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Collection
Stanford Research Data
The Fundamental Kinetic Database Utilizing Shock Tube Measurements Database summarizes the published shock tube experimental work performed under the supervision of Prof. Ronald K. Hanson of the Mechanical Engineering Department at Stanford University. The database covers the years from 1974 to 2013 inclusively. The database is divided into three types of data: ignition delay times, species time-history measurements, and reaction rate measurements. Volumes are in DOCX format and data tables in the volumes can be easily cut and pasted into separate user spread sheets. Volume 1 of the Fundamental Kinetic Database Utilizing Shock Tube Measurements includes a summary of the ignition delay time data measured and published by the Shock Tube Group in the Mechanical Engineering Department of Stanford University. The cut-off date for inclusion into this volume was January 2005. Volume 2 includes a summary of the species concentration time-histories. The cut-off date for inclusion in this volume was December 2005. Some of the figures embedded in this DOCX file can be opened using ORIGIN software. The data in this volume is available in tabular form in the accompanying ZIP file or in this volume. Volume 3 includes a summary of the reaction rate measurements. The cut-off date for inclusion in this volume was January 2009. Volume 4 includes a summary of the ignition delay time data. The start data for inclusion into this volume is January 2005 (the cutoff date for Volume 1) and the cutoff date is January 2014. Volume 5 includes a summary of the species concentration time-histories. The cut-off date for inclusion in this volume was January 2014. The format of this volume differs from that of Volume 2 in that we have not included the data files. Some of this data is available in the relevant papers and some of the data files may be accessible by contacting Dr. David Davidson at dfd@stanford.edu. Much of this data was used for reaction rate constant determinations and the mixtures in the experiments reflect this use; the mixtures were designed to isolate or enhance the sensitivity of the measured species to a particular reaction rate constant. Volume 6 includes a summary of the reaction rate measurements. The cut-off date for inclusion in this volume was January 2014.
Collection
Stanford Research Data
This a snapshot of the NeuroVault.org database. It include all public collections of statistical maps deposited in NeuroVault as long as they were linked to an external publication. This snapshot is an attempt to improve chances of long term persistance of data deposited in NeuroVault.org.
Collection
Stanford Research Data
This data set is a compilation of the historical CMOS technology scaling data presented in the ITRS, journals, and conferences including IEDM and VLSI Technology from 1988 and onward. Chi-Shuen Lee, Jieying Luo, and H.-S. Philip Wong at Stanford University compiled the data; Thomas N. Theis at Columbia University provided the data originally compiled by Robert W. Keyes at IBM T.J. Watson Research Center and published in Figure 1 of Rolf Landauer's 1988 paper. The historical scaling trend of logic switching energy and integration density were published in Figure 1 and 2, respectively in the paper, "The End of Moore’s Law: A New Beginning for Information Technology" by Theis and Wong (see Related Published Work below for the full citation.
Collection
Stanford Research Data
In matrix recovery from random linear measurements, one is interested in recovering an unknown $M$-by-$N$ matrix $X_0$ from $n
Collection
Reproducible Research Support for Statistics of the Microbiome
Complete ribosomal sequence variant abundance data and analysis files for paper entitled: Multidomain Analyses of a Longitudinal Human Microbiome Intestinal Cleanout Perturbation Experiment. This work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods. Funded by NIH TR01 grant AI112401.
Collection
Payne Paleobiology Lab Data Files
Over the past 3.8 billion years, the maximum size of living organisms has increased by approximately 18 orders of magnitude. Much of this increase is associated with two major evolutionary innovations: the evolution of eukaryotes from prokaryotic cells ~ 1.9 billion years ago (Ga), and multicellular life diversifying from unicellular ancestors ~ 0.6 Ga. However, the quantitative relationship between organismal size and structural complexity remains poorly documented. We assessed this relationship using a comprehensive dataset that includes organismal size and level of biological complexity for 11,172 extant genera. We find that the distributions of sizes within complexity levels are unimodal whereas the aggregate distribution is multimodal. Moreover, both the mean size and the range of size occupied increases with each additional level of vertical complexity. Interestingly, the increase in size range is non-symmetric; the maximum organismal size increases more than the minimum. The majority of the observed increase in organismal size over the Geozoic is accounted for by two discrete jumps in complexity rather than evolutionary trends within levels of complexity. Our results provide quantitative support for an evolutionary expansion away from a minimal size constraint and suggest a fundamental rescaling of the constrains on maximal size as biological complexity increases.
