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127 results for “Self-assembly”
Photomorphogenesis for Robot Self-assembly: Adaptivity, Collective Decision-making, and Self-repair
<p>Self-assembly in biological systems is an inspiration for engineered large-scale multi-modular systems with desirable characteristics, such as robustness, scalability, and adaptivity. Previous works have shown that simple mobile robots can be used to emulate and study self-assembly behaviors. However, many of these studies were restricted to rather static and inflexible aggregations in predefined shapes, and were limited in adaptivity compared to that observed in nature. We propose a photomorphogenesis approach for robots using our vascular morphogenesis model---a light-stimuli directed method for multi-robot self-assembly inspired by the tissue growth of trees. Robots in the role of `leaves' collect a virtual resource that is proportional to a real, sensed environmental feature. This resource is then shared throughout the whole robot aggregate and determines where it grows or shrinks as a reaction to the dynamic environment. In our approach the robots use supplemental bioinspired models to collectively select a seed robot to decide who starts to self-assemble (and where), or to assemble static aggregations. The robots then use our vascular morphogenesis model to aggregate in a directed way preferring bright areas, hence resembling natural phototropism (growth towards light). In this assembly, they are adaptive and able to react to a dynamic environment by collectively and autonomously rearranging the aggregate, discarding outdated parts and growing new ones. In representative experiments, the self-assembling robots collectively make rational decisions on where to grow. Cutting off parts of the aggregate triggers a self-organizing repair process in the robots, and the parts regrow. All these capabilities of adaptivity, collective decision-making, and self-repair in our robot self-assembly originate directly from self-organized behavior of the vascular morphogenesis model. Our approach opens up opportunities for self-assembly with reconfiguration on short time-scales with high adaptivity of dynamic forms and structures.</p>
Supporting data for: "Hybrid Computational-Experimental Data-Driven Design of Self-Assembling π-Conjugated Peptides"
<p>This repository contains supporting data and code for the paper titled "Hybrid Computational-Experimental Data-Driven Design of Self-Assembling π-Conjugated Peptides" by Kirill Shmilovich, Sayak Subhra Panda, Anna Stouffer, John D. Tovar, and Andrew L. Ferguson.</p>
Molecular trajectories and general MD files: Molecular insights on confined water in the nanochannels of self-assembled ionic liquid crystal
<p>This repository includes the MD simulation dataset of self-assembled ionic liquid crystal reported in the article of <a href="https://doi.org/10.1126/sciadv.abf0669"><em>Sci. Adv.</em> <strong>7</strong>, eabf0669 (2021) [DOI: 10.1126/sciadv.abf0669]</a>. The chemical structure of ionic liquid crystal is described in <a href="https://advances.sciencemag.org/content/advances/7/31/eabf0669/F1.large.jpg">Fig. 1A</a>. The cation involves an ionic moiety of <em>N</em>-methyl-<em>N</em>,<em>N</em>,<em>N</em>-triethylammonium group, and the terminals of the two alkyl chains are conjugated dienes. The anion is tetrafluoroborate BF<sub>4</sub>. The molecular and atomic-group charges of cation and anion are shown in the topology files named "ilc-oplsdft.itp" and "bf4-oplsdft.itp", respectively. The TIP3P and TIP4P/2005 models are employed for water molecules. After the careful equilibration process, the production MD was performed for 50 ns under the <em>NPT</em> condition at each composition. This dataset provides the configuration, topology, and general MD input files of Gromacs for all the states and models of bicontinuous and columnar structures obtained in the article. The 3D view of bicontinuous and columnar structures can be available in <a href="https://advances.sciencemag.org/content/advances/7/31/eabf0669/F2.large.jpg">Fig. 2</a>. The attached edr and log files are energy and general outputs of the MD simulation generated in our environment, and the xtc file is a trajectory output generated with a time interval of 20 ps.</p>
Data for publication "Lipid oxidation controls peptide self-assembly near membranes through a surface attraction mechanism"
<p>The data provided refer to our published article:</p> <p>T. John,* S. Piantavigna, T. J. A. Dealey, B. Abel, H. J. Risselada, L. L. Martin*, Lipid oxidation controls peptide self-assembly near<br>membranes through a surface attraction mechanism, Chem. Sci. 14 (2023), 3730-3741. <a href="https://doi.org/10.1039/d3sc00159h">https://doi.org/10.1039/d3sc00159h</a>.</p>
Self-assembly and structure of a clathrin-independent AP-1:Arf1 tubular membrane coat
Open the record for dataset details and reuse information.
