{"url":"/dataset/sider","name":"SIDER","full_name":"SIDER","description_markdown":"**SIDER** contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug–target relations.\n\nSource: [Side Effect Resource](http://sideeffects.embl.de/)\nImage Source: [http://sideeffects.embl.de/drugs/2756/](http://sideeffects.embl.de/drugs/2756/)","description_withheld":null,"homepage":"http://sideeffects.embl.de/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Graph Classification","url":"/task/graph-classification","datasets_with_task":"/datasets/task/graph-classification"},{"name":"Drug Discovery","url":"/task/drug-discovery","datasets_with_task":"/datasets/task/drug-discovery"},{"name":"Molecular Property Prediction","url":"/task/molecular-property-prediction","datasets_with_task":"/datasets/task/molecular-property-prediction"},{"name":"Molecular Property Prediction (1-shot))","url":"/task/molecular-property-prediction-1-shot","datasets_with_task":"/datasets/task/molecular-property-prediction-1-shot"}],"languages":[],"variants":["SIDER"],"data_loaders":[],"num_papers_in_archive":19,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/molecular-property-prediction-on-sider-1","task":"Molecular Property Prediction","dataset_variant":"SIDER","rows":19,"metrics":["ROC-AUC"],"first_row_in_archive_order":{"model":"BioAct-Het","paper":"/paper/bioact-het-a-heterogeneous-siamese-neural","metrics":{"ROC-AUC":"91.11"},"code_links":[{"title":"CBRC-lab/BioAct-Het","url":"https://github.com/CBRC-lab/BioAct-Het"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/drug-discovery-on-sider","task":"Drug Discovery","dataset_variant":"SIDER","rows":4,"metrics":["AUC"],"first_row_in_archive_order":{"model":"elEmBERT-V1","paper":"/paper/structure-to-property-chemical-element","metrics":{"AUC":"0.778"},"code_links":[{"title":"dmamur/elembert","url":"https://github.com/dmamur/elembert"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/graph-classification-on-sider","task":"Graph Classification","dataset_variant":"SIDER","rows":2,"metrics":["ROC-AUC"],"first_row_in_archive_order":{"model":"GTOT-Tuning","paper":"/paper/fine-tuning-graph-neural-networks-via-graph","metrics":{"ROC-AUC":"63.5"},"code_links":[{"title":"youjibiying/gtot-tuning","url":"https://github.com/youjibiying/gtot-tuning"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/integrating-convolutional-layers-and-biformer","title":"Integrating convolutional layers and biformer network with forward-forward and backpropagation training","date":"2025-02-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/pre-training-graph-neural-networks-on","title":"Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck","date":"2025-02-20","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/fine-tuning-graph-neural-networks-by","title":"Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns","date":"2023-12-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":13,"samples_ran":13,"samples_unverified":0,"pointer_only_for_licence":13,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/bioact-het-a-heterogeneous-siamese-neural","title":"BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representatio","date":"2023-10-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/structure-to-property-chemical-element","title":"Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties","date":"2023-09-17","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/git-mol-a-multi-modal-large-language-model","title":"GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text","date":"2023-08-14","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/molxpt-wrapping-molecules-with-text-for","title":"MolXPT: Wrapping Molecules with Text for Generative Pre-training","date":"2023-05-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/molecular-structure-property-co-trained","title":"Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model","date":"2022-11-19","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/galactica-a-large-language-model-for-science-1","title":"Galactica: A Large Language Model for Science","date":"2022-11-16","rows_on_this_dataset":5,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/uni-mol-a-universal-3d-molecular","title":"Uni-Mol: A Universal 3D Molecular Representation Learning Framework","date":"2022-09-08","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/fine-tuning-graph-neural-networks-via-graph","title":"Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport","date":"2022-03-20","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/chemrl-gem-geometry-enhanced-molecular","title":"ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction","date":"2021-06-11","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/grover-self-supervised-message-passing","title":"Self-Supervised Graph Transformer on Large-Scale Molecular Data","date":"2020-06-18","rows_on_this_dataset":2,"code_links":3,"syntology":null},{"paper":"/paper/locally-constant-networks","title":"Oblique Decision Trees from Derivatives of ReLU Networks","date":"2019-09-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/pre-training-graph-neural-networks","title":"Strategies for Pre-training Graph Neural Networks","date":"2019-05-29","rows_on_this_dataset":2,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":10,"samples_unverified":4,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/are-learned-molecular-representations-ready","title":"Analyzing Learned Molecular Representations for Property Prediction","date":"2019-04-02","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":3,"samples_unverified":12,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/n-gram-graph-a-novel-molecule-representation","title":"N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules","date":"2018-06-24","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":0,"samples_unverified":14,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/low-data-drug-discovery-with-one-shot","title":"Low Data Drug Discovery with One-shot Learning","date":"2016-11-10","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":8,"samples_harvested":63,"samples_ran":28,"samples_unverified":35,"pointer_only_for_licence":15,"papers_with_no_sample_that_ran":3,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}