Collection
Stanford Research Data
# Data for Waskom and Wagner (2017) PNAS This repository contains data related to the following paper: Waskom M.L., Wagner A.D. (2017). Distributed representation of context by intrinsic subnetworks in prefrontal cortex. Proceedings of the National Academy of the Sciences, USA. The paper is available on the PNAS website: http://www.pnas.org/cgi/doi/10.1073/pnas.1615269114 Code implementing the results in the paper is included here and is also available on github: https://github.com/WagnerLabPapers/Waskom_PNAS_2017 The datasets in this repository are organized in subdirectories as follows: ## Preprocessed data - roi_cache: Preprocessed/denoised time series data from the ROIs in the paper ## Analysis results - decoding_analysis: Decoding analyses and estimated context preferences - spatial_analysis: Spatial organization analyses - correlation_analysis: Spontaneous correlation analyses ## Supporting data - mesh: Computationally reconstructed cortex models - reg: Functional template and registration relating it to anatomical space ## Analysis code - code: A copy of the analysis code repository available on github ## License Copyright (c) 2017, Michael Waskom and Anthony Wagner Released under a CC-BY 4.0 License
Collection
Marine Biogeochemistry Data
The 2013 US GEOTRACES Eastern Pacific Zonal Transect (GP16) extended from the Peruvian coast to Tahiti, along a line that fell between 10 and 15°S. This transect sampled the Peruvian oxygen deficient zone (ODZ) and the hydrothermal plume extending from the East Pacific Rise (EPR) for a variety of trace elements and isotopes (TEIs). Here we report nutrient and hydrographic measurements collected on this cruise, as well as results from an Optimum Multiparameter Analysis (OMPA) to quantify the fractional contributions of endmember water masses in each sample. In the thermocline, Equatorial Subsurface Water (ESSW) dominated the low oxygen waters of the eastern tropical South Pacific, blending into Eastern South Pacific Intermediate Water (ESPIW) and South Pacific Central Water (SPCW) further west. Below the thermocline, distributions of Antarctic Intermediate Water (AAIW) and Equatorial Pacific Intermediate Water (EqPIW) were relatively homogenous along the section between 800 and 1200 m depth. Deeper in the water column, distinct water mass signatures were found on opposite sides of the EPR: southward flowing Pacific Deep Water (PDW) dominated the basin east of the EPR, while the northward flowing Antarctic Bottom Water (AABW) and Lower Circumpolar Deep Water (LCDW) had the strongest contributions on the western side of the EPR. These findings support previous studies that indicate the Peruvian ODZ is largely contained within ESSW and that the EPR plays an important role in steering water mass distributions in the deep waters of the tropical Pacific. Overall, these results agree well with previous water mass analyses in this region and are consistent with the general circulation patterns in the eastern tropical Pacific.
Dataset
1 online resource
At approximately 1 km resolution (30" X 30"), LandScan is the finest resolution global population distribution data available and represents an ambient population (average over 24 hours). The LandScan algorithm uses spatial data and imagery analysis technologies and a multi-variable dasymetric modeling approach to disaggregate census counts within an administrative boundary. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution models are tailored to match the data conditions and geographical nature of each individual country and region.
Collection
Stanford Research Data
Impulsivity is a variable behavioral trait that depends on numerous factors. For example, increasing the absolute magnitude of available choice options promotes far-sighted decisions. We argue that this magnitude effect arises in part from differential exertion of self-control as the perceived importance of the choice increases. First, we demonstrate that frontal executive control areas are engaged for more difficult decisions and that this effect is enhanced for high magnitude rewards. Second, we show that increased hunger, which is associated with lower self-control, reduces the magnitude effect. Third, we tested an intervention designed to increase self-control and show that it interferes with the magnitude effect. Taken together, our findings challenge existing theories about the magnitude effect and suggest that visceral and cognitive factors affecting choice may do so by influencing self-control.
Collection
Stanford Research Data
This dataset contains cortical (EEG) and behavioral data collected during natural music listening. Dense-array EEG was recorded from 20 adult participants who each heard a set of 10 full-length songs with electronically produced beats at various tempos. In a separate subsequent listen, each participant tapped to the beat of a 35-second excerpt from each song. Participants also delivered ratings of familiarity and enjoyment for each full-length song during the EEG recording. Finally, the dataset includes basic demographic information about the participants, as well as Matlab scripts to perform the illustrated analyses presented in the paper introducing the dataset (Losorelli et al., 2017). Cleaned and aggregated data are published in Matlab format; raw EEG is published in Matlab format, while raw tapping data are published in .txt format. Stimulus audio is not published, but metadata links are provided. Cleaned EEG files have been aggregated across participants on a per-song basis and range in size from 656-721MB. Raw EEG recordings (two recordings per participant) range in size from 753-861MB. All other files are less than 1MB in size. In total the dataset comprises 55 downloadable files, with a total size of 39GB.
