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ShareScore release 0.9.0
Dataset results
1,084 results for “substrate”
Plasticity in AAA+ proteases reveals substrate specificity niches
GEO Series GSE166765. Caulobacter vibrioides NA1000. 9 samples. Type: Expression profiling by high throughput sequencing.
Comparative analysis of the Trichoderma reesei transcriptome during growth on the cellulase inducing substrates wheat straw and lactose
GEO Series GSE46155. Trichoderma reesei; Trichoderma reesei QM9414. 3 samples. Type: Expression profiling by array.
E. coli evolution to alternating substrate conditions
GEO Series GSE97944. Escherichia coli str. K-12 substr. MG1655. 23 samples. Type: Expression profiling by high throughput sequencing.
Caveolin-1 modulates mechanotransduction responses to substrate stiffness through actin-dependent control of YAP
GEO Series GSE120514. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide analysis of cellular SMD or NMD substrates that regulated by Upf1 or PNRC2 in HeLa cell
GEO Series GSE26781. Homo sapiens. 6 samples. Type: Expression profiling by array.
Genome-wide analysis of Human Upf1, SMG5, SMG7 and PNRC2 downregulated substrates in HeLa cell
GEO Series GSE34876. Homo sapiens. 10 samples. Type: Expression profiling by array.
Inactivation of the LKB1 substrate AMPK accelerates lung adenocarcinoma and leads to immune evasion.
GEO Series GSE175479. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Substrate Specificity of the TRAMP Nuclear Surveillance Complexes
GEO Series GSE135526. Saccharomyces cerevisiae. 38 samples. Type: Other.
RNA-seq study of HUVEC/MSC cell growth on micropatterned Si-TiB2 substrates
GEO Series GSE135824. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide analysis of miRNA-targeted cellular NMD substrates in HeLa cell
GEO Series GSE16170. Homo sapiens. 6 samples. Type: Expression profiling by array.
Enzyme-inhibitor complexes of unithiol with metallo-beta-lactamases and a NDM1-meropenem enzyme-substrate complex
<p>Gemetry configurations obtained at the QM(PBE0-D3/(6-31G**+LANL2DZ(Zn)))/MM(CHARMM) level of theory.</p> <p> </p>
Simulation data in "Haloalkenyl Imidoyl Halides as Multifacial Substrates Breaking Limits in the Stereoselective Synthesis of N-Alkenyl Compounds"
<p>Collection of the Gaussian log files of the optimization and the resulting optimized structures obtained in the work: "Haloalkenyl Imidoyl Halides as Multifacial Substrates Breaking Limits in the Stereoselective Synthesis of N-Alkenyl Compounds".</p>
Data from: Insect adhesion on rough surfaces: analysis of adhesive contact of smooth and hairy pads on transparent micro-structured substrates
Insect climbing footpads are able to adhere to rough surfaces, but the details of this capability are still unclear. To overcome experimental limitations of randomly rough, opaque surfaces, we fabricated transparent test substrates containing square arrays of 1.4 µm diameter pillars, with variable height (0.5 and 1.4 µm) and spacing (from 3 to 22 µm). Smooth pads of cockroaches (Nauphoeta cinerea) made partial contact (limited to the tops of the structures) for the two densest arrays of tall pillars, but full contact (touching the substrate in between pillars) for larger spacings. The transition from partial to full contact was accompanied by a sharp increase in shear forces. Tests on hairy pads of dock beetles (Gastrophysa viridula) showed that setae adhered between pillars for larger spacings, but pads were equally unable to make full contact on the densest arrays. The beetles' shear forces similarly decreased for denser arrays, but also for short pillars and with a more gradual transition. These observations can be explained by simple contact models derived for soft uniform materials (smooth pads) or thin flat plates (hairy-pad spatulae). Our results show that microstructured substrates are powerful tools to reveal adaptations of natural adhesives for rough surfaces.
Supplementary material S31: Averaged spectrograms for the full collection of jolting pulses on each substrate.
<p>A series of spectrograms to demonstrate the filtering parameters chosen for each collection of jolt pulses to improve the alignment process. A selection of pulses from each substrate collection were averaged to produce each panel. This number differed based upon the number of pulses that showcased clarity (petri-dish = 40, honeycomb = 8, brood-comb = 40). Background frequencies were filtered as follows: 19 kHz high-pass (a), 500 Hz high-pass and 12 – 19 kHz band-stop (b), 500-2500 Hz bandpass (c), leaving only the frequencies where strong signal occurs. This then produces cleaner accelerometer data for improved scrutiny of the pulses to identify similarities within each substrate. The colour-coding of each spectrogram is not relevant for this figure as it serves only the purpose of substantiating the filtering choices. </p>
Supplementary material S25: Time course of the loudest Varroa pulse on each substrate compared to that of Varroa walking behaviour.
<p>Time course of a <em>Varroa </em>jolting pulse and walking accelerometer traces. A 0.5 second accelerometer extract of mite walking behaviour (black) is here compared to a 0.5 second extract of accelerometer data containing the loudest pulse on each substrate (red).</p>
Neural Network for Determination of the Substrate Activation in Enzymes
<p>1. Multiwfn_lap.sh -- a Linux script to run calculation of the Laplacian of electron density grid in the plain of a nucleophile atom and a carbonyl group. </p> <p>2. lapZero150DPI.py - a Python script for visualization of the 2D Laplacian of the electron density map</p> <p>3. crop_image.py - a Python script that crops the image </p> <p>4. 2500_crop_dataset_MolInf.ipynb - a Python notebook that trains the CNN with the dataset_crop_2500-MolInf </p> <p>5. dataset_crop_2500-MolInf.7z - a dataset to train the CNN</p> <p>6. model_crop_2500-MolInf.h5 - trained CNN, ready for utilization </p> <p>7. validation_datasets.zip -- an archive that includes additional datasets for the neural network validation (complexes of the Mpro with substrates containing Ser, Thr and Pro at P2 and a complex of the NDM-1 and imipenem)</p>
Acyl-CoA dehydrogenases involved in fatty acid degradation of Pseudomonas aeruginosa: substrate specificity
<p>MD trajectories raw data </p>
Molecular Mechanism of Substrate Transport and Dynamics of the Cyanobacterial Bicarbonate Transporter BicA
<p>Molecular Mechanism of Substrate Transport and Dynamics of the Cyanobacterial Bicarbonate Transporter BicA</p>
[PART 3] How to fit a round peg in a square hole: Pseudomonas aeruginosa acyl-CoA dehydrogenases and structure-guided inversion of their substrate specificity.
<p>Metadynamics data for the PaFADE1</p> <p>1320- PaFadE1 8PNS noCoA +FAD + G129M A295E - metadynamics, 10A3 OPLS4 T3P<br>1321- PaFadE1 8PNS noCoA +FAD WT - metadynamics, 10A3 OPLS4 T3P</p>
[PART 2] How to fit a round peg in a square hole: Pseudomonas aeruginosa acyl-CoA dehydrogenases and structure-guided inversion of their substrate specificity.
<p>Classical unbiased molecular dynamics dataset generated with Maestro 2023.4</p> <p>1320- PaFadE1 8PNS noCoA +FAD + G129M A295E, 10A3 OPLS4 T3P<br>1321- PaFadE1 8PNS noCoA +FAD WT, 10A3 OPLS4 T3P</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.