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- Creator:
- McCuen, Brett A.
- Description:
- The data were used to study the high-frequency geomagnetic disturbances within the magnetic field data. Included in this repository are the python scripts that perform an identification and classification of high-frequency signals within the magnetometer data that is downloaded from the databases listed in the Methodology section. All analysis and plots were created using subsequent Python libraries. The machine learning study implemented libraries from the sci-kit learn software. All of the specific methodology can be accessed in the readme.txt script.
- Keyword:
- geomagnetic field, high frequency, space weather, transient-large-amplitude, TLA, high frequency dB/dt, and dB/dt search algorithm
- Discipline:
- Science
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- Creator:
- Li, Jieming, Zhang, Leyou, Johnson-Buck, Alexander, and Walter, Nils G.
- Description:
- Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we have used deep learning to develop a rapid, automatic SMFM trace selector, termed AutoSiM, that improves the sensitivity and specificity of an assay for a DNA point mutation based on single-molecule recognition through equilibrium Poisson sampling (SiMREPS). The improved performance of AutoSiM is based on accepting both more true positives and fewer false positives than the conventional approach of hidden Markov modeling (HMM) followed by thresholding. As a second application, the selector was used for automated screening of single-molecule Förster resonance energy transfer (smFRET) data to identify high-quality traces for further analysis, and achieves ~90% concordance with manual selection while requiring less processing time. AutoSiM can be adapted readily to novel datasets, requiring only modest Transfer Learning.
- Keyword:
- deep learning, single-molecule fluorescence, total internal reflection microscopy, SiMREPS, smFRET, and Forster resonance energy transfer
- Citation to related publication:
- Li, J., Zhang, L., Johnson-Buck, A., & Walter, N. G. (2020). Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning. Nature Communications, 11(1), 5833. https://doi.org/10.1038/s41467-020-19673-1 and Hayward, S., Lund, P., Kang, Q., Johnson-Buck, A., Tewari, M., Walter, N. (2018). Single-molecule microscopy image data and analysis files for "Ultra-specific and Amplification-free Quantification of Mutant DNA by Single-molecule Kinetic Fingerprinting" [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/Z2CZ35DF
- Discipline:
- Science
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- Creator:
- Curlis, JD, Renney, TJ, Davis Rabosky, AR, and Moore, TY
- Description:
- Efficient comparisons of biological color patterns are critical for understanding the mechanisms by which organisms evolve in ecosystems, including sexual selection, predator-prey interactions, and thermoregulation. However, elongate or spiral-shaped organisms do not conform to the standard orientation and photographic techniques required for automated analysis. Currently, large-scale color analysis of elongate animals requires time-consuming manual landmarking, which reduces their representation in coloration research despite their ecological importance. We present Batch-Mask: an automated and customizable workflow to facilitate the analysis of large photographic data sets of non-standard biological subjects. First, we present a user guide to run an open-source region-based convolutional neural network with fine-tuned weights for identifying and isolating a biological subject from a background (masking). Then, we demonstrate how to combine masking with existing manual visual analysis tools into a single streamlined, automated workflow for comparing color patterns across images. Batch-Mask was 60x faster than manual landmarking, produced masks that correctly identified 96% of all snake pixels, and produced pattern energy results that were not significantly different from the manually landmarked data set. The fine-tuned weights for the masking neural network, user guide, and automated workflow substantially decrease the amount of time and attention required to quantitatively analyze non-standard biological subjects. By using these tools, biologists will be able to compare color, pattern, and shape differences in large data sets that include significant morphological variation in elongate body forms. This advance will be especially valuable for comparative analyses of natural history collections, and through automation can greatly expand the scale of space, time, or taxonomic breadth across which color variation can be quantitatively examined.
- Keyword:
- convolutional neural network, photography, sensory ecology, color evolution, vision, and image segmentation
- Citation to related publication:
- Curlis, Renney, Davis Rabosky, Moore (submitted) Batch-Mask: An automated Mask R-CNN workflow to isolate non-standard biological specimens for color pattern analysis.
