Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
21,281
datasets available to search
ShareScore release 0.9.0
Dataset results
21,281 results for “molecular”
RNA-seq dataset for Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
<p>Data to be used along with <a href="https://github.com/neelroop/asd-development-coexpression-2013">code</a> from 2013 paper that was originally on a site hosted at UCLA, but may no longer be accessible.</p>
Online Appendix for PhD Thesis Titled "Dissecting Causal Relationships and Molecular Mechanisms in Disease using Genetic Risk Profiles"
<p>This repository contains 23 tables and two figures, which are too big to be included in the Appendix section of my thesis document.</p> <p>The second version includes additional summary statistics of metabolite-PGS associations which can be found at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas/.</p>
Molecular dynamics simulation of SpoIVFB:Pro-SigmaK complex (replicate 1)
<p>Replicate simulation 1/4</p> <p>Found here are all files needed to reproduce or visualize the results of molecular dynamics simulation of the SpoIVFB intramembrane protease bound to the transcription factor Pro-sigmaK. The protein complex was embedded in a POPE_POPG_DAG_CL bilayer using CHARMM-GUI and simulated using OpenMM. The README file is a C-shell script that will run equilibration and 250ns of unrestrained simulation. </p> <p>Individual output (.out) and trajectory (.dcd) files are provided for each checkpoint of the simulation. A combined trajectory containing 250 ns of unrestrained simulation is also provided (combined_250ns_traj.dcd). Together with the step5_input.psf file, this combined dcd file can be used with common software such as VMD to visualize the molecular dynamics trajectory.</p>
Unstable Crystallographic & Molecular Structures for Machine Learning of System Energies
<div> <div> <div> <p>Extended QM9 (E-QM9) includes diverse sizes (i.e. number of atoms) and compositions of OoE molecules, through extending a subset of QM9 with OoE versions of 10k of its molecules.</p> <p>Periodic crystals (PC) allows learning regular bonding patterns that arise in periodic structures by repeating the base crystal lattice. We use the Face-Centred Cubic (fcc) Bravais lattice for aluminium (Al) and copper (Cu) crystals.</p> <p>Crystal Growth (CG) contains growing crystals of increasing size and complexity. Starting from a basic fcc crystal seed of 14 atoms, new systems are generated by iteratively placing atoms at a random location on the surface of the growing crystal following its lattice pattern, with sizes ranging from 15 to 114 atoms. We use 20 random seeds for each atom type, thus creating 40 varied Al and Cu crystal growths and 4,000 stable systems. As a result, for a given crystal size and composition (atom type), there are 20 samples with differently located atoms. CG enables experi- menting with large scale atomic interactions in non-regular sys- tems, and enables evaluation of an ML method’s ability to learn how each atom contributes to the final potential energy.</p> <p>In all datasets, OoE systems are obtained by compressing/dilating all interatomic distances (i.e. isometrically) at regular intervals within 90-150% of stable geometry, which we refer to as ‘scaling’. In other words, scaling is applied to the coordinates of all atoms within the system. At each geometry, the ground-truth potential energy is calculated using CP2K7’s DFT.</p> </div> </div> </div>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% POPS with Na+ counterions using ff99 ions
<p><strong>System: </strong>Symmetric bilayer of anionic POPS (palmitoyl-oleoyl-phosphatidylserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of POPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion model:</strong> Amber ff99 [J Åqvist <em>J. Phys. Chem.</em> <strong>94</strong> 8021 (1990)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup: </strong>2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 298 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Molecular dynamics simulation trajectory of an anionic lipid bilayer: 100 mol% DOPS with Na+ counterions using Joung-Cheetham Ions
