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625 results for “rules”
Concrete Permuted Rule Operations
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Experimental HIL datasets of a heat pump controlled by MPC or rule-based controllers for energy flexibility
<p>Hardware-in-the-loop experiment performed in the SEILAB laboratory of IREC<br> Air-to-water heat pump including a DHW tank for production of SH and DHW, which external unit is placed in a climate chamber that reproduces the desired weather conditions dynamically<br> Control is MPC or rule-based, both triggered either by a signal of price or CO2 intensity from the grid (4 series of experiments)<br> Connected to virtual residential building (flat) in Spanish Mediterranean climate<br> More information:<br> https://doi.org/10.1109/ACCESS.2019.2903084</p>
Flood Hazard Maps and Associated Data for Case Study: Funding rules that promote equity in climate adaptation outcomes
<p>Inundation grids for multiple return periods and multiple scenarios. Please see the underlying study for more details about the methods. The data here can be reproduced following the code and instructions at this repository: https://github.com/CoRE-Lab-UCF/Pollack_et_al_2024/tree/main. Also available here: https://doi.org/10.5281/zenodo.14515896. </p>
Complex basis of hybrid female sterility and Haldane's rule in Heliconius butterflies: Z-linkage and epistasis - RADseq and RNAseq reads, sterility phenotypes and pedigree
<p>RADseq and RNAseq reads (.fastq files), and sterility phenotypes and pedigree (.xlsx) using for QTL mapping of Heliconius pardalinus sterility crosses in Rosser, N., Edelman, N.B., Queste, L.M., Nelson, M., Seixas, F., Dasmahapatra, K.K. and Mallet, J., 2021. Complex basis of hybrid female sterility and Haldane’s rule in Heliconius butterflies: Z-linkage and epistasis, accepted for publication in Molecular Ecology. Queries to Neil Rosser (neil.rosser@york.ac.uk). </p> <p> </p>
The contribution of genetic and environmental effects to Bergmann's rule and Allen's rule in house mice
<p>Data associated with the manuscript, "The contribution of genetic and environmental effects to Bergmann's rule and Allen's rule in house mice".</p> <p><strong>Abstract</strong>: Distinguishing between genetic, environmental, and genotype-by-environment effects is central to understanding geographic variation in phenotypic clines. Two of the best-documented phenotypic clines are Bergmann's rule and Allen's rule, which describe larger body sizes and shortened extremities in colder climates, respectively. Although numerous studies have found inter- and intraspecific evidence for both ecogeographic patterns, we still have a poor understanding of the extent to which these patterns are driven by genetics, environment, or both. Here, we measured the genetic and environmental contributions to Bergmann's rule and Allen's rule across introduced populations of house mice (<em>Mus musculus domesticus</em>) in the Americas. First, we documented clines for body mass, tail length, and ear length in natural populations, and found that these conform to both Bergmann's rule and Allen's rule. We then raised descendants of wild-caught mice in the lab and showed that these differences persisted in a common environment and are heritable, indicating that they have a genetic basis. Finally, using a full-sib design, we reared mice under warm and cold conditions. We found very little plasticity associated with body size, suggesting that Bergmann's rule has been shaped by strong directional selection in house mice. However, extremities showed considerable plasticity, as both tails and ears grew shorter in cold environments. These results indicate that adaptive phenotypic plasticity as well as genetic changes underlie major patterns of clinal variation in house mice and likely facilitated their rapid expansion into new environments across the Americas.</p> <p>Supplemental data files are provided below.</p> <p>Code associated with the analysis of these data can be found on GitHub at <a href="https://github.com/malballinger/Ballinger_allenbergmann_AmNat_2021">https://github.com/malballinger/Ballinger_allenbergmann_AmNat_2021</a>.</p>
Pre-parsed reaction rule files from RetroRules (rr02-rp2-hs)
<p>RetroRules (https://retrorules.org/) is a database of reaction rules for metabolic pathway discovery and metabolic engineering. Reaction rules are generic descriptions of reactions to be used in retrosynthesis workflows in order to enumerate possible biosynthetic routes connecting target molecules to precursors. The use of such rules is becoming more and more important in the context of synthetic biology applied to de novo pathway discovery and in systems biology to discover underground metabolism due to enzyme promiscuity.</p> <p>Pre-parsed reaction rule files are ready-to-use files that provide all the non-stereo reaction rules for diameter 2 to 16. The present dataset have the following specifications:</p> <ul> <li>release: rr02</li> <li>diameters: 2 to 16</li> <li>Hs handling: explicit</li> <li>Compatibility: RetroPath2.0 ready</li> </ul> <p>How to cite: Duigou T, du Lac M, Carbonell P, Faulon JL. RetroRules: a database of reaction rules for engineering biology. <em>Nucleic Acids Research</em>, 2019. | doi: <a href="https://doi.org/10.1093/nar/gky940">10.1093/nar/gky940</a> | PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30321422">30321422</a></p> <p> </p>
