 5.1; 95% CI: 1.6 – 16.0, p=0.005]. The median (Q1, Q3) total IIEF score did not revealed significant difference between the preoperative (62.0 [37.5, 66.5]) and postoperative groups (67.0 [57.0, 70.0]). However, median scores in domains of erectile function (EF), sexual desire (SD), and overall satisfaction (OS) were significantly higher in the postoperative group. The median SQoL–M was significantly higher (81.8 [51.5, 89.4] vs 88.6 [84.8, 90.9]; p&lt;0.05) in the postoperative group. <b>Conclusions </b>A lower prevalence of erectile dysfunction and better sexual quality of life was observed in the patients after surgical weight loss. The improvement in male sexual function may be considered as an advantage of bariatric surgery.
DOI: 10.6084/m9.figshare.3175393.v1
title: Potomac Project Files Directory

description: Directory containing analysis files from Qiime and R, including statistics and figures.
DOI: 10.6084/m9.figshare.3175417.v1
title: SBGRid DB Poster - Force2016.pdf

description: Access to experimental X--‐‑ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. In response to evolving needs of the structural biology community, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG, url: data.sbgrid.org), to preserve primary experimental datasets that support journal publications. Datasets archived with the SBDG are freely available to the research community under a public domain dedication license and the metadata for all datasets is published under the DataCite schema. Datasets are accessible to researchers through the Data Access Alliance infrastructure, which facilitates global and institutional data access. Our analysis of a pilot collection of crystallographic datasets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. It is anticipated that access to the experimental datasets will enable paradigm shift in the community from the static archive towards a much more dynamic body of continuously improving refined models. Following the success of this pilot study, the SBDG has extended its services to the entire community and will be used to develop support for other types of biomedical datasets, such as MicroED, Molecular Dynamics trajectories and LaPice Light--‐‑Sheet Microscopy.
DOI: 10.6084/m9.figshare.3175162
title: Animation showing the location of marine surface observations from ICOADS 2.5 for 1855 - 2011

description: Animation of point observations from ICOADS release 2.5 for the period 1855 - 2011. Each frame shows the observations within a 15 day period - the most recent 5 days in red, days 5 - 10 in green and 10 - 15 in blue.<br>
DOI: 10.6084/m9.figshare.3175156
title: Ventral Striatum Connectivity During Reward Anticipation in Adolescent Smokers

description: Substance misusers, including adolescent smokers, often have reduced reward system activity during processing of non-drug rewards. Using a psychophysiological interaction approach, we examined functional connectivity with the ventral striatum during reward anticipation in a large (<i>N</i> = 206) sample of adolescent smokers. Increased smoking frequency was associated with (1) increased connectivity with regions involved in saliency and valuation, including the orbitofrontal cortex and (2) reduced connectivity between the ventral striatum and regions associated with inhibition and risk aversion, including the right inferior frontal gyrus. These results demonstrate that functional connectivity during reward processing is relevant to adolescent addiction.
DOI: 10.6084/m9.figshare.3175162.v1
title: trackp_movie_all.mp4

description: Animation of point observations from ICOADS release 2.5 for the period 1855 - 2011. Each frame shows the observations within a 15 day period - the most recent 5 days in red, days 5 - 10 in green and 10 - 15 in blue.<br>
DOI: 10.6084/m9.figshare.3175162.v3
title: Animation showing the location of marine surface observations from ICOADS 2.5 for 1855 - 2011

description: Animation of point observations from ICOADS release 2.5 for the period 1855 - 2011. Each frame shows the observations within a 15 day period - the most recent 5 days in red, days 5 - 10 in green and 10 - 15 in blue.<br>
DOI: 10.6084/m9.figshare.3175162.v2
title: Animation showing the location og marine surface observations from ICOADS 2.5 for 1855 - 2911

description: Animation of point observations from ICOADS release 2.5 for the period 1855 - 2011. Each frame shows the observations within a 15 day period - the most recent 5 days in red, days 5 - 10 in green and 10 - 15 in blue.<br>
DOI: 10.6084/m9.figshare.3175123
title: Impact of SNPs on CpG Islands in the MYC and HRAS oncogenes and in a wide variety of tumor suppressor genes: A multi-cancer approach

