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1,294 results for “reactions”
SONAR -- experimental redox potentials for organic compounds undergoing 2-electron/2-proton transfer reactions
<p>reference data for the demo-compounds used as input for predicting redox potentials by a trained model </p><p>The file</p><ul><li>lists redox potentials and oxidized/reduced form for organic molecules undergoing a two-electron/two-proton reduction reaction (M + 2 e- + 2 H+ --> MH2)</li><li>contains data for 25 organic compounds compiled from various sources in literature</li><li>uses "|" as a separator</li><li>column names and explanations<ol><li><strong>ID</strong>: abbreviated trivial names e.g. for labelling</li><li><strong>orig redox potential [V]:</strong> original values reported in respective reference</li><li><strong>solvent</strong>: total formula, water (H2O) throughout</li><li><strong>pH</strong>: pH value of electrolyte solution. If not reported, inferred from the concentration of supporting electrolyte</li><li><strong>supporting_electrolyte</strong>: if spefified: total formula, if available; concentration</li><li><strong>SMILES_ox</strong>: molecular structures encoded as (manually assigned) SMILES strings for the oxidized species (M)</li><li><strong>SMILES_red</strong>: molecular structures encoded as (manually assigned) SMILES strings for the reduced species (MH2)</li><li><strong>ref_electrode:</strong> reference electrode the originally reported half cell potential refers to. If not specified, RHE was used as default</li><li><strong>redox potential vs SHE [V]</strong>:<ul><li>In case of missing information, reversible hydrogen electrode (RHE at pH = 0) was assumed, which corresponds to SHE</li><li>In case of conflicting entries (SHE and pH != 0), we assumed the pH should be accounted for and replaced "RHE" as reference electrode instead of "SHE". "NHE" was treated like "RHE".</li><li>In case the reference electrode was other than SHE, NHE or RHE, a respective offset was added. This was the case once for Ag/AgCl (assuming saturated solution, offset = 0.210, see respective reference)</li><li>Finally, the potential values were transferred to SHE according to: E(SHE) = E(RHE) + 0.05913 * pH</li><li>CAVEAT: Lacking information about individual pKa values, no other correction was made.</li></ul></li><li><strong>reference</strong>: orginal source</li></ol></li></ul>
Adverse Drug Reaction (ADR) Text Dataset
<p>This repository contains text data and code related to the identification and clustering of Adverse Drug Reactions (ADR) using Sentence-BERT (S-BERT) embeddings and the SS-DBSCAN clustering algorithm. The dataset includes both labeled and unlabeled patient reports extracted from the publicly available MIMIC-III database.</p> <p>The labeled data has been manually annotated to distinguish between ADR and non-ADR cases. The unlabeled dataset is used for unsupervised clustering experiments, particularly to assess high-dimensional data clustering performance.</p> <p>New in This Version:<br>- Added Jupyter Notebook: `mimic-5k_PCA_tSNE_clustering.ipynb`<br>- Included detailed `README_ADR_Clustering_Task.txt` with step-by-step instructions to reproduce clustering results<br>- Explained how to scale experiments from 1,000 to full dataset size</p>
Dataset of "Tracking high-valent surface iron species in the oxygen evolution reaction on cobalt iron (oxy)hydroxides"
<p>Dataset of the paper entitled "Tracking high-valent surface iron species in the oxygen evolution reaction on cobalt iron (oxy)hydroxides"</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>
Alkali-silica reaction. A multi-disciplinary approach. Supplementary Materials: Movie file.
