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598 results for “Small molecules”
Radiation Damage in Small Molecule Crystallography - Benchmark experiment
<p>Benchmark experiment performed at the UK National Crystallography Service facility in Southampton.</p>
Thermodynamics of small-molecule insertion across membrane mixtures: Insight from the potential of mean force
<p>This repository contains input data referenced in supporting information of the paper titled "Thermodynamics of small-molecule insertion across membrane mixtures: Insight from the potential of mean force" by Alessia Centi, Arghya Dutta, Sapun H. Parekh, and Tristan Bereau.</p>
Data-Error Scaling Laws in Machine Learning on Combinatorial Mutation-prone Sets: Proteins and Small Molecules
<div> </div> <h3>Data</h3> <p> This folder contains the raw data used during this work. `out_seq_total.txt` contains information on the sequences used (mutations, number of mutations, etc.). `output_energies_total.txt` contains the response variables, which include: a) unrelaxed EvoEF energies (peptides); b) relaxed EvoEF energies (peptides, `*_repaired.txt`); and c) solvation energies (molecules). 3D structures are provided in `.xyz` format in the subfolder `XYZ` (molecules).</p> <div> <div><strong>GB1 dataset</strong></div> <br> <div>The GB1 dataset was <strong>not</strong> generated by us (https://doi.org/10.48550/arXiv.2405.05167). If you use the GB1 dataset, please cite the original paper:</div> <br> <div>Wu, N. C., Dai, L., Olson, C. A., Lloyd-Smith, J. O., & Sun, R. (2016). <em>Adaptation in protein fitness landscapes is facilitated by indirect paths. </em><strong>eLife</strong>, 5:e16965. doi:10.7554/eLife.16965</div> </div> <h3>Results</h3> <p>This folder contains the results (outputs) of the ML models trained using the provided scripts (see github repository). Such results are incuded in the form of `.npy` files. To load the files please include the option `allow_pickle=True`.</p> <p> Each `.npy` file contains the following keys:<br> * `initial_parameters`: script inputs.<br> * `d_encoder`: encoder used (not always included).<br> * `ns_train`: number of training points used for the LCs (rounded, integers).<br> * `ns_train_float`: number of training points used for the LCs (not rounded, float).<br> * `ns_train_norm`: number of training points used for the LCs (normalized, float).<br> * `res`: test MAEs.<br> * `res_tot`: (train,validation,test) MAEs.<br> * `res_tot_mut`: (train,validation,test) MAEs sorted by mutation number.<br> * `l_opt`: optimal kernel length used during the test.<br> * `ls`: kernel lengths used for grid search.<br> * `idx_seeds`: indices used to reshuffle the data. If one want to rebild the initial order use `np.argsort(idx_seeds)`.<br> * `alpha_opt`: optimal regression parameters used to calculate the test error. To sort the data use `alpha_opt[i][ii][np.argsort(idx_seeds[ii,0:arg_train_max].astype(int)[:ns_train[i]]`. Where `i` is the replicate number (0-99) and ii is the idex in the LC.<br> * `valid_errs`: validation error (MAE) calculated for each point in the hyperparameter (kernel scale) optimisation.<br> * `test_errs`: test error (MAE) calculated for each point in the hyperparameter (kernel scale) optimisation.</p>
Characterizing diffusion-controlled release of small-molecules using quantitative MRI: Application to orthopedic infection - dataset
<p>Dataset for paper submitted to Scientific Reports titled "Characterizing diffusion-controlled release of small-molecules using quantitative MRI: Application to orthopedic infection"</p>
Dataset for the paper "Aqueous Redox Flow Batteries: Small Organic Molecules for the Positive Electrolyte Species", ChemSusChem, DOI: 10.1002/cssc.202300303
<p>The data in this spreadsheet was used to produce the figures in the paper</p> <p>Authors:Christopher G. Cannon, Dr. Peter A. A. Klusener, Prof. Nigel P. Brandon, Prof. Anthony R. J. Kucernak</p> <p>Title:Aqueous Redox Flow Batteries: Small Organic Molecules for the Positive Electrolyte Species</p> <p>Journal:ChemSusChem</p> <p>DOI:10.1002/cssc.202300303</p> <p>Please cite the above reference if you wish to use this data</p>
Fig. 8 in HSQC-based small molecule accurate recognition technology discovery of diverse cytotoxic sesquiterpenoids from Elephantopus tomentosus L. and structural revision of molephantins A and B
Fig. 8. (A)The structural revision of molephantin A and B (B) Observed inconsistent NMR data of 9–12.