- Discipline:
- Engineering and Science
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- Creator:
- Tye, Alexander R, Wolf, Aaron S, and Niemi, Nathan A
- Description:
- Detrital zircon age distributions provide robust insights into past sedimentary systems, but these age distributions are often complex and multi-peaked, with sample sizes too small to confidently resolve population distributions. This limited sampling hinders existing quantitative methods for comparing detrital zircon age distributions, which show systematic dependence on the sizes of compared samples. The proliferation of detrital zircon studies motivates the development of more robust quantitative methods. We present the first attempt, to our knowledge, to infer probability model ensembles (PMEs) for samples of detrital zircon ages using a Bayesian method. Our method infers the parent population age distribution from which a sample is drawn, using a Monte Carlo approach to aggregate a representative set of probability models that is consistent with the constraints that the sample data provide. Using the PMEs inferred from sample data, we develop a new estimate of correspondence between detrital zircon populations called Bayesian Population Correlation (BPC). Tests of BPC on synthetic and real detrital zircon age data show that it is nearly independent from sample size bias, unlike existing correspondence metrics. Robust BPC uncertainties can be readily estimated, enhancing interpretive value. When comparing two partially overlapping zircon age populations where the shared proportion of each population is independently varied, BPC results conform almost perfectly to expected values derived analytically from probability theory. This conformity of experimental and analytical results permits direct inference of the shared proportions of two detrital zircon age populations from BPC. We provide MATLAB scripts to facilitate the procedures we describe.
- Keyword:
- provenance, statistics, zircon, Bayesian, detrital, and density estimation
- Citation to related publication:
- A.R. Tye, A.S. Wolf, N.A. Niemi, Bayesian population correlation: A probabilistic approach to inferring and comparing population distributions for detrital zircon ages, Chemical Geology, Volume 518, 2019, Pages 67-78, ISSN 0009-2541, https://doi.org/10.1016/j.chemgeo.2019.03.039
- Discipline:
- Science
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- Creator:
- Stockbridge, Randy B. and Christian B. Macdonald
- Description:
- This data set includes text files (.csv files) for the bioinformatic annotation of SMR genes found in a dataset of phylogenetically diverse bacterial genomes. Bioinformatic analysis includes genome mining to identify SMR genes, prediction of the functional transporter subtype, and prediction of the direction of insertion in the bacterial membrane. Research overview: This bioinformatic dataset was prepared for a review on the structures, functions, and occurrence of Small Multidrug Resistance (SMR) Transporters. This dataset includes bioinformatic annotation of SMR genes identified in bacterial genomes from the Joint Genome Institute’s curated set of ~1000 Genomic Encyclopedia of Bacteria and Archaea (GEBA) genomes. The file GEBA_SMR_annotation.csv provides NCBI identification information (genome, species and chromosome information, locus tag, translation) and bioinformatic predictions of the SMR subtype and membrane insertion direction for each gene identified in the GEBA genome set. The file GEBA_SMR_species_table.csv has a separate entry for species in the GEBA genome set, along with the bioinformatic prediction of SMR subtype and membrane insertion direction for each SMR gene identified in the genome of that species. Dataset was generated by Christian B. Macdonald and Randy B. Stockbridge (Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI, 48019) Generation of this dataset was supported by National Institutes of Health grants R35-GM128768 to Randy B. Stockbridge. Use and access: This dataset is provided as a .csv file (comma separated values) and can be read using any text editor or spreadsheet software such as Microsoft Excel.
- Citation to related publication:
- Burata OE, Yeh TJ, Macdonald CB, Stockbridge RB. (2022). Still rocking in the structural era: a molecular overview of the Small Multidrug Resistance transporters. Journal of Biological Chemistry. In press.
- Discipline:
- Science
-
Biologically Inspired Robotics and Dynamical Systems (BIRDS) Lab
User Collection- Creator:
- Revzen, Shai
- Description:
- Professor Revzen and his team at the Biologically Inspired Robotics and Dynamical Systems (BIRDS) Lab are working on discovering, modeling, and reproducing the strategies animals use when interacting with physical objects. This work consists of collaboration with biomechanists to analyze experimental data, developing new mathematical tools for modeling and estimation of model parameters, and construction of robots which employ the new principles.
- Discipline:
- Science
7Works -
- Creator:
- BIRDS Lab, U. Michigan
- Description:
- These data were produced for ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics" and ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" to explore the trade-offs between various oscillator coupling models in modeling multilegged locomotion of Multipod robots with 6,8,10 and 12 legs. The data is stored in .csv.gz files, one file for each robot morphology. Details of how to run the processing code on the raw dataset to generate the processed files found here, as well as example code for loading the data found here, are in the README. This dataset is self contained and can be used on its own without running any of the provided code.