<p>Movie file being part of the Supplementary Materials document of the manuscript with the same title and submitted to the <a href="https://letters.rilem.net/index.php/rilem">RILEM Technical Letters</a>.</p>
Dataset supporting the paper "Power discontinuity and shift of the energy onset of a molecular de-bromination reaction induced by hot-electron tunneling. Nanoscale 13, 15215 (2021)"
<p>Dataset corresponding to theoretical calculations in the paper "Power discontinuity and shift of the energy onset of a molecular de-bromination reaction induced by hot-electron tunneling. Nanoscale 13, 15215 (2021)". DOI: <a href="https://doi.org/10.1039/D1NR04229G">10.1039/D1NR04229G</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <ul> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).<br> </li> </ul>
Data Set for the Journal Article "Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis"
<p>This dataset includes the XYZ structures of the centroids of all compounds found. Charge and multiplicity are given in the comment line of each XYZ file.</p>
Automatic affective reactions to physical effort
<p>Dataset for the study titled "automatic affective responses during physical effort: a virtual reality study".</p> <p>This dataset includes:</p> <p><strong>1) A codebook (including the name of the main variables)</strong></p> <p>--> "code_book_affect_effort.xlsx"</p> <p><strong>2) Behavioral data (raw)</strong></p> <p>--> in the folder "data_ps_VR". </p> <p>The raw data are added for transparency, but are not necessary to run the models. </p> <p><strong>3) Self-reported data (raw)</strong></p> <p>--> "20220112_VR_expe.xlsx"</p> <p>--> "20220112_VR_pilot.xlsx"</p> <p>The raw data are added for transparency, but are not necessary to run the models. </p> <p><strong>4) clean data ready to used for the statistical analyses</strong></p> <p>--> "data_VR_all_clean.csv".</p> <p>This clean data are produced by the R script. These data included the self-reported and the behavioral measures. </p> <p><strong>5) R script for the data management (i.e., from the raw data to data ready to be analyzed)</strong></p> <p>--> "data_management_effort.R" to create the dataset (return the file: "data_VR_all_clean.RData")</p> <p><strong>6) R script for the models tested</strong></p> <p>--> "Data_mixed_effects_models.R" for the models tested in the paper</p> <p><strong>7) The video of the experiment</strong></p>
Can a knee sleeve influence ground reaction forces and knee joint power during a step-down hop in participants following ACL reconstruction? Discrete and time-continuous datasets
<p>Using a cross-over design, we estimated GRF and knee kinematics and kinetics during a step-down hop for 30 participants (age 26.1 [SD 6.7] years, 14 women) following ACL reconstruction (median 16 months post-surgery) with and without wearing a knee sleeve. In a subsequent randomised clinical trial, participants in the ‘Sleeve Group’ (n=9) then wore the sleeve for 6 weeks at least 1 hour daily, while a ‘Control Group’ (n=9) did not wear the sleeve. Statistical parametric mapping (SPM) was used to compare (1) GRF trajectories in the three planes as well as knee joint power between three conditions at baseline (uninjured side, unsleeved injured and sleeved injured side); (2) within-participant changes for GRF and knee joint power trajectories from baseline to follow-up between groups. We also compared discrete peak GRFs and power, rate of (vertical) force development, and mean knee joint power in the first 5% of stance phase. Time-continuous and discrete data are included in this dataset.</p>
Raw Data - High resolution electrochemical additive manufacturing of microstructured active materials: case study of MoSx as a catalyst for the hydrogen evolution reaction
<p>The dataset contains raw data that complements the article:</p> <p>High resolution electrochemical additive manufacturing of microstructured active materials: Case study of MoSx as a catalyst for the hydrogen evolution reaction, J. Mater. Chem. A, 2021, 9, 22072-22081.</p> <p>C. Iffelsberger and M. Pumera*</p> <p>https://doi.org/10.1039/D1TA05581J</p> <p>Related to the MSCA Project: 888797 LoCatSpot</p>