Collection
Mapping the Republic of Letters
The json file(s) were created within the visualization application Palladio (hdlab.stanford.edu/palladio).
Collection
Reproducible Research Support for Statistics of the Microbiome
Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. Previous studies have suggested that the maternal vaginal microbiota contributes to the pathophysiology of PTB, but conflicting results in recent years have raised doubts. We conducted a study of PTB compared to term birth in two cohorts of pregnant women: one predominantly Caucasian (n=39) at low risk for PTB, the second predominantly African American and at high-risk (n=96). We profiled the taxonomic composition of 2,179 vaginal swabs collected prospectively and weekly during gestation using 16S rRNA gene sequencing. Previously proposed associations between PTB and lower Lactobacillus and higher Gardnerella abundances replicated in the low-risk cohort, but not in the high-risk cohort. Using state-of-the-art bioinformatic techniques, we improved our taxonomic resolution to the species and subspecies level, revealing that Lactobacillus crispatus was protective against PTB in both cohorts, while Lactobacillus iners was not, and that a subspecies clade of Gardnerella vaginalis explained the genus association with PTB. Patterns of co-occurrence between L. crispatus and Gardnerella were highly exclusive, while Gardnerella and L. iners often co-existed at high frequencies. We argue that the vaginal microbiota is better represented by the quantitative frequencies of these key taxa than by classifying communities into five community state types. Our findings extend and corroborate the association between the vaginal microbiota and PTB, suggest that previous conflicting results may reflect the different risk profile of women of black race, offer a more robust signature of PTB, and demonstrate the benefits of high-resolution statistical bioinformatics.
Database topics
Communication and Journalism; Sociology; Government Information: State and Local
Dataset
1 online resource : sound, color illustrations
On a typical day in the United States, police officers make more than 50,000 traffic stops. Our team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Our goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public."--Home page.
Collection
Stanford Research Data
"RNA viruses have a great evolutionary capacity, allowing them to quickly adapt and overcome challenges encountered during infection. Here we show that poliovirus infection requires adaptation to tissue-specific innate immune microenvironments. The virus’ ability to establish robust infection and virulence correlates with its evolutionary capacity. We further identified a region in the multi-functional poliovirus protein 2B as a hotspot for the accumulation of minor alleles that facilitate a more effective suppression of the interferon response. We propose that population genetic dynamics enables poliovirus spread between tissues through optimization of the genetic composition of low frequency variants, which together cooperate to circumvent tissue-specific challenges. Thus, intrahost virus evolution determines pathogenesis, allowing a dynamic regulation of viral functions required to overcome barriers to infection." The data set deposited here includes the following: 1. Gene expression 2. Viral allele fitness values computed from in vitro passaged populations. "FitnessValues.csv" 3. Host gene expression values computed by TopHat/CuffDiff pipeline. "hostgeneexpressionvalues_PVinfection.csv" 4. Genetic composition data for in vivo poliovirus populations determined by RNAseq. "InVivoPVRNAseq.zip" 5. Mus musculus GO annotation db Rdata structure. "mmusAnnots.Rdata" 5. Analysis data for clustering of significant DEGs. "PV_mmus_cluster_MDS_FCdata.txt" 6. Raw CuffDiff output "RawCuffDiffData.zip"
Collection
Stanford Research Data
Group II chaperonins are ring-shaped chaperones. Their ATP-dependent allosteric regulation remains ill-defined. Given their complex oligomeric topology, structural techniques have had limited success in suggesting allosteric determinants. High sequence conservation among chaperonins has also hindered the prediction of allosteric networks, as many mathematical covariation approaches cannot be applied to conserved proteins. Here, we develop an information theoretic strategy robust to residue conservation and apply it to group II chaperonins. We identify a contiguous network of covarying residues that connects all nucleotide binding pockets within each chaperonin ring. An interfacial residue between the networks of neighboring subunits controls positive cooperativity by communicating nucleotide occupancy. Strikingly, chaperonin allostery is tunable through mutations at this position. Naturally occurring variants that double the extent of positive cooperativity are less prevalent in nature. We propose that being less cooperative that attainable allows the chaperonins to support robust folding over a wider range of metabolic conditions.