<p><strong>System: </strong>Symmetric bilayer of anionic DOPS (1,2-Dioleoyl-<em>sn</em>-glycero-3-phosphoserine 100 mol-%) lipids with sodium (Na<sup>+</sup>) counter ions.</p> <p><strong>Number of DOPS:</strong> 128.<br> <strong>Number of Na<sup>+</sup>-ions:</strong> 128.<br> <strong>Number of waters:</strong> 4480.</p> <p><strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].</p> <p><strong>Ion models: </strong>Joung–Cheatham [IS Joung, TE Cheatham III <em>J. Phys. Chem. B </em><strong>112</strong> 9020 (2008)].</p> <p><strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].</p> <p><strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].</p> <p><strong>Number of independent repeats per setup: </strong>2.<br> <strong>Trajectory lengths per repeat:</strong> 400 ns + 100 ns.<br> <strong>Previously equilibrated for:</strong> 100 ns.<br> <strong>Sampling rate:</strong> every 10 ps.</p> <p><strong>Time integration step:</strong> 2 fs.</p> <p><strong>Thermodynamic ensemble:</strong> NpT. <br> <strong>Temperature coupling:</strong> 'Langevin' at T = 303 K.<br> <strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.</p> <p><strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br> <strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.</p> <p><strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].</p> <p><strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).</p>
Accompnaying Dataset for: Chemical Heredity as Group Selection at the Molecular Level
<p>Accompnaying Dataset for: Chemical Heredity as Group Selection at the Molecular Level. File descriptions are provided in the Appendix of [Markovitch, Witkowski and Virgo; Chemical Heredity as Group Selection at the Molecular Level, arXiv (2018)] (https://arxiv.org/abs/1802.08024).</p>
Molecular Models and Wave Function Definitions for Models A-G of the [2Fe]F Cluster in FeFe-hydrogenase Maturase Enzyme HydF
<p>The dataset contains all relevant atomic positional coordinates for 2Fe-cluster models, and electronic wave function data (using formatted Gaussian checkpoint files) as described in the related publication (see citation below).</p> <p>The version 2.0 contains additional models for [2Fe-2S] cluster linked [2Fe]F constructs.</p> <p>The top folder contains "analysis.xlsx" electronic spreadsheet that summarizes all the numerical results for absolute and relative electronic energy values, internal coordinates, calculated and scaled vibrational frequencies for diatomic stretching modes. The details of developing scaled quantum forcefields as a function of level of theory and model composition are also given.<br> The schematic structural definitions are given in the "models.pdf" file and keys for abbreviations are provided in "symbols.txt" file.<br> </p>
A molecular dynamics study of adenylyl cyclase: the impact of ATP and G-protein binding
<p>Adenylyl cyclases (ACs) catalyze the biosynthesis of cyclic adenosine monophosphate (cAMP) from adenosine triphosphate (ATP) and play an important role in many signal transduction pathways. The enzymatic activity of ACs is carefully controlled by a variety of molecules, including G-protein subunits that can both stimulate and inhibit cAMP production. Using homology models developed from existing structural data, we have carried out all-atom, microsecond-scale molecular dynamics simulations on the AC5 isoform of adenylyl cyclase and on its complexes with ATP and with the stimulatory G-protein subunit Gsα. The results show that both ATP and Gsα binding have significant effects on the structure and flexibility of adenylyl cyclase. New data on ATP bound to AC5 in the absence of Gsα notably help to explain how Gsα binding enhances enzyme activity and could aid product release. Simulations also suggest a possible coupling between ATP binding and interactions with the inhibitory G-protein subunit Gαi.</p> <p>All-atom molecular dynamics simulations were performed with the GROMACS 5 package. The simulations were carried out in an NTP ensemble at a temperature of 310 K and a pressure of 1 bar using a Bussi velocity-rescaling thermostat (t<sub>T</sub> = 1 ps) and a Parrinello-Rahman barostat (t<sub>P</sub> = 1 ps). We provide the atomistic trajectories of the following 6 systems after 400 ns of equilibration:</p> <ul> <li>AC5</li> <li>AC5+ATP</li> <li>AC5+Gsα</li> <li>AC5+ATP+Gsα</li> <li>AC5+FOK</li> <li>AC5+ATP+FOK</li> </ul> <p>In each trajectory, the frames are saved each 20 ps.</p>
Method Classification of Open Access INTACT Molecular Interaction data.
<p>Simple classification data derived from open access papers indexed in the INTACT database (https://www.ebi.ac.uk/intact/downloads) based on PSI-MI25 codes for interaction detection methods or participant detection methods based on the subfigure caption text. <br> <br> intact_records_and_captions_complete.tsv - This file links available text of subfigure captions to PSI-MI25 codes for the interaction detection method and participant detection method. </p> <p>evidx_run_file.txt - This file provides execution codes for the 'EvidX' machine learning text classifier (https://github.com/SciKnowEngine/evidX/releases/tag/v0.1.0)</p> <p> </p> <p> </p> <p> </p>
Assessment of mutation probabilities of KRAS G12 missense mutants and their long-time scale dynamics by atomistic molecular simulations and Markov state modeling: Datasets.
