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.
356
datasets available to search
ShareScore release 0.9.0
Dataset results
356 results for “In silico”
In silico prediction of high-resolution Hi-C interaction matrices (part II)
<p>The uploaded files are source datasets for the HiC-Reg approach. HiC-Reg is a regression based method that predict contact counts from one-dimensional regulatory signals such as epigenetic marks and regulatory protein binding. See more details here (<a href="https://github.com/Roy-lab/HiC-Reg">https://github.com/Roy-lab/HiC-Reg</a>). There are a total of six files in this dataset: Data.tgz, Gm12878.tgz, Hmec.tgz, K562.tgz, Huvec.tgz and Nhek.tgz. The Data.tgz include predictions and other downstream analysis such as feature importance analysis, significant interaction calling, and data files for select figures. The Gm12878.tgz, K562.tgz, Huvec.tgz, Hmec.tgz and Nhek.tgz contain trained models, predictions, feature files for two chromosomes for in each cell line.</p> <p>This is part II of the dataset which contains K562.tgz and Huvec.tgz.</p>
Fig. 2 in Response to enantiomers of (Z3Z9)-6,7-epoxy-octadecadiene, sex pheromone component of Ectropis obliqua Prout (Lepidoptera: Geometridae): electroantennagram test, field trapping, and in silico study
Fig. 2. Field trial of Ectropis obliqua Prout. (A) Water pan trap; (B) male moths captured.
In-silico CID MS/MS Spectra for the Blood Exposome Compounds
<p>In-silico spectra (+ve mode, M+H) were generated for the Blood Exposome Compounds ( BloodExposome.org ) using the ICEBERG model, re-trained using MONA/GNPS/NIST2020 spectra. </p> <p>Disclaimer: These are simulated spectra so they should be used with cautions to annotate compounds in LC-HRMS datasets. </p> <p>Files are available in the NIST MSP format and the NIST Library (lib2nist conversion)</p>
Data accompanying "In silico analysis of the profilaggrin sequence indicates alterations in the stability, degradation route, and intracellular protein fate in filaggrin null mutation carriers" article.
<p>This research was supported by the National Science Centre, Poland, grant PRELUDIUM number 2021/41/N/NZ1/03473 to NS, National Science Centre, Poland, grant SONATA BIS number 2019/34/E/NZ6/00354 to DG-O, as well as POIR.04.04.00-00-21FA/16–00 grant, carried out within the First TEAM programme of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund (awarded to DG-O). WP was supported by the National Science Centre, Poland, grant SONATA-BIS number 2021/42/E/NZ1/00190. SB is supported by a Wellcome Trust Senior Research Fellowship (220875/Z/20/Z).</p>
Comparative genomics of Helotiales (Leotiomycetes) and in silico analysis of temperature adaptations of plant-associated genes
<p><span>Table S1: Genome assembly size and quality for every species in this study; </span></p> <p><span>Table S2: Genome annotation counts for P450, virulence factors, effectors, and CAZy genes and their temperature adaptation.</span></p>
SGLT2-Inhibition reverts urinary peptide changes associated with severe COVID-19: an in-silico proof-of-principle of proteomics-based drug repurposing
<p>Severe COVID-19 is reflected by significant changes in urine peptides. Based on this observation, a clinical test predicting COVID-19 severity, CoV50, was developed and registered as in vitro diagnostic in Germany. We have hypothesized that molecular changes displayed by CoV50, likely reflective of endothelial damage, may be reversed by specific drugs. Such an impact by a drug could indicate potential benefits in the context of COVID-19. To test this hypothesis, urinary peptide data from patients without COVID-19 prior to and after drug treatment were collected from the human urinary proteome database. The drugs chosen were selected based on availability of sufficient number of participants in the dataset (n>20) and potential value of drug therapies in the treatment of COVID-19 based on reports in the literature. In these participants without COVID-19, spironolactone did not demonstrate a significant impact on CoV50 scoring. Empagliflozin treatment resulted in a significant change in CoV50 scoring, indicative of a potential therapeutic benefit. The study serves as a proof-of-principle for a drug repurposing approach based on human urinary peptide signatures. The results support the initiation of a randomised control trial testing a potential positive effect of empagliflozin for severe COVID-19, possibly via endothelial protective mechanisms.</p>
