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Thompson, Mike, Martín, Mariano, Olmo, Trinidad Sanmartín, Rajesh, Chandana, Koo, Peter K, Bolognesi, Benedetta, Lehner, Ben (May 2025) Massive experimental quantification allows interpretable deep learning of protein aggregation. Science Advances, 11 (18). eadt5111. ISSN 2375-2548 (Public Dataset)

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

Karakida Kawaguchi, Risa, Tang, Ziqi, Fischer, Stephan, Rajesh, Chandana, Tripathy, Rohit, Koo, Peter K, Gillis, Jesse (December 2022) Learning single-cell chromatin accessibility profiles using meta-analytic marker genes. Briefings in Bioinformatics. bbac541. ISSN 1467-5463

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