<p>Datasets related to the publication [1].<br> Including:</p> <ul> <li>KRAS G12X mutations derived from COSMIC v.79 [http://cancer.sanger.ac.uk/cosmic/] (KRAS_G12X_mut_COSMICv79..xlsx)</li> <li>RMSFs (300-2000ns) of GDP-systems (300_2000rmsf_GDP_systems_RAW_AVG_SE.xlsx)</li> <li>RMSFs (300-2000ns) of GTP-systems (300_2000RMSF_GTP_systems_RAW_AVG_SE.xlsx)</li> <li>PyInteraph analysis data for salt-bridges and hydrophobic clusters (.dat files for each system in the PyInteraph_data.zip-file)</li> <li>Backbone trajectories for each system (residues 4-164; frames for every 1ns). Last number (e.g. _1) refers to the replica of the simulated system.</li> <li>backbone_4-164.gro/.pdb/.tpr -files (resid 4-164) </li> </ul> <p><br> [1] Pantsar T et al. Assessment of mutation probabilities of KRAS G12 missense mutants and their long-time scale dynamics by atomistic molecular simulations and Markov state modeling. <em>PLoS Comput Biol Submitted</em> (2018)</p>
Catalog of laboratory parameters for the Lyman and Werner bands of molecular hydrogen
<p>Catalog of laboratory parameters for the Lyman and Werner bands of molecular hydrogen based on the compilation of Malec et al. (2010). The wavelength values are partly updated to the measurements from Table 11 and 12 in Bailly et al. (2010). The values for the oscillator strength f and the damping constant gamma are re-calculated following (Morton 2003).</p> <p> </p>
Dataset of molecular docking data of neuropeptides to acid-sensing ion channels
<p>The *.dock4 files are result files of molecular docking with the software Autodock Vina to the human ASIC1a closed state model, of the peptides FRRFa and KNFLRFa (FRRF.dock4, KNFLRF.dock4) that can be visualized with structure viewing programs such as UCSF Chimera on the closed ASIC1a model file (closed_ASIC_pH7.4.pdb). The file “FRRF_KNFLRF_complexes.pdb” provides the structures of selected poses of FRRFa and KNFLRFa peptides docked to the closed conformation of the human ASIC1a model.</p>
The molecular architecture of the yeast spindle pole body core determined by Bayesian integrative modeling
<p>This repository pertains to the molecular architecture of the yeast spindle pole body (SPB), the structural and functional equivalent of the metazoan centrosome. Data from in vivo FRET and yeast two-hybrid, along with SAXS, X-ray crystallography, and electron microscopy were integrated by a Bayesian structure modeling approach.</p> <p>For more information about how to reproduce this modeling, see the <a href="https://salilab.org/spb/">Sali lab website</a> or the README file.</p>
Supporting data for "Quantifying the Strength of a Salt Bridge by Neutron Scattering and Molecular Dynamics"
<p>Supporting data for the following published paper: Mason, Jungwirth, Duboué-Dijon, 2019, JPhysChemLett, 10, 3254-3259</p> <p>Contains both data from neutron scattering measurements and input simulation files necessary for reproduction of the work.</p>
Molecular dynamics simulations of the interaction of the quadruple mutant human CYP2J2 (R111A + R117A + R382A + R446A) with arachidonic acid (POSES 1-3)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_quadmut_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the quadruple R111A + R117A+R382A+R446A) mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p>
Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R117A) with arachidonic acid (POSES 5-6)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR117A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Molecular dynamics simulations of the interaction of wild type human CYP2J2 with DHA (POSES 1-4)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_wt_CYP2J2_DHA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of docosahexaenoic acid (DHA) in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 4 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 3 and 4)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_wt_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 4 times, hence there are 4 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Homology modelling, molecular docking and molecular dynamics simulations of wild type and mutant human CYP2J2 with three polyunsaturated fatty acids
<p>This is the "parent" repository for the Data Note : "­Molecular dynamics simulations of the interaction of wild type and mutant human CYP2J2 with polyunsaturated fatty acids" by Abelak, Bishop-Bailey and Nobeli.</p> <p>It contains a document (<strong>Abelak_etal_Methods.pdf</strong>) describing the methods used to produce the data here and the data in all repositories supplementing it.</p> <p>It also contains a shell script (<strong>create_sim4_repeats.sh</strong>) that is typical of those used to set up the molecular dynamics simulations in the repositories supplementing this one.</p> <p>Finally, it contains the results of the homology modelling and docking simulations that formed the starting points for the molecular dynamics simulations in this study.</p> <p>Description of files in this dataset:</p> <p><strong>C2J2_min3_mod_noH.pdb</strong> : Homology model of the wild type CYP2J2 built from an alignment of templates with PDB ids: 1SUO, 2P85, 3EBS and 1Z10.</p> <p><strong>docking_wild_type_C2J2.zip</strong> : Nine docked poses of arachidonic acid docked to the homology model of the wild type CYP2J2.</p> <p>Details of how this data was produced is available in the Abelak_etal_Methods.docx document.</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.