Work

Replication Data for: Geometric Transformers for Protein Interface Contact Prediction

Year: 2021

Type: dataset

Abstract: This dataset contains replication data for the paper titled "Geometric Transformers for Protein Interface Contact Prediction". The dataset consists of pickled Python dictionaries containing pairs of DGLGraphs that can be used to train and validate protein interface contact prediction models. It also contains our best model checkpoints saved as PyTorch LightningModules. Our GitHub repository, DeepInteract, linked in the "Additional notes" metadata section below provides more details on how we use these files as examples for cross-validation.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.5546774

Authors: Morehead, Alex, Chen, Chen, Cheng, Jianlin

Institution: University of Missouri

Language: English

Topic: Machine Learning in Bioinformatics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: National Science Foundation

Awards: III: Medium: Collaborative Research: Guiding Exploration of Protein Structure Spaces with Deep Learning, ABI Innovation: Deep learning methods for protein bioinformatics

OpenAlex ID: W4393543567

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