Palmitic Acid Sophorolipid Biosurfactant: From Self-Assembled Fibrillar Network (SAFiN) To Hydrogels with Fast Recovery
<p>Data are zipped using Winrar 5.40 version</p> <p>Folder "Figures": it contains the images of Figure 1 through 6. Images are available as datasets readable with Origin software (any version) or QTplot software.</p> <p>Folder "Figure 4": it contains images corresponding to Figure 4 and Figure S5. Images can be read nd processed with Fiji software. Folder also contains ascii files corresponding to the plots.</p> <p>File "Figures": this is the powerpoint file containing all composed images of the main text and Supporting Information. Plots can be opened with Origin software.</p> <p> </p>
Improved small-angle x-ray scattering of nanoparticle self-assembly using a cell with a flat liquid surface
<p>One important way of forming nanostructures entails the assembly of nanoparticle (NP) monolayers at a liquid surface. Probing this assembly of 11.8-nm-diameter iron oxide NPs by small-angle x-ray scattering (SAXS) is studied using cells with walls at angles designed to significantly reduce the size of the meniscus. This enables the collection of much larger signals in the SAXS images of ordered arrays of NPs at liquid/gas interfaces, as is needed for kinetics studies and x-ray exposure minimization, along with the observation of extremely high degrees of order. Meniscus flattening and improved signal collection are demonstrated for the assembly of ordered arrays of iron oxide NP monolayers at a diethylene glycol surface.</p>
Robot Self-Assembly as Adaptive Growth Process
<p>Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions.In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We explain how our approach will be extended to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.</p>
Data regarding "Development and evaluation of RADA-PDGF2 self-assembling peptide hydrogel for enhanced skin wound healing"
<p>Raw data for data published in Development and evaluation of RADA-PDGF2 self-assembling peptide hydrogel for enhanced skin wound healing, Front. Pharmacol. Sec. Experimental Pharmacology and Drug Discovery Volume 14 - 2023 | <a href="https://doi.org/10.3389/fphar.2023.1293647">doi: 10.3389/fphar.2023.1293647</a></p>
Window[1]resorcin[3]arenes: A novel macrocycle able to self-assemble to a catalytically active hexameric cage
<p>open data for paper Window[1]resorcin[3]arenes: A novel macrocycle able to self-assemble to a catalytically active hexameric cage</p>
Data supporting "Stereocontrolled Self-Assembly of a Helicate-Bridged CuI12L4 Cage That Emits Circularly-Polarized Light"
<p>This repository contains the set of data to reproduce the computational results shown in "Stereocontrolled Self-Assembly of a Helicate-Bridged CuI12L4 Cage That Emits Circularly-Polarized Light" published on Journal of the American Chemical Society (DOI: to be assigned).</p>
An aperiodic chiral tiling by topological molecular self-assembly
<p>Data used in preparation of publication 'An aperiodic chiral tiling by topological molecular self-assembly'</p>
Data from the paper "Porphyrin central metal ion driven self-assembling in heterogeneous ZnTPP – CoTPP films grown on Fe(001)-p(1 × 1)O"
Open the record for dataset details and reuse information.