Pre-parsed reaction rule files from RetroRules (rr01-rp2-hs)
<p>RetroRules (https://retrorules.org/) is a database of reaction rules for metabolic pathway discovery and metabolic engineering. Reaction rules are generic descriptions of reactions to be used in retrosynthesis workflows in order to enumerate possible biosynthetic routes connecting target molecules to precursors. The use of such rules is becoming more and more important in the context of synthetic biology applied to de novo pathway discovery and in systems biology to discover underground metabolism due to enzyme promiscuity.</p> <p>Pre-parsed reaction rule files are ready-to-use files that provide all the non-stereo reaction rules for diameter 2 to 16. The present dataset have the following specifications:</p> <ul> <li>release: rr01</li> <li>diameters: 2 to 16</li> <li>Hs handling: explicit</li> <li>Compatibility: RetroPath2.0 ready</li> </ul> <p>How to cite: Duigou T, du Lac M, Carbonell P, Faulon JL. RetroRules: a database of reaction rules for engineering biology. <em>Nucleic Acids Research</em>, 2019. | doi: <a href="https://doi.org/10.1093/nar/gky940">10.1093/nar/gky940</a> | PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30321422">30321422</a></p> <p> </p>
Pre-parsed reaction rule files from RetroRules (rr02-rp3-nohs)
<p>RetroRules (https://retrorules.org) is a database of reaction rules for metabolic pathway discovery and metabolic engineering. Reaction rules are generic descriptions of reactions to be used in retrosynthesis workflows in order to enumerate possible biosynthetic routes connecting target molecules to precursors. The use of such rules is becoming more and more important in the context of synthetic biology applied to de novo pathway discovery and in systems biology to discover underground metabolism due to enzyme promiscuity.</p> <p>Pre-parsed reaction rule files are ready-to-use files that provide all the non-stereo reaction rules for diameter 2 to 16. The present dataset have the following specifications:</p> <ul> <li>release: rr02</li> <li>diameters: 2 to 16</li> <li>Hs handling: implicit</li> <li>Compatibility: RetroPath RL ready</li> </ul> <p>How to cite: Duigou T, du Lac M, Carbonell P, Faulon JL. RetroRules: a database of reaction rules for engineering biology. <em>Nucleic Acids Research</em>, 2019. | doi: <a href="https://doi.org/10.1093/nar/gky940">10.1093/nar/gky940</a> | PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30321422">30321422</a></p> <p> </p>
MERRIN: MEtabolic Regulation Rule INference from time series data (Docker image and notebooks)
<p>This record contains notebooks and Docker image for reproducing the results of the paper "MERRIN: MEtabolic Regulation Rule INference from time series data" published as part of the ECCB 2022 conference.</p> <p>Notebooks can be executed interactively within the Docker image <code>bioasp/merrin:v1</code> which extends the <a href="http://colomoto.org/notebook">CoLoMoTo Docker</a> version <code>2021-02-01.</code></p> <p>Also see <a href="https://github.com/bioasp/merrin-covert">https://github.com/bioasp/merrin-covert</a></p> <p>The Docker image can be executed as follows:</p> <pre><code class="language-bash">docker pull bioasp/merrin:v1 docker run -it --rm -p 8888:8888 bioasp/merrin:v1 </code></pre> <p>then point your browser to <a href="http://127.0.0.1:8888">http://127.0.0.1:8888</a>.</p> <p>The image can be imported using the command <code>docker load</code> with the image file provided in this record:</p> <pre><code>docker load -i image.tar.gz</code></pre> <p>or with the <code>donodo</code> command available at <a href="https://github.com/pauleve/donodo">https://github.com/pauleve/donodo</a>:</p> <pre><code>pip install -U donodo donodo pull 10.5281/zenodo.6670165</code></pre>
Datasets for Collections: Rule Based Uploader tutorial
<p>Datasets for Collections: Rule Based Uploader tutorial at <a href="https://galaxyproject.github.io/training-material/topics/galaxy-data-manipulation/tutorials/upload-rules/tutorial.html">https://galaxyproject.github.io/training-material/topics/galaxy-data-manipulation/tutorials/upload-rules/tutorial.html</a></p>
GLM2_modified and Results as used in Ma et al: Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2, Geosci. Model Dev., 2020
<p>Code modified GLM2, scripts and result as used in Ma et al 2019, Ma et al 2019, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-146</p>
Extracting interpretable rules with Bayesian Networks. A case study of intrinsic human hazardous properties of silver nanoforms for the Safety Dimension of Safe and Sustainable by design paradigm.
<p>Three different datasets: toxicological attributes in i) lung and ii) intestinal cell line along with system dependent features and iii) system independent pchem properties) were merged. Each row represents one set of experimental testing conditions and related system dependent nanodescriptors based on the exposure dose and NFs pre-treatment (for intestinal assessments). The system independent inputs are NF specific and independent of experimental conditions. Data is captured via FAIR principles where the reader can find the origin (institution) of each data, the responsible data creators (experimentalists), the raw measurements, the protocols followed and the instrumentations used for each experiment. .</p>
The Unofficial Guide on applying NCN Open Access rules to GitHub repositories.