description: Single nucleotide polymorphisms (SNPs) that occur within CpG Islands may lead to increased hypermethylation if a SNP allele has the potential to form a CpG dinucleotide, as well as potentially lead to hypomethylation if a SNP allele eliminates a CpG dinucleotide. We analyzed CpG-related SNP allele frequencies in whole genome sequences (WGS) across 5 TCGA cancer datasets, thereby exploiting a more recent appreciation for signaling pathway degeneracy in cancer. The cancer data sets were analyzed for SNPs in CpG islands associated with the oncogenes, HRAS and MYC, and in the CpG islands associated with the tumor suppressor genes, APC, DCC, and RB1. We determined that one SNP allele (rs3824120) in a CpG island associated with MYC which eliminated a CpG was more common in the cancer datasets than in the 100Genomes databases (p &lt; 0.01). For HRAS, 2 SNP alleles (rs112690925, rs7939028) that created CpG's occurred significantly less frequently in the cancer data sets than in the general SNP databases (e.g., rs7939028, p &lt; 0.0002, in comparison with AllSNPs(142)). Also, one SNP allele (rs4940177) that created a CpG in a CpG island associated with the DCC tumor suppressor gene, was more common in the cancer datasets (p &lt; 0.0007). To understand a broader picture of the potential of SNP alleles to create CpG's in CpG islands of tumor suppressor genes, we developed a scripted algorithm to assess the SNP alleles associated with the CpG islands of 43 tumor suppressor genes. The following tumor suppressor genes have the possibility of significant, percent increases in their CpG counts, depending on which SNP allele(s) is present: VHL, BRCA1, BRCA2, CHEK2, PTEN and RB1.
DOI: 10.6084/m9.figshare.3175123.v2
title: Impact of SNPs on CpG Islands in the MYC and HRAS oncogenes and in a wide variety of tumor suppressor genes: A multi-cancer approach

description: Single nucleotide polymorphisms (SNPs) that occur within CpG Islands may lead to increased hypermethylation if a SNP allele has the potential to form a CpG dinucleotide, as well as potentially lead to hypomethylation if a SNP allele eliminates a CpG dinucleotide. We analyzed CpG-related SNP allele frequencies in whole genome sequences (WGS) across 5 TCGA cancer datasets, thereby exploiting a more recent appreciation for signaling pathway degeneracy in cancer. The cancer data sets were analyzed for SNPs in CpG islands associated with the oncogenes, HRAS and MYC, and in the CpG islands associated with the tumor suppressor genes, APC, DCC, and RB1. We determined that one SNP allele (rs3824120) in a CpG island associated with MYC which eliminated a CpG was more common in the cancer datasets than in the 100Genomes databases (p &lt; 0.01). For HRAS, 2 SNP alleles (rs112690925, rs7939028) that created CpG's occurred significantly less frequently in the cancer data sets than in the general SNP databases (e.g., rs7939028, p &lt; 0.0002, in comparison with AllSNPs(142)). Also, one SNP allele (rs4940177) that created a CpG in a CpG island associated with the DCC tumor suppressor gene, was more common in the cancer datasets (p &lt; 0.0007). To understand a broader picture of the potential of SNP alleles to create CpG's in CpG islands of tumor suppressor genes, we developed a scripted algorithm to assess the SNP alleles associated with the CpG islands of 43 tumor suppressor genes. The following tumor suppressor genes have the possibility of significant, percent increases in their CpG counts, depending on which SNP allele(s) is present: VHL, BRCA1, BRCA2, CHEK2, PTEN and RB1.
DOI: 10.6084/m9.figshare.3175123.v1
title: Impact of SNPs on CpG Islands in the MYC and HRAS oncogenes and in a wide variety of tumor suppressor genes: a multi-cancer approach

description: Single nucleotide polymorphisms (SNPs) that occur within CpG Islands may lead to increased hypermethylation if a SNP allele has the potential to form a CpG dinucleotide, as well as potentially lead to hypomethylation if a SNP allele eliminates a CpG dinucleotide. We analyzed CpG-related SNP allele frequencies in whole genome sequences (WGS) across five TCGA cancer datasets, thereby exploiting a more recent appreciation for signaling pathway degeneracy in cancer. The cancer datasets were analyzed for SNPs in CpG islands associated with the oncogenes, HRAS and MYC, and in the CpG islands associated with the tumor suppressor genes, APC, DCC, and RB1. We determined that one SNP allele (rs3824120) in a CpG island associated with MYC which that eliminated a CpG was more common in the cancer datasets than in the 1000Genomes databases (p &lt; 0.01). For HRAS, two SNP alleles (rs112690925, rs7939028) that created CpG's occurred significantly less frequently in the cancer datasets than in the general SNP databases (e.g., rs7939028, p &lt; 0.0002, in comparison with AllSNPs(142)). Also, one SNP allele (rs4940177) that created a CpG in a CpG island associated with the DCC tumor suppressor gene, was more common in the cancer datasets (p &lt; 0.0007). To understand a broader picture of the potential of SNP alleles to create CpG's in CpG islands of tumor suppressor genes, we developed a scripted algorithm to assess the SNP alleles associated with the CpG islands of forty-three tumor suppressor genes. The following tumor suppressor genes have the possibility of significant, percent increases in their CpG counts, depending on which SNP allele(s) is present: VHL, BRCA1, BRCA2, CHEK2, PTEN and RB1.
DOI: 10.6084/m9.figshare.3175054
title: Genome sharing projects around the world: how to find data for your research

description: The poster introduces the Repositive platform for finding and accessing human genomic data for research. <br><br>If you need more genomic data for your research you can now search through multiple data sources from all over the world *in one place*! <br>Repositive is a new FREE community platform where you can find data for your research and establish data collaborations. <br><br>To try the platform follow this link: http://discover.repositive.io/?code=yMhLWKmJEtc=<br><br><br>