Comparing natural hydrogels to self-assembling peptides in spinal cord injury treatment: a systematic review
<p><strong>Abstract</strong></p> <p><em><strong>Background:</strong></em><em> </em>In many cases, central nervous system (CNS) injury is unchanging due to the absence of neuronal regeneration and repair capabilities.<strong> </strong>In recent years, regenerative medicine, and especially hydrogels, have reached a significant amount of attention for their promising results for the treatment of spinal cord injury (SCI) currently considered permanent. Hydrogels are categorized based on their foundation: synthetic, natural, and combination. The objective of this study was to compare the properties and efficacy of commonly used hydrogels, like collagen, and other natural peptides with synthetic self-assembling peptide hydrogels in the treatment of SCI. </p> <p><em><strong>Methods</strong></em><em>:</em><em> </em>Articles were searched in PubMed, Scopus, Web of Science, and Embase. All studies from 1985 until January 2020 were included in the primary search. Eligible articles were included based on the following criteria: administering hydrogels (both natural and synthetic) for SCI treatment, soley foucsing on spinal cord injury treatment, and published in a peer-reviewd journal. Data surronding xonal regeneration, revascularization, elasticity, drug delivery efficacy, and porosity were extracted.</p> <p><em><strong>Results:</strong></em> A total of 24 articles were included for full-text review and data extraction. There were only one experimental study directly comparing Collagen I (as natural hydorgel) and PEG (as synthetic hydrogels) in an <em>in vitro </em>setting. The included study suggested PEG’s cell behavior is more expectable in the injury site, which makes it a more reliable scaffold.</p> <p><em><strong>Conclusions:</strong></em> There is limited research comparing and evaluating both types of natural and self-assembling peptides (SAPs) in the same animal or <em>in vitro</em> study, despite its importance. Although we assume that the remodeling of natural scaffolds may lead to a stable hydrogel, there was not a definitive conclusion that synthetic hydrogels are more beneficial than natural hydrogels in neuronal regeneration.</p>
Research data supporting: "Classifying soft self-assembled materials via unsupervised machine learning of defects"
<p>Research data supporting: "Classifying soft self-assembled materials via unsupervised machine learning of defects".</p> <p>The root folder contains 5 folders:</p> <ol> <li>FIBERS</li> <li>MEMBRANES_and_MICELLES</li> <li>NANOPARTICLES</li> <li>COMPARISON</li> <li>paper_images</li> </ol> <p>The folders 1. to 3. contain the data for every soft-matters architecture used to produce the results discussed in the main paper. Each of these folders contain additional sub-fordels: TRAJ, SOAP, PCA, CLUSTERING, containing the files discussed in the main paper.</p> <p>Folder 4. contains the data of the comparison between different classes of materials (SOAP, PCA, and CLUSTERING sub-folders).</p> <p>Folder 5. contains the images that are showed in the main paper and in the Supporting Information.</p>
Data set for the replication package of the paper "Simulations of DNA-origami self-assembly reveal design-dependent nucleation barriers"
<p>Data set for the replication package of the paper "Simulations of DNA-origami self-assembly reveal design-dependent nucleation barriers".</p>
Data for "Tetramine Aspect Ratio and Flexibility Determine Framework Symmetry for Zn8L6 Self-Assembled Structures"