Research data for "Phase transitions in NiO during the Oxygen Evolution Reaction assessed via electrochromic phenomena through operando UV-Vis spectroscopy"
<p>This is the dataset supporting the publication "Phase transitions in NiO during the Oxygen Evolution Reaction assessed via electrochromic phenomena through operando UV-Vis spectroscopy", published by the authors in Electrochimica Acta (2024), 144626 under <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.electacta.2024.144626" target="_blank" rel="noreferrer noopener">doi.org/10.1016/j.electacta.2024.144626</a>.</p> <p>The data is ordered according to Figure numbers in the main manuscript and the electronic supplementary information.</p>
Dataset for 'Low Molar Mass Cyclic Poly(L-lactide)s: Separate Transesterification Reactions of Cycles and Linear Chains in the Solid State'
<p>This set contains all MALDI and DSC data used for publication 'Low Molar Mass Cyclic Poly(L-lactide)s: Separate Transesterification Reactions of Cycles and Linear Chains in the Solid State' in RSC Soft Matter, DOI: 10.1039/D4SM00567H.</p>
RetroTransformDB - a dataset of transforms (retrosynthetic reactions)
<p>Here we present a dataset of transforms compiled and coded in SMIRKS line notation by us. The collection is comprised of more than 100 records each including id, reactions name, SMIRKS linear notation, target functional group and transform type. All SMIRKS transforms were tested syntactically, semantically and from chemical point of view in different software platforms. SMIRKS notations are written with explicit H atoms, therefore it is expected that the used software will apply the SMIRKS transforms against molecules with explicit H atoms.</p>
Beyond Textual Issues: Understanding the Usage and Impact of GitHub Reactions
<p>Recently, GitHub introduced a new social feature, named reactions, which are pictorial characters similar to the emoji symbols widely used nowadays in text-based communications. Particularly, GitHub users can use a set of such symbols to react to issues and pull requests. However, little is known about the real usage and benefits of GitHub reactions. In this paper, we analyze the reactions provided by developers to more than 2.5 million issues and 9.7 million issue comments, in order to answer an extensive list of ten research questions about the usage and adoption of reactions. We show that reactions are being increasingly used by open-source developers. Moreover, we also found that issues with reactions usually take more time to be closed and have longer discussions.</p> <p>This dataset contains the data used in the paper "Beyond Textual Issues: Understanding the Usage and Impact of GitHub Reactions", accepted for SBES 2019.</p>
Collection of UV/Vis spectra acquired while monitoring reaction progress of thymidine phosphorolysis with varying reactant concentrations
<p>This data set accompanies the publication "Dynamic modelling of phosphorolytic cleavage catalyzed by pyrimidine-nucleoside phosphorylase" in MDPI Processes, and is a collection of UV/vis spectra used for monitoring of reaction progress under various experimental conditions.</p> <p>The monitored reaction is thymidine phosphorolysis, catalyzed by an enzyme (EC 2.4.2.2). Phosphate and thymidine concentrations are in the range of 2–80 mM and 0.8–5 mM, respectively, and final enzyme concentration in the range of 12.5–50 µg/mL. The recorded data represents time courses over 24 hours for 48 reaction conditions.</p> <p>This collection also contains the documentation of all work done in the laboratory to achieve this data (provenance in the form of the complete lab journal).</p>
Databases with structures used for "Improving the Activity of M-N4 Catalysts for the Oxygen Reduction Reaction by Electrolyte Adsorption"
<p>DFT optimised structures used for the paper "Improving the Activity of M-N<sub>4</sub> Catalysts for the Oxygen Reduction Reaction by Electrolyte Adsorption". There is a separate database for structures with Cr, Mn, Fe and Co as the central metal atom in the M-N4 motif, and one with the molecular references. The structures can be retrieved using the Atomic Simulation Environment (ASE).</p>
High Accuracy Barrier Heights, Enthalpies, and Rate Coefficients for Chemical Reactions
