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32 results for “Biomolecules”
Tuning the transport properties of biomolecules atom by atom.
<p>Data presented in the CECAM Conference: BioMolecular Electronics -- BIOMOLECTRO ( link: <a href="https://www.cecam.org/workshop-details/246">https://www.cecam.org/workshop-details/246</a>). </p> <p>Here we discuss how point mutations can result in abrupt changes of the electron transfer properties of proteins, and the findings are rationalized using a combination of Ab-Initio and Molecular dynamics simulations. This is intended to provide an overview of the results published in several peer-reviewed freely available papers:</p> <p>J. Am. Chem. Soc. 139, 15337-15346 (2017) [DOI: 10.1021/jacs.7b06130]<br> Phys. Chem. Chem. Phys. 20, 30392 (2018) [DOI:10.1039/C8CP06862C]<br> Biomolecules 9, 611 (2019) [DOI:10.3390/biom9100611]<br> Biomolecules 9, 506 (2019) [DOI: 10.3390/biom9090506]</p>
Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images
<p>Synthetic dataset used for validating MDSPACE method for analyzing continuous conformational variability of biomolecules in cryo-EM single particle images. A README file with the contents of the dataset is included. </p>
Fig. 3 in Trichilia (Meliaceae) plants: an important source of biomolecules with insecticidal properties
Fig. 3. Survival curves of Copitarsia decolora larvae fed on an artificial diet supplemented with extracts of Trichilia hirta bark at 100, 500, 1,000, and 1,500 ppm: (a) hexane, (b) acetone, (c) methanol, and (d) aqueous.
Fig. 4 in Trichilia (Meliaceae) plants: an important source of biomolecules with insecticidal properties
Fig. 4. Survival curve of Copitarsia decolora larvae fed on an artificial diet supplemented with hexane extract of Trichilia havanensis bark at 100, 500, 1,000, and 1,500 ppm.
Figure 11 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 11. The efficacy of RM of orange peels against human pathogenic bacteria. ****Extremely significant among compared groups at p <0.05 level. Test 1: RM of Valen-cia orange; Test 2: RM of Mandarin orange; Test 3: RM of African navel orange.
Figure 6 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 6. The structure of bioactive compounds of RM of African Navel orange peel (1) Limonene; (2) Hexadecanoic acid, 2-hydroxy-1- (hydroxymethyl) ethyl; (3) 9,12-Octadecadienoic acid (Z,Z)-, methyl ester; (4) Terephthalic acid, di(2-ethylhexyl) ester; (5) α-Sitosterol; (6) α-D-Glucopyranose, 4-O-α-D-galactopyranosyl-; (7) 2-Methoxy-4-vinylphenol; (8) Eugenol; (9) cis-Vaccenic acid; (10) De-canal; (11) Vitamin E; (12) Dichloroxylenol.
Figure 3 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 3. GC-MS chromatogram of the RMs of orange peels. (A) RM of Valencia orange; (B) RM of Mandarin orange; (C) RM of African Navel orange.
Figure 2 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 2. The morphology of orange fruits. (A) Valenica orange; (B) Madarin orange; (C) African Navel orange.
Figure 5 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 5. The structure of bioactive compounds of RM of Mandarin orange peel (1) Lim-onene; (2) Octadecanoic acid, 2-hydroxy-1- (hydroxymethyl) ethyl; (3) Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl) ethyl; (4) Tetradecanamide; (5) n-Hexadecanoic acid; (6) α-D-Mannofuranoside, 1-O-(10-undecenyl)-; (7) 3-Deoxy-d-mannoic lactone; (8) Desulpho-sinigrin; (9) 2-Methoxy-4-vinylphenol; (10) Decanal; (11) Vitamin E; (12) 1-Monolinoleoylglycerol trimethylsilyl ether.