<p>In the following subdirectories are the input and outputs of cage and face analysis for:</p> <p>Published DOI: <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/anie.202217987">10.1002/anie.202217987 </a></p> <p>Code: <a href="https://github.com/andrewtarzia/sca_cage_assembler/tree/cubism-production">sca_cage_assembler</a></p> <p>Previously uploaded in 10.5281/zenodo.8432296 and <a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer">https://github.com/andrewtarzia/citable_data</a></p> <p>NOTES:</p> <ul> <li>the naming convention differs from manuscript:</li> </ul> <table> <tbody> <tr> <th>manuscript tetra-aniline</th> <th>computational label</th> <th>xtal-label</th> </tr> <tr> <td>A</td> <td>5</td> <td>370</td> </tr> <tr> <td>B</td> <td>16</td> <td>326</td> </tr> <tr> <td>C</td> <td>12</td> <td>235</td> </tr> <tr> <td>D</td> <td>3</td> <td>301</td> </tr> <tr> <td>E</td> <td>8</td> <td>257</td> </tr> <tr> <td>F</td> <td>2</td> <td>354</td> </tr> </tbody> </table> <ul> <li>computational labels are often preceded by `quad2_` or `cl1_quad2_`</li> <li>much of the analysis was not used in the manuscript but remains part of the accumulated data</li> </ul> <p> </p> <p>cage_library directory:</p> <ul> <li>_CS.json: information on all cages in the set of diastereomers - properties and whether they optimized successfully.</li> <li>_ligand_measures.json: information on the ligand associated with a set of cage diastereomers.</li> <li>_measures.json: represenets a cleaned up collation of all measures the diastereomers made from a given ligand</li> <li>C_NAME_optc.mol: optimized (at xTB level) structure of each cage.</li> <li>set_dft_run directory contains the input and output of the CP2K optimisations of one set of diastereomers</li> </ul> <p>complex_library directory:</p> <ul> <li>contains the optimised structures of both complexes</li> </ul> <p>ligand_library directory:</p> <ul> <li>contains `_opt.mol` input ligand structures for cage construction</li> <li>for cap, the input was provided manually in `manual/` directory</li> <li>in `face_analysis` directory: <ul> <li>contains manual_complex directory, with necessary input for face construction</li> <li>_long_properties.json files contains the measurements for the named face (in file name)</li> <li>_long_lopt.mol files contain the optimised structure of the named face, on which analysis was performed</li> <li>`long` corresponds to the longer restricted optimization discussed in the SI.</li> </ul> </li> </ul> <p>xray_structures directory:</p> <ul> <li>analysis directory: <ul> <li>contains input .pdb files for xray structure (as single molecules) used in analysis</li> <li>contains `all_xray_csv_data.csv`, which has all data needed on xray structures.</li> </ul> </li> </ul>
Molecular dynamics trajectories and portable binary run files for the self-assembly of heparin and amyloid-β(16-22) with the ProMPT forcefield
<h1>About this repository</h1> <p>Self-assembly simulations of heparin and amyloid-β(16-22) were performed at various numbers of peptides (<em>N_pep</em>), number of heparin molecules (<em>N_hep</em>), degrees of polymerization of heparin (<em>hep_dp</em>) and rigidity factors (<em>rig_f</em>) for heparin. This repository contains one folder per system, characterized by a combination of four system variables: <em>N_pep</em>, <em>N_hep</em>, <em>hep_dp</em> and <em>rig_f. </em></p> <p>The simulations were performed on the GROMACS 2019.4 molecular dynamics engine, with the ProMPT forcefield for coarse-grained molecular dynamics. Four independent trials: <em>trial_A</em>, <em>trial_B</em>, <em>trial_C</em> and <em>trial_D</em> were performed per system, each with different starting velocities. Each trial was run for 3000 ns.</p> <h1>Contents</h1> <h2><code>> heparin_abeta_trajectories.zip</code></h2> <p>The repository contains the zip file <code>heparin_abeta_trajectories.zip</code> with 13 folders named according to the convention,<code> "{<em>N_pep</em>}pep_{<em>N_hep</em>}hep_dp{<em>hep_dp</em>}_{<em>rig_f</em>}xRigid"</code>. For example, data for the system consisting of 16 peptides (<em>N_pep</em>), 1 heparin (<em>N_hep</em>), 18 monosaccharides in length (<em>hep_dp</em>) with a rigidity factor of 100 (<em>rig_f</em>) would be stored in the directory <code>16pep_1hep_dp18_100xRigid/</code>.