Dataset II related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP3P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7342311</p>
Dataset III related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP4P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7341954</p>
An in silico approach to determine inter-subunit affinities in human septin complexes
<p>The septins are a conserved family of filament-forming guanine nucleotide binding proteins, often named the fourth component of the cytoskeleton. Correctly assembled septin structures are required for essential intracellular processes such as cytokinesis, vesicular transport, polarity establishment, and cellular adhesion. Septins structurally belong to the P-Loop NTPases but they do not mediate signals to effectors through GTP binding and hydrolysis. GTP binding and hydrolysis are believed to contribute to septin complex integrity, but biochemical approaches addressing this topic are hampered by the stability of septin complexes after recombinant expression and the lack of nucleotide-depleted complexes. To complement this limitation, we used a molecular dynamics based approach to determine inter-subunit free binding energies in available human septin dimer structures and in their apo forms, which we generated <em>in silico</em>. The nucleotide in the GTPase active subunits SEPT2 and SEPT7, but not in SEPT6, was identified as a stabilizing element in the G interface as it is coordinated at its ribose ring to conserved amino acids. Removal of GDP from SEPT2 and SEPT7 results in flipping of a conserved Arg residue and disruption of an extensive hydrogen bond network in the septin unique element, concomitant with a decreased inter-subunit affinity.</p>
Optimization Framework for Temporal Interference Current Tibial Nerve Stimulation in Tibial Nerves based on In-Silico Studies
<p><strong>Online Resource 1:</strong> All MR-based 3D models and cross-sections. n = 29.</p> <p> </p> <p><strong>Online Resource 2:</strong> Comparison of changes in electrode pairs according to anatomical differences (independent sample t-test for Online Resource 2, *p<0.0001)</p> <p>When Electrode opt TI was applied, the model in which the combination of electrodes was changed relative to Parallel opt TI was referred to as the Change group, and the model that was unaltered was called the Non-change group. In the case of the Change group, PR values increased in Electrode opt compared with those in the Parallel opt group. When comparing the ratio of nerve depth to the total length of the model section, we confirmed the Change group exhibited a smaller ratio. Since the sample size of each group was different, the difference of average in the PR value of each group was evaluated using an independent sample t-test. Purple dots present raw data. Mean and standard deviation of the changes are shown in black.</p>
Solution, Crystal and in-Silico Structures of the Organometallic Vitamin B12-Derivative Acetylcobalamin and of its Novel Rhodium-Analogue Acetylrhodibalamin
<p>Cartesian coordinates of all calculated structures discussed in the paper.</p>
Dataset I related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>WaterMaps results related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the WaterMap results for each structure.</li> </ul> <p><em>Additional notes: there is a typo in the 5v90 file name (it is the 5v9o structure).</em></p> <p>Related datasets: 10.5281/zenodo.7341954 and 10.5281/zenodo.7342311</p>
In silico prediction and biophysical validation of novel 14-3-3σ homodimer stabilizers
<p>this dataset is related to "In silico prediction and biophysical validation of novel 14-3-3σ homodimer stabilizers" Aljabal G., Teh, A.-H., Yap B.K.</p>
In silico spatial transcriptomic editing at single-cell resolution
<p>The data for training the GAN (Inversion) model and reproduce the results reported in the paper </p>
Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease
<p>In the present research, we propose a novel approach, termed the Machine Learning (ML)-Based q-RASAR (quantitative read-across structure-activity relationship) method, for the identification of potential multi-target inhibitors against AD. The q-RASAR effectively combines the principles of both read-across and 2D QSAR approaches. As a result, it is imperative to take into account similarity-related aspects in the process of developing q-RASAR models. In this investigation, we have implemented ML-based q-RASAR modeling against seven major targets (AChE, BuChE, BACE1, 5-HT6, CDK-5 enzymes, Amyloid precursor protein, and Tau aggregation) of AD using the initially selected features in 2D QSAR models for the identifications of novel multitarget inhibitors. The models were individually used to check the applicability domain of a pool of 407270 natural products (NPs) obtained from the COCONUT database (<a href="https://coconut.naturalproducts.net/download">https://coconut.naturalproducts.net/download</a>) and provided prioritized compounds for experimental detection of their performance as anti-Alzheimer's drugs. Furthermore, we have also developed the q-RASAAR (quantitative read-across structure-activity-activity relationship) and selectivity-based q-RASAR models to explore the most important features contributing to the dual inhibition against the respective targets. Furthermore, we have applied seven distinct machine learning algorithms to enhance the predictive abilities of q-RASAR and q-RASAAR models. Moreover, we have also developed the univariate q-RASAR model, with the RA function as the primary independent variable. Moreover, molecular docking experiments have been conducted to gain insights into the atomic-level molecular interactions between ligands and enzymes. These observations are then juxtaposed with the structural characteristics obtained from models that elucidate the mechanistic aspects of binding events. These proposed models may serve as valuable tools for pinpointing crucial molecular attributes when designing potential drugs for Alzheimer's therapy through the rational design of multi-target inhibitors.</p>
Direct synthesis, characterization, in vitro and in silico studies of simple chalcones as potential antimicrobial and antileishmanial agents
Open the record for dataset details and reuse information.
COVID-19 patient data from a study in Singapore curated for input into an in silico infection model
Open the record for dataset details and reuse information.
A comparison between mouse, in silico, and robot odor plume navigation reveals advantages of mouse odor-tracking
Open the record for dataset details and reuse information.
An in-silico generated library of DMED derivatized FAHFA lipids (Data Supplement)
<p>Data supplement for publication "An in-silico generated library of DMED derivatized FAHFA lipids (Data Supplement)" (2020)<br> Jun Ding(1,2), Tobias Kind(1), Quan-Fei Zhu(2), Yu Wang(2), Jing-Wen Yan(2), Oliver Fiehn(1), Yu-Qi Feng(2,3)<br> (1) West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, California 95616, United States<br> (2) Department of Chemistry, Wuhan University, Wuhan, 430072, PR China<br> (3) Frontier Science Center for Immunology and Metabolism, Wuhan University, Wuhan, 430072, PR China</p> <p><br> Content:<br> 1) arabidopsis-chromatograms: UPLC-MSMS of DMED derivatized FAHFAs<br> 2) decoy: Decoy search of DMED library against NIST17 library<br> 3) developement: XLS template sheet for development (can be used to adjust or create new library)<br> 4) MSP-spectra: spectra in NIST MSP format (use with MS-Dial or NIST MS Search)<br> 5) NIST-Format: NIST17 compatible DMED-FAHFA library (use with NIST MS Search)<br> 6) Orbitrap-reference-spectra: DMED-FAHFA authentic reference spectra in Thermo RAW format (CID)<br> 7) MSP-reference-standards: DMED-FAHFA authentic in NIST MSP format (for searching NIST MS-Search)<br> 8) structures: Compound mol files and SMILES files</p> <p>Version 1.0<br> January 13 2020</p>
Dataset related to publication "In silico evaluation of the thermal stress induced by MRI switched gradient fields in patients with metallic hip implant"
<p>The datasets reported in the figures of the article "In silico evaluation of the thermal stress induced by MRI switched gradient fields in patients with metallic hip implant", published on Phys. Med. Biol. 64 245006, 2019.</p> <p>This work focuses on the in silico evaluation of the energy deposed by MRI switched gradient fields<br> in bulk metallic implants and the consequent temperature increase in the surrounding tissues. The results show that the gradient coils can generate local increases of temperature up to some kelvin when acting without radiofrequency excitation. Hence, their contribution in general should not be disregarded when evaluating patients’ safety.</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.