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Paper

Majdandzic, Antonio, Rajesh, Chandana, Koo, Peter K (May 2023) Correcting gradient-based interpretations of deep neural networks for genomics. Genome Biology, 24 (1). p. 109. ISSN 1474-760X

Koo, Peter K, Ploenzke, Matt, Anand, Praveen, Paul, Steffan, Majdandzic, Antonio (2023) ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks. Methods in Molecular Biology, 2586. pp. 197-215. ISSN 1064-3745

Majdandzic, Antonio, Rajesh, Chandana, Tang, Amber, Toneyan, Shushan, Labelson, Ethan, Tripathy, Rohit, Koo, Peter K (November 2022) Selecting deep neural networks that yield consistent attribution-based interpretations for genomics. Proc Mach Learn Res, 200. pp. 131-149. ISSN 2640-3498

Majdandzic, Antonio, Koo, Peter K (May 2022) Statistical correction of input gradients for black box models trained with categorical input features. BioRxiv. (Unpublished)

Koo, Peter K, Majdandzic, Antonio, Ploenzke, Matthew, Anand, Praveen, Paul, Steffan B (May 2021) Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks. PLoS Computational Biology, 17 (5). e1008925. ISSN 1553-7358

Koo, Peter, Majdandzic, Antonio, Ploenzke, Matthew, Anand, Praveen, Paul, Steffan (September 2020) Global Importance Analysis: An Interpretability Method to Quantify Importance of Genomic Features in Deep Neural Networks. BioRxiv. (Unpublished)

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