Collection
Folding@home Collection
It is unclear how the known atomic structures of NMDA receptors (NMDARs) relate to the functional states of NMDARs inferred from electrophysiological recordings. We address this problem by all-atom computer simulations, a method successfully applied in the past to much smaller biomolecules. Our simulations predict that four ‘non-active’ cryoEM structures of NMDARs rapidly interconvert on submicrosecond timescales, and therefore, correspond to the same functional state of the receptor. The files 'structures_and_computations.zip' and 'structures_and_computations.tar.gz' (the same contents, different archiving formats) contain scripts and high-level data mentioned in the paper (computation of time-independent based components, specification of Markov state models, etc.). The file 'trajectories.tar' can be assembled from the provided 280 files named 'trajectories.tar.part_*' by "cat trajectories.tar.part_* > trajectories.tar". The file 'trajectories.tar' contains the molecular dynamics trajectories of NMDA receptors used in this paper. Note that 'trajectories.tar' is 2.8 Tb in size, as well as the folder generated by untarring it.
Collection
Stanford Research Data
Continuous monitoring of physiological parameters inside a living cell will lead to major advances in understanding of biology and complex diseases, such as cancer. It also enables us to develop new medical diagnostics and therapeutics. In addition, progress in nanofabrication and wireless communication has opened up the potential of making our wireless chip small enough that it can be wholly inserted into a cell. To investigate how the chip could be internalized into the cell and how the chip would affect cell physiology, we designed and fabricated a series of 3D multilayer structures with different sizes as a potential RFID (Radio Frequency IDentification) cell tracker. Our experiments show that the chips with smaller sizes than 21 micron x 9 micron x 1.5 micron can be easily internalized by various types of living cells, such as macrophages, cancer cells, and normal/healthy cells. The incubated cells with internalized chips stayed alive during the 5 days of monitoring. Also, we observed successful cell division from these incubated cells. These results are the first steps towards long-term, wireless, intracellular physiologic monitoring. This data set contains short and long videos of cell division or internalization (as indicated in the file names) of macrophages cells incubating microscale silicon chips of 4 different sizes -- 12 micron x 12 micron, 9 micron x 15 micron, 9 micron x 18 micron, and 9 micron x 21 micron.
Collection
Stanford Research Data
Continuous monitoring of physiological parameters inside a living cell will lead to major advances in understanding of biology and complex diseases, such as cancer. It also enables us to develop new medical diagnostics and therapeutics. In addition, progress in nanofabrication and wireless communication has opened up the potential of making our wireless chip small enough that it can be wholly inserted into a cell. To investigate how the chip could be internalized into the cell and how the chip would affect cell physiology, we designed and fabricated a series of 3D multilayer structures with different sizes as a potential RFID (Radio Frequency IDentification) cell tracker. Our experiments show that the chips with smaller sizes than 21 micron x 9 micron x 1.5 micron can be easily internalized by various types of living cells, such as macrophages, cancer cells, and normal/healthy cells. The incubated cells with internalized chips stayed alive during the 5 days of monitoring. Also, we observed successful cell division from these incubated cells. These results are the first steps towards long-term, wireless, intracellular physiologic monitoring. This data set contains short and long videos of internalization or incubation of melanoma, breast, colon cancer or healthy fibroblast skin cells with microscale silicon tags of 4 different sizes -- 12 micron x 12 micron, 9 micron x 15 micron, 9 micron x 18 micron, and 9 micron x 21 micron.
Collection
VISTA Lab
We use modern computer graphics tools such as ray-tracing, digital camera simulation tools, and a physically accurate model of seawater constituents to simulate how light is captured by the imaging sensor in a digital camera placed in underwater ocean environments. Our water model includes parameters for the type and amount of phytoplankton, the concentration of chlorophyll, the amount of dissolved organic matter (CDOM) and the concentration of detritus (non-algal particles, NAP). We show that by adjusting the model parameters, we can predict real sensor data captured by a digital camera at a fixed distance and depth from a reference target with known spectral reflectance. We also provide an open-source implementation of all our tools and simulations. This repository contains sample data (camera images and simulation results) that demonstrates how the simulation environment works and that allows to reproduce the analyses we present in publications.