<p>This Zenodo repository contains the data presented in Spiekermann, K. A.; Pattanaik, L.; Green, W. H.* <a href="https://www.nature.com/articles/s41597-022-01529-6">High Accuracy Barrier Heights, Enthalpies, and Rate Coefficients for Chemical Reactions</a>, Sci. Data 9, 417, (2022). We recommend people refer to this dataset as RDB7 i.e. a diverse reaction database whose transition states contain up to 7 heavy atoms.</p> <p>Atom-mapped SMILES, barrier heights, reaction enthalpies, and Reaction Mechanism Generator (RMG) reaction family for each reaction are listed in the comma-separated values files <strong><em>b97d3.csv</em></strong>, <strong><em>wb97xd3.csv</em></strong>, <strong><em>ccsdtf12_dz.csv</em></strong>, and<em> <strong>ccsdtf12_tz.csv</strong></em>. <em><strong>ccsdtf12_dz_individual_heats_of_formation.csv</strong></em> containing the individual heats of formation for each stable species (i.e., reactant and product). The values in all of these files are in kcal/mol. Q-Chem output files from the reoptimized products are provided for 16,302 reactions at B97-D3/def2-mSVP and for 11,926 reactions at ωB97X-D3/def2-TZVP level of theory. For convenience, these also include the original log files for the reactant, transition state, and non-reoptimized products from Grambow et al. (10.5281/zenodo.3715478) since they were used to calculate barrier heights, enthalpies, and rate constants in this work. The numbering of reaction indices matches that from the originally published dataset to facilitate easy comparison. MOLPRO output files from the single point calculations are provided for 11,926 reactions at the CCSD(T)-F12/cc-pVDZ-F12 level of theory as well as for the 15 validation reactions run at CCSD(T)-F12/cc-pVTZ-F12. The raw log files for all calculations are stored in <strong><em>b97d3.tar.gz</em></strong>, <strong><em>wb97xd3.tar.gz</em></strong>, <strong><em>ccsdtf12_dz.tar.gz</em></strong>, and <strong><em>ccsdtf12_tz.tar.gz</em></strong>. Each archive contains a separate folder for each reaction, which contains log files for the reactant, transition state, and product/s. The Q-Chem log files contain the output from a geometry optimization and harmonic vibrational analysis while the MOLPRO log files contain output from an energy calculation. Transition state theory rate constants, fitted Arrhenius parameters, and average percentage error between the calculated and fitted rate constants can be found for the rigid reactions in <strong><em>ccsdtf12_dz_rigid.csv</em></strong>. The list of 50 temperatures (K) used during Arrhenius fitting is provided in <strong><em>arkane_temperatures.csv</em></strong>, and the raw Arkane outputs are provided in <strong><em>ccsdtf12_dz_rigid.tar.gz</em></strong>.</p> <p>The improvement from fitting bond additivity corrections at B97-D3/def2-mSVP, ωB97X-D3/def2-TZVP, CCSD(T)-F12/cc-pVDZ-F12//ωB97X-D3/def2-TZVP, and CCSD(T)-F12/cc-pVTZ-F12//ωB97X-D3/def2-TZVP is shown in <strong><em>b97d3_def2msvp_BAC.csv</em></strong>, <strong><em>wb97xd3_def2tzvp_BAC.csv</em></strong>, <strong><em>ccsdtf12_ccpvdzf12__wb97xd3_def2tzvp_BAC.csv</em></strong>, and <strong><em>ccsdtf12_ccpvtzf12__wb97xd3_def2tzvp_BAC.csv</em></strong> respectively. The files contain the experimental and calculated enthalpies for the reference species from the RMG-database used for fitting. The correction values are publicly stored on the RMG-database GitHub on the AEC_BAC branch, though they are also provided in <strong><em>fitted_corrections.pkl</em></strong> for convenience. Further validation of the BACs at the double zeta level was done by comparing to experimental values from the Pedley set since over half of these molecules were not in the RMG-database training set used for fitting. The comparison is shown in <strong><em>ccsdtf12_dz_vs_Pedley_experimental.csv</em></strong>.</p> <p> </p>
Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplification and flow cytometry
<p>This dataset contains the raw data that were used for the publication entitled, "Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplificaiton and flow cytometry" published in Biosensors and Bioelectronics on 5 October 2024.</p>
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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.