Figure 4 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 4. The structure of bioactive compounds of RM of Valencia orange peel (1) Limonene; (2) 9-Octadecenamide, (Z)-; (3) Hexadecanoic acid, 2- hy-droxy-1-(hydroxymethyl)ethyl; (4) Octadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl; (5) Tetradecanamide; (6) Hexadecanamide; (7) Ethyl iso-allocholate; (8) Ethyl α-d-glucopyranoside; (9) d-Glycero-d-galacto-heptose; (10) α-Sitosterol; (11) Vitamin E; (12) 4H-1-Benzopyran-4-one, 2-(3,4-dimethoxyphenyl)-5,6,7-trimethoxy-.
Interaction of biomolecules with anatase, rutile and amorphous TiO2 surfaces: A molecular dynamics study / supplement
<ul> <li>S1 File - Short videos representing the interaction of the 6 different biomolecules (KGD, KRSR, LGD, LRSR, RGD and RSR) with the 3 different TiO<sub>2</sub> surface (anatase, amorphous and rutile).</li> <li>S2 File - A representative trajectory file of the LRSR peptide and amorphous TiO<sub>2</sub> surface MD simulation without the ions and water molecules.</li> <li>S3 File - Force-distance curve data for the binding energy calculations.</li> </ul>
Supplementary information: Specific versus Nonspecific Solvent Interactions of a Biomolecule in Water [Dataset]
<p><strong>Data availability</strong><strong> to the manuscript </strong><em>"</em>Specific versus Nonspecific Solvent Interactions of a Biomolecule in Water<em>"</em> by <strong>Lanhai He, Lukáš Tomaník, Sebastian Malerz, Florian Trinter, Sebastian Trippel, Michal Belina, Petr Slavíček, Bernd Winter, and Jochen Küpper</strong>, pubulished at<em> JPCL </em></p> <p>The dataset contains the complete x-ray photoelectron-emission spectra of indole<sub>aq</sub> in a liquid microjet. The uploaded files include:</p> <ul> <li>Valence band PES data (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0053VB.ibw">May02_0053VB.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0058VB_background.ibw">May02_0058VB_background.ibw</a>),</li> <li>core level PES data (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0045C1s.ibw">May02_0045C1s.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0049N1s.ibw">May02_0049N1s.ibw</a>),</li> <li>Auger PES pectra (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0052CAuger.ibw">May02_0052CAuger.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0057CAuger.ibw">May02_0057CAuger.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0056NAuger.ibw">May02_0056NAuger.ibw</a>)</li> <li>rough-scanned full spectra (<a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0046Full.ibw">May02_0046Full.ibw</a>, <a href="../api/files/eec96d6e-1972-463a-bc54-ee320bb2280e/May02_0047Full.ibw">May02_0047Full.ibw</a>).</li> </ul> <p>In addition, a python script (Read_ibw_file.py) has been uploaded, which can be used to read raw PES data files in .ibw format and export the intergraded PES data as a .txt file.</p>
Data for "CryoDRGN-ET: Deep reconstructing generative networks for visualizing dynamic biomolecules inside cells"
<p>Trained models weights, training parameters, sampled density maps, reconstructed density maps for featured classes, and plotting scripts are included for each of the following datasets and training runs:</p> <ul> <li><em>M. pneumoniae</em> ribosome, initial training run with all 18,466 particles, 1 tilt per particle</li> <li><em>M. pneumoniae</em> ribosome, training run with 16,655 filtered particles and 10 tilts per particle</li> <li><em>M. pneumoniae</em> ribosome, training run with 16,655 filtered particles and 41 tilts per particle</li> <li><em>S. cerevisiae </em>ribosome, initial training run with all 119,031 particles, 10 tilts per particle</li> <li><em>S. cerevisiae </em>ribosome, training run with 93,281 filtered particles, 10 tilts per particle</li> <li><em>S. cerevisiae</em> ribosome, training run with 30,657 particles in the non-rotated state, 10 tilts per particle</li> <li><em>S. cerevisiae </em>ribosome, training run with 62,624 particles in the rotated state, 10 tilts per particle</li> <li><em>S. cerevisiae </em>fatty acid synthase, initial training run with all 33,492 particles, 10 tilts per particle</li> <li><em>S. cerevisiae </em>fatty acid synthase, training run with all 5,239 filtered particles, 10 tilts per particle</li> </ul>
Figure 1 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 1. Schematic representation of experimental protocol.