<p><b>The Unofficial Guide on applying NCN Open Access rules to GitHub repositories.</b> <i>Some</i> HTML code can be used here.</p>
Catalytic Rules and Validation Results for "EzMechanism: An Automated Tool to Propose Catalytic Mechanisms of Enzyme Reactions"
<p>Dataset containing the "Rules of Enzyme Catalysis" as created during the development of EzMechanism and the validation results of the software. For more information see https://www.biorxiv.org/content/10.1101/2022.09.05.506575v1, and the M-CSA website in https://www.ebi.ac.uk/thornton-srv/m-csa/</p>
Extensions to Mining Framework Annotation Rules
<p>Framework usage is challenging because the requirements for the correctness are often implicit. We focus on making</p> <p>such requirements more explicit by association rule mining on the data from client projects that use a framework.</p> <p>We present an extension to an existing baseline method that does this. In particular, we examine alternative rule</p> <p>quality measures used in the ranking of association rules mined, and alternatives in the selection of client projects.</p> <p>Such alternatives are novel and have not been explored in the context of the baseline method. We evaluate the alternatives</p> <p>by comparing their results to those produced by the baseline method. More concretely, we base the comparison on their</p> <p>ranking of incorrect rules, and on their measurements for the Area Under Curve metric. We conclude that some of</p> <p>the evaluated quality measures outperform the baseline for the ranking and selection of rules. We also show that the</p> <p>selection of secondary client projects, adding some clients that do not directly use the framework of interest, matters.</p>
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 in Phylogenetic analysis and systematic position of two new species of the ant genus Crematogaster (Hymenoptera, Formicidae) from Southeast Asia
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 taxa using five genes (ArgK, CAD, LWRh, Top1, Wg) in a MrBayes analysis. Above node numbers indicate posterior probability. Data were partitioned by PartitionFinder v.1.1.1 and analyzed using a best fit model for each gene and codon position, with 10 million generations and a burn-in of 25 %. Area enclosed by dashed lines is enlarged on Fig. 2.
Rule based and information integration category learning
<p>The following dataset includes sessions from rats and humans learning and generalizing to Rule-based and Information Integration categories. Here, category exemplars are Gabor patches, which are circular stimuli that contain black and white gratings. Across exemplars, these gratings can change in their spatial frequency and orientation. For Rule-based tasks, only one stimulus dimension (i.e., spatial frequency or orientation) is category-relevant, and the other dimension varies randomly. For Information Integration tasks, both stimulus dimensions (i.e., spatial frequency and orientation) are category-relevant. On each learning trial, participants are presented with a category exemplar and must decide its category membership. Feedback guides learning. Rats are trained using a touchscreen apparatus, whereas humans are trained using a desktop computer. </p>
Test Data Generation from Business Rules
<p><strong>Overview of Data</strong></p> <p>The site includes data only for the two subjects: Ceu-pacific and JBilling. For both the subjects, the “<em>.model” shows the model created from the business rules obtained from respective websites, and “</em>_HighLevelTests.csv” shows the tests generated. Among csv files, we show tests generated by both BUSTER and Exhaust as well.</p> <p><strong>Paper Abstract</strong></p> <p>Test cases that drive an application under test via its graphical user interface (GUI) consist of sequences of steps that perform actions on, or verify the state of, the application user interface. Such tests can be hard to maintain, especially if they are not properly modularized—that is, common steps occur in many test cases, which can make test maintenance cumbersome and expensive. Performing modularization manually can take up considerable human effort. To address this, we present an automated approach for modularizing GUI test cases. Our approach consists of multiple phases. In the first phase, it analyzes individual test cases to partition test steps into candidate subroutines, based on how user-interface elements are accessed in the steps. This phase can analyze the test cases only or also leverage execution traces of the tests, which involves a cost-accuracy tradeoff. In the second phase, the technique compares candidate subroutines across test cases, and refines them to compute the final set of subroutines. In the last phase, it creates callable subroutines, with parameterized data and control flow, and refactors the original tests to call the subroutines with context-specific data and control parameters. Our empirical results, collected using open-source applications, illustrate the effectiveness of the approach.</p>
Tutorial Photonics Explorer Module 3 part 2: lenses, imaging rules, optical setups and telescopes
<p>Photonics Austria (PhAu) has conducted Teacher Training Programmes about Phoronics - the Photonics Explorer- in order to promote the potential of photonics to enliven physics lessons. This video is concerned with the topic polarisation and optical activity.</p> <p> </p>
Tutorial Photonics Explorer Module 3 part 1: lenses, imaging rules, optical setups and telescopes
<p>Photonics Austria (PhAu) has conducted Teacher Training Programmes about Photonics - the Photonics Explorer- in order to promote the potential of photonics to enliven physics lessons. This video tutorial contains several experiments designed to illustrate imaging equation and the laws of lenses.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.