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Chapter and Conference Paper
A Sequence-Based Antibody Paratope Prediction Model Through Combing Local-Global Information and Partner Features
Antibodies are proteins which play a vital role in the immune system by recognizing and neutralizing antigens. The region on the antibody binding to an antigen, known as paratope, mediates antibody-antigen int...
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Article
Open AccessPredicting chemical bioavailability using microarray gene expression data and regression modeling: A tale of three explosive compounds
Chemical bioavailability is an important dose metric in environmental risk assessment. Although many approaches have been used to evaluate bioavailability, not a single approach is free from limitations. Previ...
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Chapter and Conference Paper
Learning to Recognize Protected Health Information in Electronic Health Records with Recurrent Neural Network
De-identification in electronic health records is a prerequisite to distribute medical records for further clinical data processing or mining. In this paper, we introduce a framework based on recurrent neural ...
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Article
Open AccessImplementation of multiple-instance learning in drug activity prediction
In the context of drug discovery and development, much effort has been exerted to determine which conformers of a given molecule are responsible for the observed biological activity. In this work we aimed to p...
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Article
Open AccessLeveraging domain information to restructure biological prediction
It is commonly believed that including domain knowledge in a prediction model is desirable. However, representing and incorporating domain information in the learning process is, in general, a challenging prob...