Figure 9 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 9. FT-IR spectroscopy of RM of African Navel orange peel.
Figure 10 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 10. The dose-response curve of RM of orange peels against MCF-7 cells.
Figure 7 in Spectral characterization and biological evaluation of biomolecules from the peels of three orange fruits: a comparative study
Figure 7. FT-IR spectroscopy of RM of Valencia orange peel.
In-Droplet Electrophoretic Separation and Enrichment of Biomolecules
<p>Data underlying the figures in the publication “In-Droplet Electrophoretic Separation and Enrichment of Biomolecules”, published in <em>Anal. Chem.</em> <strong>2020</strong>, 92, 12, 8414–8421.</p> <p><a href="https://pubs.acs.org/doi/10.1021/acs.analchem.0c01044">https://pubs.acs.org/doi/10.1021/acs.analchem.0c01044</a></p> <p>Table of contents:</p> <p><strong>1. Figure 2 – Analyte Enrichement</strong>; Zip. archive containing (1) experimental videos of in-droplet separation for nine analytes at different electric fields, (2) the extracted fluorescence intensity values of the videos, and (3) the average enrichment factor.</p> <p><strong>2. Figure 3 – Electrode Length</strong>; Zip. archive containing (1) experimental videos of in-droplet separation when (a) HPMC, (b) buffers with different ionic strengths, and (c) different analyte concentrations are used, (2) the extracted fluorescence intensity values of the videos, and (3) the average enrichment factor.</p> <p><strong>3. Figure 4 – Extra Parameters</strong>; Zip. archive containing (1) experimental videos of in-droplet separation when (a) HPMC, (b) buffers with different ionic strengths, and (c) different analyte concentrations are used, (2) the extracted fluorescence intensity values of the videos, and (3) the average enrichment factor.</p> <p><strong>4. Figure 5 – Size and Velocity</strong>; Zip. archive containing (1) experimental videos of in-droplet separation for dichlorofluorescein at different droplet geometries and velocities, (2) the extracted fluorescence intensity values of the videos, and (3) the average enrichment factor.</p> <p><strong>5. Figure 6 – Mass Spectrometry</strong>; Zip. archive containing the mass spectrum of anodic and cathodic droplets after the in-droplet separation and splitting.</p> <p> </p> <p> </p>
Data from: Describing complex structure-function relationships in biomolecules at equilibrium
Open the record for dataset details and reuse information.
Data from: The importance of phytoplankton biomolecule availability for secondary production
The growth and reproduction of animals is affected by their access to resources. In aquatic ecosystems, the availability of essential biomolecules for filter-feeding zooplankton depends greatly on phytoplankton. Here, we analyzed the biochemical composition, i.e., the fatty acid, sterol and amino acid profiles and concentrations as well as protein, carbon, nitrogen, and phosphorus content of 17 phytoplankton monocultures representing the seven most abundant phytoplankton classes in boreal and sub-arctic lakes. To examine how the differences in the biochemical composition between phytoplankton classes affect their nutritional quality for consumers, we assessed the performance of Daphnia, on these diets. Furthermore, we defined the most important biomolecules regulating the somatic growth and reproduction of Daphnia, expecting that higher concentrations of certain biomolecules are needed for reproduction than for growth. Finally, we combined these results with phytoplankton field data from over 900 boreal and sub-arctic lakes in order to estimate whether the somatic growth of Daphnia is sterol-limited when the natural phytoplankton communities are cyanobacteria-dominated. Our analysis shows that Daphnia grows best with phytoplankton rich in sterols, ω-3 fatty acids, protein, and amino acids. Their reproduction follows food sterol and ω-3 concentration as well as C:P-ratio being two times higher in Daphnia feeding on cryptophytes than any other diet. Interestingly, we found that a high dietary ω-6 fatty acid concentration decreases both somatic growth and reproduction of Daphnia. When combined with phytoplankton community composition field data, our results indicate that zooplankton is constantly limited by sterols in lakes dominated by cyanobacteria (≥40% of total phytoplankton biomass), and that the absence of cryptophytes can severely hinder zooplankton production in nature.
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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.