- Citation to related publication:
- Zhao, D. & Revzen, S. Multi-legged steering and slipping with low DoF hexapod robots Bioinspiration & biomimetics, 2020, 15, 045001 https://doi.org/10.1088/1748-3190/ab84c0, Zhao, D. Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" University of Michigan 2021 https://deepblue.lib.umich.edu/handle/2027.42/169985, and BIRDS Lab Multipod robot motion tracking data - RAW data, doi:10.7302/m05a-0d90
- Discipline:
- Engineering and Science
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- Creator:
- BIRDS Lab U. Michigan
- Description:
- These data were produced for ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics" and ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" to explore the trade-offs between various oscillator coupling models in modeling multilegged locomotion. The data were also used extensively in examining multi-contact slipping, in the studying the influence of number of legs on otherwise identical locomotion patterns, and in the use of geometric mechanics models for multilegged locomotion. Folder and file names encode the meta-data, with names following an informative naming convention documented in the README.
- Keyword:
- phase, multilegged, robot, and locomotion
- Citation to related publication:
- Zhao, D. & Revzen, S. Multi-legged steering and slipping with low DoF hexapod robots Bioinspiration & biomimetics, 2020, 15, 045001 https://doi.org/10.1088/1748-3190/ab84c0 and Zhao, D. Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" University of Michigan 2021 https://deepblue.lib.umich.edu/handle/2027.42/169985
- Discipline:
- Science and Engineering
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- Creator:
- BIRDS Lab U. Michigan
- Description:
- This dataset contains the videos used for https://doi.org/10.7302/m05a-0d90 (the "raw" motion tracking dataset), and is intended to be unpacked into the same directory tree. The data were produced for ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics" and ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" to explore the trade-offs between various oscillator coupling models in modeling multilegged locomotion. The data were also used extensively in examining multi-contact slipping, in the studying the influence of number of legs on otherwise identical locomotion patterns, and in the use of geometric mechanics models for multilegged locomotion. Folder and file names encode the meta-data, with names following an informative naming convention documented in the README.
- Keyword:
- phase, multilegged, robot, and locomotion
- Citation to related publication:
- BIRDS Lab U. Michigan. BIRDS Lab Multipod robot motion tracking data - RAW dataset [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/m05a-0d90, Zhao, D. Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" University of Michigan 2021 https://deepblue.lib.umich.edu/handle/2027.42/169985, and Zhao, D. & Revzen, S. Multi-legged steering and slipping with low DoF hexapod robots Bioinspiration & biomimetics, 2020, 15, 045001 https://doi.org/10.1088/1748-3190/ab84c0
- Discipline:
- Science and Engineering
-
- Creator:
- Sealey, Briana A., Larson, Joanna G., Westeen, Erin P., Sánchez-Paredes, Ciara M., Moore, Talia Y., and Davis Rabosky, Alison R.
- Description:
- In this study, we experimentally tested for the effects of four simulated predator cues on defensive displays in two species of South American calico snakes (genus Oxyrhopus). We found that juvenile snakes were both more likely to respond and to respond more strongly than adults and that displays were most common in response to tactile stimuli than to other treatments. However, we also found broad similarity across both simulated predator treatments and species in the components used in each snake’s defensive display, suggesting a high degree of stereotyping. This research suggests an important role for both ontogeny and intensity of predation risk in structuring variation in defensive behavior in Neotropical snakes and emphasizes the foundational importance of context dependence in conceptual frameworks for understanding predator-prey interactions. and *On January 4, 2024, “Supplementary_material.pdf” was replaced with an updated version that has slightly different versions of Figures S4 and S8 after an error in code was corrected. Within “HeatmapFigures.zip,” two code files, “IndividualHeatmaps_matrices.R” and “FigureS4_S8_averagedHeatmaps.R” were updated to correct the code error. Three additional files were added to both the “figures” and “matrices” folders within the subfolder “heatmaps.” These files represent the correlation matrices, by body part, and graphical representation of the matrices for one experimental trial that had previously been excluded due to the code error.
- Keyword:
- context-dependence, anti-predator behavior, Peruvian Amazon, ontogeny, coral snake mimicry, Colubridae
- Citation to related publication:
- Sealey, B.A.*, Larson, J.G.*, Westeen, E.P., Sanchez-Paredes, C.M., Moore, T.Y., Davis Rabosky, A.R. Body size and predator cues structure variation in defensive displays of Neotropical calico snakes (Oxyrhopus spp.). Ethology. In press. *Authors contributed equally
- Discipline:
- Science