</p> <p>If the system did not contain heparin, <em>N_hep, hep_dp</em> and <em>rig_f</em> were set to 0 by default. For example, data for the system consisting of 16 peptides (<em>N_pep</em>) and no heparin would be stored in the directory <code>16pep_0hep_dp0_0xRigid/</code>.</p> <p>A directory such as <code>16pep_1hep_dp18_100xRigid/</code> will have the following contents:</p> <ul> <li><code><strong>solute_only.ndx</strong></code><br>Contains an index group for solute molecules (peptides and/or heparin) only.</li> <li><code><strong>trial_A/</strong></code> <ul> <li><code><strong>md.tpr</strong></code> <br>Portable run file with which the current trajectory was generated. This file may be used to reproduce the trajectory as well.</li> <li><code><strong>solute_only.cluster_center.xtc </strong></code><br>A gromacs trajectory containing only the solute molecules (peptides and/or heparin), centered with the gromacs tool <em>gmx trjconv</em></li> <li><code><strong>solute_only.tpr </strong></code><br>A gromacs portable binary input file containing data for the solute molecules (peptides and/or heparin) only, generated with the <em>gmx convert-tpr</em> tool.<br>This file may be used during analysis of the solute_only.cluster_center.xtc trajectory.</li> </ul> </li> <li><code><strong>trial_B/</strong></code><br>contents same as <code><strong>trial_A/</strong></code></li> <li><strong><code>trial_C/</code><br></strong>contents same as <code><strong>trial_A/</strong></code></li> <li><strong><code>trial_D/</code><br></strong>contents same as <code><strong>trial_A/</strong></code></li> </ul> <h2><code>> psf_files_for_VMD_visualization.zip</code></h2> <p>This zip file contains thirteen .psf files, one per system, that can be used in accord with <code>solute_only.cluster_center.xtc </code>files to visualize trajectories on the Visual Molecular Dynamics (VMD) software.</p> <p><strong>Please seek out the associated publication for essential context on these trajectories. </strong></p> <p><strong>To access the source files with which these simulations were set-up, and a brief tutorial, see: </strong><a href="https://github.com/suhasgotla/heparin_amyloid_self-assembly">https://github.com/suhasgotla/heparin_amyloid_self-assembly</a></p>
Dataset: Design and Self-Assembly of Second-Generation Dendrimer-Like Block Copolymers
<p>This dataset contains processed data (data) and plotting scripts (plots) of the simulation related to the paper: </p> <p><br>F. Hartmann, R. Dockhorn, S. Pusse, B.-J. Niebuur, M. Koch, T. Kraus, A. Schießer, B. N. Balzer, and M. Gallei, <br>"Design and Self-Assembly of Second-Generation Dendrimer-Like Block Copolymers"<br>Macromolecules <strong>2024</strong>; DOI: <a href="https://doi.org/10.1021/acs.macromol.4c00944">10.1021/acs.macromol.4c00944</a></p> <p>Please consult the ReadMe.md in the zip.</p>
Data for "Diastereoselective Self-Assembly of Low-Symmetry PdnL2n Nanocages through Coordination-Sphere Engineering"
<p>In the following subdirectories are the input and outputs of cage and face analysis for:</p> <p>Published DOI: 10.1002/anie.202315451</p> <p>Previously uploaded in <span>10.5281/zenodo.8432296 and </span><a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer"><span>https://github.com/andrewtarzia/citable_data</span></a></p> <p>Note that all scripts are self-contained. There is some duplicate code between them.</p> scripts: <ul> <li> build_cages.py: <ul> <li>Builds the Pd2L4 cage models.</li> <li>Some manual optimisation is assumed.</li> <li>Paths for xTB and GULP are set to my machine.</li> <li>All outputs are relative to working directory.</li> </ul> </li> <li> build_dwall_triangles.py: <ul> <li>Builds the Pd3L6 cage models.</li> <li>Some manual optimisation is assumed.</li> <li>Paths for xTB and GULP are set to my machine.</li> <li>All outputs are relative to working directory.</li> </ul> </li> </ul>
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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)
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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.