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Organic/inorganic chemistry, analytical chemistry, electrochemistry, molecular properties, chemical reactions
2,032 datasets
A dataset from the OpenML platform with the identifier QSAR-TID-10475. No descriptive metadata, row count, or column information is available.
This is the QSAR-TID-11024 dataset from the OpenML platform. No descriptive metadata, column information, or row count is available.
A dataset from the OpenML platform with identifier QSAR-TID-17081. No descriptive metadata, column information, or sample data is available. The row count, column count, and other specifics are unknown.
A dataset from the OpenML platform with the identifier QSAR-TID-11556. No descriptive metadata, column information, or sample data is available.
A dataset from the OpenML platform with the identifier QSAR-TID-101557. No descriptive metadata, column information, or sample data is available.
A dataset from the OpenML platform with the identifier QSAR-TID-17035. No information is available on its contents, size, or provenance.
A dataset from the OpenML platform with the identifier QSAR-TID-18044. No descriptive metadata, column information, or sample data is available.
This is the QSAR-TID-208 dataset from the OpenML platform. No information is available regarding its contents, size, or provenance.
A dataset from the OpenML platform. No descriptive metadata, row count, or column information is available.
A dataset from the OpenML platform with the identifier QSAR-TID-12514. No descriptive metadata, column information, or sample data is available.
A dataset from the OpenML platform with the identifier QSAR-TID-12886. No information is available on its contents, size, or structure.
A dataset from the OpenML platform with the identifier QSAR-TID-12276. No descriptive metadata, column information, or sample data is available.
Raw data underpins research on iron(III) complexes achieving prolonged luminescence through a mechanism of excited-state equilibration. The dataset includes NMR, time-resolved absorption spectroscopy (TAS), time-correlated single photon counting (TCSPC), time-dependent density functional theory (TD-DFT) results, and mass spectrometry files. These files support the validation and reproduction of findings on reversible intercomponent electron transfer.
More than 300,000 oxygenase genes, primarily monooxygenases and dioxygenases, were identified from a global ocean gene dataset. The dataset comprises approximately 200 million predicted genes from global ocean metagenomes. It was authored by Changfei He and last updated on figshare in April 2026.
6,004,131 chemical compounds from a February 2026 PubChem snapshot have been filtered using the Rule of Three (Ro3) for drug-like properties. Each entry includes a PubChem ID, canonical SMILES string, and 43 molecular descriptors calculated with the RDKit cheminformatics toolkit. The dataset represents a curated subset of the original 123 million PubChem compounds, focused on lead-like chemical space.
A subsampled dataset for quantitative structure-activity relationship (QSAR) modeling of chemical biodegradability. It was created by Eddie Bergman from the original qsar-biodeg dataset on OpenML using a controlled random sampling process. The subsampling parameters included a seed of 4, a maximum of 2000 rows, 100 columns, and 10 classes, with stratification applied.
A subsampled dataset for quantitative structure-activity relationship (QSAR) modeling of chemical biodegradability. It was created by Eddie Bergman from the original qsar-biodeg dataset on OpenML using a controlled random sampling procedure. The subsampling parameters include a seed of 1, a maximum of 2000 rows, 100 columns, and 10 classes, with stratification applied.
A 2000-row, 100-column subsample of the QSAR-biodeg dataset, generated with a random seed of 0 and stratified sampling. The dataset was created by Eddie Bergman and is licensed as public domain in the United States. It likely contains molecular descriptors for modeling chemical biodegradability.
Functioning as titled 'qsar-biodeg'. No information is available on its contents, size, creator, or creation date.
A dataset demonstrating quality degradation caused by 100 iterative edits using the Nano Banana Pro model. It was created by kenantang and last updated on April 10, 2026. The dataset illustrates how imperceptible noise from single-step edits compounds over repeated applications, eventually degrading images to an unusable level.