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Datasets › NCI1

NCI1

Introduced in Comparison of descriptor spaces for chemical compound retrieval and classification1 Jan 2006 archive 2025-07-28

The NCI1 dataset comes from the cheminformatics domain, where each input graph is used as representation of a chemical compound: each vertex stands for an atom of the molecule, and edges between vertices represent bonds between atoms. This dataset is relative to anti-cancer screens where the chemicals are assessed as positive or negative to cell lung cancer. Each vertex has an input label representing the corresponding atom type, encoded by a one-hot-encoding scheme into a vector of 0/1 elements.

Source: Ring Reservoir Neural Networks for Graphs

HomepageBenchmarksPapers JSON

Benchmarks archive 2025-07-28

All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Graph Classification NCI1 TFGW ADJ (L=2) Accuracy 88.1% Template based Graph Neural Network with Optimal... cedricvincentcuaz/TFGW 69 Compare
Graph Classification NCI-123 GAM Accuracy 64.79% Graph Classification using Structural Attention benedekrozemberczki/GAM 1 Compare

Papers archive 2025-07-28

30 shown of 62 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 260. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck 1 1 20 Feb 2025 not harvested
Multi-hop Attention-based Graph Pooling: A Personalized PageRank Perspective 1 1 4 Mar 2024 not harvested
An end-to-end attention-based approach for learning on graphs 1 1 16 Feb 2024 not harvested
Graph isomorphism UNet 1 1 23 Aug 2023 not harvested
Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity 3 1 18 Aug 2023 ran 5 of 26 samples (21 unverified)
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes 0 1 13 Aug 2023 not harvested
CIN++: Enhancing Topological Message Passing 1 1 6 Jun 2023 not harvested
Strengthening structural baselines for graph classification using Local Topological Profile 1 1 1 May 2023 not harvested
Cell Attention Networks 1 1 16 Sep 2022 ran 0 of 5 samples (5 unverified)
Pure Transformers are Powerful Graph Learners 2 1 6 Jul 2022 ran 7 of 7 samples (0 unverified; 7 pointer-only for licence)
TREE-G: Decision Trees Contesting Graph Neural Networks 1 1 6 Jul 2022 ran 0 of 10 samples (10 unverified)
Template based Graph Neural Network with Optimal Transport Distances 1 1 31 May 2022 not harvested
Recipe for a General, Powerful, Scalable Graph Transformer 4 1 25 May 2022 ran 3 of 21 samples (18 unverified)
Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization 0 1 6 Apr 2022 not harvested
A New Perspective on the Effects of Spectrum in Graph Neural Networks 1 1 14 Dec 2021 ran 0 of 2 samples (2 unverified)
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks 1 1 11 Nov 2021 ran 0 of 3 samples (3 unverified)
Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks 1 1 24 Jun 2021 not harvested
Relation order histograms as a network embedding tool 1 1 9 Jun 2021 not harvested
Do Transformers Really Perform Bad for Graph Representation? 5 1 9 Jun 2021 not harvested
How Attentive are Graph Attention Networks? 8 1 30 May 2021 ran 6 of 16 samples (10 unverified; 1 pointer-only for licence)
A Novel Higher-order Weisfeiler-Lehman Graph Convolution 1 1 1 Jul 2020 not harvested
Wasserstein Embedding for Graph Learning 1 1 16 Jun 2020 not harvested
Principal Neighbourhood Aggregation for Graph Nets 8 1 12 Apr 2020 ran 33 of 55 samples (22 unverified; 48 pointer-only for licence)
A Fair Comparison of Graph Neural Networks for Graph Classification 5 2 20 Dec 2019 not harvested
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations 1 1 18 Nov 2019 not harvested
Hierarchical Graph Pooling with Structure Learning 3 1 14 Nov 2019 not harvested
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling 1 1 24 Oct 2019 ran 1 of 1 samples (0 unverified; 1 pointer-only for licence)
A Non-Negative Factorization approach to node pooling in Graph Convolutional Neural Networks 0 1 7 Sep 2019 not harvested
Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation 1 1 4 Jul 2019 ran 0 of 1 samples (1 unverified)
Wasserstein Weisfeiler-Lehman Graph Kernels 2 1 4 Jun 2019 ran 0 of 11 samples (11 unverified)

The full list of 62 is in the JSON twin.

Dataset loaders archive 2025-07-28

docs.dgl.ai/api/python/dgl.data.html#dgl.data.TUDatasetdmlc/dglpytorchtfmxnet
graphneural.network/datasets/#tudatasetdanielegrattarola/spektraltf

2 loaders as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

Graph Classification

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Graphs

Languages archive 2025-07-28

Chinese

Variants archive 2025-07-28

  • NCI1
  • NCI-123

2 variant names, as the archive lists them.

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