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Drug-target interaction, molecular screening, ADMET, compound databases, pharmaceutical data
626 datasets
A materials database integrated with hierarchical ion-transport calculations for screening solid electrolytes. The platform, reported by Bing He, automates preprocessing for first-principles nudged elastic band (FP-NEB) calculations and provides an open web interface to facilitate machine learning. The SPSE database is based on the FAIR principles for the research community.
46 schoolchildren participated in an observational, prospective, cross-sectional study comparing auditory function and genotoxic biomarkers. The study group consisted of 21 normo-hearing students residing in a tobacco-producing region, while the control group had 25 normo-hearing students from non-rural areas. The dataset was created by Letícia Regina Kunst and is available via paperswithcode.
Proteomic data from 14 snakebite cases treated at the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine. Serum protein quantification was performed using LC-MS/MS, identifying 474 unique proteins and 93 differential abundance proteins. The dataset was created by Degang Dong to investigate pathways of venom-induced toxicity and antioxidant defense.
Molecular dynamics simulation data of wild-type and mutant IG4 T-cell receptors interacting with the NY-ESO tumor epitope peptide. The dataset comprises six simulations totaling 6000 nanoseconds (6µs), capturing states before, during, and after antigen binding. It was produced by Sunil Kumar Tripathi and shared via paperswithcode.
1,173 mutations across chimeric DcuS/EnvZ sensor histidine kinases were screened for signaling outputs in response to ligands fumarate and aspartate. Lucas Lippert deposited these barcode-count files for analysis on GitHub, with raw sequencing data available on the NIH Sequence Read Archive. The dataset was last updated on May 21, 2026.
Ami Thakkar's dataset from 2026 contains computational and experimental data on 198 longifolene derivatives designed as potential Alzheimer's disease therapeutics. The data includes results from molecular docking, MD simulations, cytotoxicity assays, and in vitro evaluations of neuroprotective effects. The dataset is hosted on figshare under a CC-BY-4.0 license.
Canadian pulp and paper mills are required to conduct sublethal toxicity testing of their effluent under the Pulp and Paper Effluent Regulations (PPER). The dataset contains results from chronic exposure tests measuring effects on survival, growth, and reproduction in marine or freshwater organisms, reported as LC50, IC25, or EC25 values. Data is published as reported by mills and has not been verified for accuracy and completeness.
A computational study screened 1820 FDA-approved compounds against the Chikungunya virus nsP2 protease. The dataset contains molecular docking scores and simulation results, identifying eight top-scoring candidates including venetoclax and lapatinib. Quynh Mai Thai authored the study, which was last updated on 2026-05-29.
A computational screening dataset of 1,820 FDA-approved compounds docked against the Chikungunya virus nsP2 protease. The dataset includes docking scores, molecular dynamics simulation results, and free energy perturbation calculations, identifying potential drug candidates like venetoclax and lapatinib. It was created by Quynh Mai Thai and last updated on 2026-05-29.
Quynh Mai Thai's dataset contains computational screening results for 1,820 FDA-approved compounds against the Chikungunya virus nsP2 protease. The data includes molecular docking scores, molecular dynamics simulation results, and free energy perturbation calculations to predict potential drug inhibitors. It was last updated on 2026-05-29.
A propensity-score-matched cohort of 50 cadmium-exposed individuals (25 anxious vs 25 non-anxious) provided plasma proteomics data. The dataset includes results from LC-MS/MS proteomic profiling, network pharmacology screening, molecular docking, 100ns molecular dynamics simulations, and rat behavioral and histological validation. The data was authored by Maoqin Tian and last updated on 2026-05-25.
Maoqin Tian published a dataset on figshare in 2026. It contains proteomics and pharmacology data from a study investigating cadmium-induced anxiety. The data includes results from a propensity-score-matched cohort of 50 individuals and validation in a rat model.
A research study by Maoqin Tian, published on figshare in 2026, describes a pipeline for identifying multi-target interventions for cadmium-induced anxiety. The work involved profiling plasma proteomes from a propensity-score-matched cohort of 50 individuals and validating findings in a rat model. The dataset consists of a DOCX document summarizing the methodology and results.
A Russian-language dataset for training a multi-task toxicity classifier across three independent binary categories: profanity, threats, and illegal requests. The dataset, created by AtesiT, was last updated on July 15, 2026. It is designed for a multi-label classification task where a single text can belong to multiple categories simultaneously.
Kinopotok Toxicity is a dataset for classifying toxic messages in the support chat of the online cinema "Kinopotok". It contains examples of user requests labeled by toxicity class, created by author dbrovkin. The dataset was last updated on July 15, 2026.
Shuo Yuan's dataset on figshare, last updated 2026-05-29, documents a 42-day trial with 48 broilers. It contains results on growth performance, immune organ indices, oxidative stress markers, inflammatory cytokines, and splenic histopathology and apoptosis, evaluating the protective effects of chitosan-selenium against aflatoxin B1-induced toxicity.
100 balanced text records for training and validating toxicity classification models for an online cinema's customer support chat. The dataset was created by author F1ow421 and was last updated on July 15, 2026. Each record includes a user message text, a toxicity label, and a toxicity category.
A dataset for binary classification of Russian text toxicity. The toxic class is derived from the AlexSham/Toxic_Russian_Comments dataset, while the non-toxic class is derived from the MTS-AI-SearchSkill/MTSBerquad dataset of neutral user questions. The dataset was authored by molyalya and last updated on 2026-07-15.
Kinopotok Toxicity is a training prototype dataset for filtering toxic messages in the support chat of the online cinema 'Kinopotok'. The dataset contains 120 records for binary classification of text as toxic or non-toxic. It was created by author petaevd and was last updated on 2026-07-15.
A dataset for binary classification of toxicity in user messages to an online cinema's support chat. Toxic messages were synthetically generated by a local Qwen/Qwen3-4B-Instruct-2507 model across six categories, while non-toxic messages were extracted from MTEB BANKING77 and two Bitext datasets, filtered, and translated into Russian. The dataset was created by aurelianvolturi and last updated on July 12, 2026.