University of Texas at Austin Dataverse Collection

The University of Texas at Austin Dataverse Collection serves as a platform for publishing and archiving the University's research data. It was established to help UT Austin's research community meet the data sharing requirements of funders and publishers, to facilitate data citation, to promote collaboration, to enable reproducibility, and to encourage data reuse.

Polar and Planetary Geophysics

Computational Waves and Optics Imaging Group

LLILAS Benson Latin American Studies and Collections Dataverse

Mood Disorders Laboratory Dataverse

Pavement Science and Engineering

Bridging Barriers Collection

Paleontology Board Game Dataverse

UT Signed Language Research Dataverse

Soft Tissue Biomechanics Laboratory

Hodges Research Group Dataverse

UTCT Dataverse

Texas Robotics

Bureau of Economic Geology

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1,231 to 1,240 of 1,732 Results

Data repository for the paper titled "Diffuse blue vs. structural silver—comparing alternative strategies for pelagic background matching between two coral reef fishes"(University of Texas at Austin) Aug 5, 2020
Search details for Ai Chi scoping review Jul 29, 2020 - Ai Chi Scoping Review Dunlap, Emily, 2020, "Search details for Ai Chi scoping review", https://doi.org/10.18738/T8/I5WX7U, Texas Data Repository, V1 This excel sheet lists specific search terms and results for Ai Chi scoping review 2020
Ai Chi Scoping Review(University of Texas at Austin) Jul 29, 2020 This dataverse contains relevant information for a scoping review. The purpose of the review is to summarize available research on Ai Chi for balance, pain, functional mobility, and QoL in adults. The qualitative analysis reveals a number of favorable results with benefits from A...
Hydrogeologic Atlas of Southwest Travis County(University of Texas at Austin) Jul 27, 2020 This study presents a compilation of existing and new hydrogeologic data in the form of a hydrogeologic atlas with accompanying digital datasets intended to improve the collective understanding of groundwater resources in SWTC. The study was a collaboration between the Barton Spr...
Data munging code for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STARD trial" Jul 24, 2020 - SNPs, prediction, and STARD trial Shumake, Jason, 2020, "Data munging code for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"", https://doi.org/10.18738/T8/NVAUFR, Texas Data Repository, V1 Data munging code
Primary analysis code and report for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STARD trial" Jul 24, 2020 - SNPs, prediction, and STARD trial Shumake, Jason, 2020, "Primary analysis code and report for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"", https://doi.org/10.18738/T8/YC49CY, Texas Data Repository, V1 Analysis code for the results presented in the manuscript.
R scripts for snp selection and ensemble learning for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STARD Jul 24, 2020 - SNPs, prediction, and STARD trial Shumake, Jason, 2020, "R scripts for snp selection and ensemble learning for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STARD", https://doi.org/10.18738/T8/GHJK6C, Texas Data Repository, V1 R scripts for snp selection and ensemble learning in STARD trial.
SNPs, prediction, and STARD trial(University of Texas at Austin) Jul 24, 2020Mood Disorders Laboratory Dataverse Analysis code and supplemental materials for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STARD trial"
Analysis Code and Supplementary Materials for Association between negative cognitive bias and depression: A symptom-level approach Jul 20, 2020 - Association between negative cognitive bias and depression: A symptom-level approach Beevers, Christopher, 2019, "Analysis Code and Supplementary Materials for Association between negative cognitive bias and depression: A symptom-level approach", https://doi.org/10.18738/T8/2QPR9Z, Texas Data Repository, V2 These files are the supplementary materials and analysis code used to generate the results reported in the Journal of Abnormal manuscript.
Data files for "Comparison of Groundwater Storage Changes from GRACE Satellites with Monitoring and Modeling of Major U.S. Aquifers"(University of Texas at Austin) Jul 16, 2020 Supplementary materials for "Comparison of Groundwater Storage Changes from GRACE Satellites with Monitoring and Modeling of Major U.S. Aquifers" paper by (Rateb et al 2020)

Data repository for the paper titled "Diffuse blue vs. structural silver—comparing alternative strategies for pelagic background matching between two coral reef fishes"(University of Texas at Austin)

Aug 5, 2020

Search details for Ai Chi scoping review

Jul 29, 2020 - Ai Chi Scoping Review

Dunlap, Emily, 2020, "Search details for Ai Chi scoping review", https://doi.org/10.18738/T8/I5WX7U, Texas Data Repository, V1

This excel sheet lists specific search terms and results for Ai Chi scoping review 2020

Ai Chi Scoping Review(University of Texas at Austin)

Jul 29, 2020

This dataverse contains relevant information for a scoping review. The purpose of the review is to summarize available research on Ai Chi for balance, pain, functional mobility, and QoL in adults. The qualitative analysis reveals a number of favorable results with benefits from A...

Hydrogeologic Atlas of Southwest Travis County(University of Texas at Austin)

Jul 27, 2020

This study presents a compilation of existing and new hydrogeologic data in the form of a hydrogeologic atlas with accompanying digital datasets intended to improve the collective understanding of groundwater resources in SWTC. The study was a collaboration between the Barton Spr...

Data munging code for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"

Jul 24, 2020 - SNPs, prediction, and STAR*D trial

Shumake, Jason, 2020, "Data munging code for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"", https://doi.org/10.18738/T8/NVAUFR, Texas Data Repository, V1

Data munging code

Primary analysis code and report for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"

Jul 24, 2020 - SNPs, prediction, and STAR*D trial

Shumake, Jason, 2020, "Primary analysis code and report for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"", https://doi.org/10.18738/T8/YC49CY, Texas Data Repository, V1

Analysis code for the results presented in the manuscript.

R scripts for snp selection and ensemble learning for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D

Jul 24, 2020 - SNPs, prediction, and STAR*D trial

Shumake, Jason, 2020, "R scripts for snp selection and ensemble learning for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D", https://doi.org/10.18738/T8/GHJK6C, Texas Data Repository, V1

R scripts for snp selection and ensemble learning in STAR*D trial.

SNPs, prediction, and STAR*D trial(University of Texas at Austin)

Jul 24, 2020Mood Disorders Laboratory Dataverse

Analysis code and supplemental materials for "Inclusion of single nucleotide polymorphisms into an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response in the STAR*D trial"

Analysis Code and Supplementary Materials for Association between negative cognitive bias and depression: A symptom-level approach

Jul 20, 2020 - Association between negative cognitive bias and depression: A symptom-level approach

Beevers, Christopher, 2019, "Analysis Code and Supplementary Materials for Association between negative cognitive bias and depression: A symptom-level approach", https://doi.org/10.18738/T8/2QPR9Z, Texas Data Repository, V2

These files are the supplementary materials and analysis code used to generate the results reported in the Journal of Abnormal manuscript.

Data files for "Comparison of Groundwater Storage Changes from GRACE Satellites with Monitoring and Modeling of Major U.S. Aquifers"(University of Texas at Austin)

Jul 16, 2020

Supplementary materials for "Comparison of Groundwater Storage Changes from GRACE Satellites with Monitoring and Modeling of Major U.S. Aquifers" paper by (Rateb et al 2020)

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