Fig. 1 in HSQC-based small molecule accurate recognition technology discovery of diverse cytotoxic sesquiterpenoids from Elephantopus tomentosus L. and structural revision of molephantins A and B
Fig. 1. SMART based prioritization of the isolation and the SMART result for Fr. B2 (top 8 structures based on cosine similarity score).
Fig. 4 in Recent advances in inducing endophytic fungal specialized metabolites using small molecule elicitors including epigenetic modifiers
Fig. 4. Epigenetic alterations include DNA methyl transferase (DNMT) mediated methylation of DNA (A) and Histone acetyl transferase (HAT) mediated acetylation or Histone deaetylase (HDAC) mediated deacetylation of Histones (B). These tags are associated with chromatin modulation required for expression of cryptic genes.
Fig. 3 in Recent advances in inducing endophytic fungal specialized metabolites using small molecule elicitors including epigenetic modifiers
Fig. 3. Small molecular weight compounds with potential to induce specialized metabolites production in fungi.
Fig. 2 in Recent advances in inducing endophytic fungal specialized metabolites using small molecule elicitors including epigenetic modifiers
Fig. 2. Attenuation of Camptothecin and Paclitaxel production on subculture over five generations of endophytic fungi Fusarium solani and Periconia sp. respectively. Notice the 12-fold decrease of camptothecin production with F. solani in going from the first to the fifth generation (Kusari et al., 2009). Similarly,,b) reported a reduction of 2.96-fold in the yield of Paclitaxel produced by Periconia sp. in going from generation one to generation five.
Fig. 1. A in Recent advances in inducing endophytic fungal specialized metabolites using small molecule elicitors including epigenetic modifiers
Fig. 1. A glimpse of the chemical diversity of specialized metabolites produced by endophytic fungi.
Fig. 5 in Recent advances in inducing endophytic fungal specialized metabolites using small molecule elicitors including epigenetic modifiers
Fig. 5. Selected cryptic metabolites produced through stimulation with DNA methyltransferase and histone deacetylase inhibitors.
In silico study on a binding mechanism of ssDNA aptamers targeting glycosidic bond-containing small molecules
<p>Files with the 5 ssDNA and their complexes with glycosidic bond-containing small molecules after docking, used in the MD simulations, along with MD simulation trajectories, are included as compressed files (.zip). </p><p>Glycosidic bond-containing small molecules docking performed using AutoDock Vina, and MD simulations based on amber software and DNA.bsc1 force fields.</p>
Intra-pemetrexed Plus Third-generation Small Molecule TKI Drugs (e.g. 'Osimertinib') Versus Third-generation Small Molecule TKI Drugs Alone for Leptomeningeal Metastasis From Epidermal Growth Factor R
ClinicalTrials.gov study NCT06304441. IPD Sharing: YES. Countries: 1. Publications: 3.
A Small-molecule Carbonic Anhydrase IX Targeting PET Tracer in Clear Cell Renal Cell Carcinoma
ClinicalTrials.gov study NCT05728515. IPD Sharing: NO. Countries: 1. Publications: 1.
Development of AWZ1066S, a Small Molecule Anti-Wolbachia Candidate Macrofilaricide Drug
ClinicalTrials.gov study NCT05084560. IPD Sharing: NO. Countries: 1. Publications: 1.
Registry for Patients With Acquired Resistance to Small Molecule Kinase Inhibitors in Non-Small-Cell Lung Cancer
ClinicalTrials.gov study NCT00579683. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Small Bioactive Molecules in Early COPD Diseases
ClinicalTrials.gov study NCT04950023. IPD Sharing: NO. Countries: 1. Publications: 1.
A Dose-Finding Study of Birabresib (MK-8628), a Small Molecule Inhibitor of the Bromodomain and Extra-Terminal (BET) Proteins, in Adults With Selected Advanced Solid Tumors (MK-8628-003)
ClinicalTrials.gov study NCT02259114. IPD Sharing: YES. Countries: 0. Publications: 2.
SAR408701 Versus Docetaxel in Previously Treated, Carcinoembryonic Antigen-related Cell Adhesion Molecule 5 (CEACAM5) Positive Metastatic Non-squamous Non-small-cell Lung Cancer Patients
ClinicalTrials.gov study NCT04154956. IPD Sharing: YES. Countries: 26. Publications: 0.
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.