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Found 5 papers, 1 papers with code
MAMMAL -- Molecular Aligned Multi-Modal Architecture and Language
Drug discovery typically consists of multiple steps, including identifying a target protein key to a disease's etiology, validating that interacting with this target could prevent symptoms or cure the disease, discovering a small molecule or biologic therapeutic to interact with it, and optimizing the candidate molecule through a complex landscape of required properties.
A large dataset curation and benchmark for drug target interaction
In this paper we propose a way to standardize and represent efficiently a very large dataset curated from multiple public sources, split the data into train, validation and test sets based on different meaningful strategies, and provide a concrete evaluation protocol to accomplish a benchmark.
Regularized adversarial examples for model interpretability
In recent years, several methods for model interpretability have been developed, aiming to provide explanation of which subset regions of the model input is the main reason for the model prediction.
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels
Medical image classification involves thresholding of labels that represent malignancy risk levels.
AdapterNet - learning input transformation for domain adaptation
Deep neural networks have demonstrated impressive performance in various machine learning tasks.
