Items where Community is "Koo Lab"

Paper

Zhou, Jessica, Rizzo, Kaeli, Tang, Ziqi, Koo, Peter K (November 2024) Uncertainty-aware genomic deep learning with knowledge distillation. bioRxiv. ISSN 2692-8205 (Public Dataset) (Submitted)

Rafi, Abdul Muntakim, Nogina, Daria, Penzar, Dmitry, Lee, Dohoon, Lee, Danyeong, Kim, Nayeon, Kim, Sangyeup, Kim, Dohyeon, Shin, Yeojin, Kwak, Il-Youp, Meshcheryakov, Georgy, Lando, Andrey, Zinkevich, Arsenii, Kim, Byeong-Chan, Lee, Juhyun, Kang, Taein, Vaishnav, Eeshit Dhaval, Yadollahpour, Payman, Random Promoter DREAM Challenge Consortium, Kim, Sun, Albrecht, Jake, Regev, Aviv, Gong, Wuming, Kulakovskiy, Ivan V, Meyer, Pablo, de Boer, Carl G (October 2024) A community effort to optimize sequence-based deep learning models of gene regulation. Nature Biotechnology. ISSN 1087-0156 (Public Dataset)

Zhou, Jessica L, Guruvayurappan, Karthik, Toneyan, Shushan, Chen, Hsiuyi V, Chen, Aaron R, Koo, Peter, McVicker, Graham (October 2024) Analysis of single-cell CRISPR perturbations indicates that enhancers predominantly act multiplicatively. Cell Genomics. p. 100672. ISSN 2666-979X (Public Dataset)

Toneyan, Shushan, Koo, Peter K (September 2024) Interpreting cis-regulatory interactions from large-scale deep neural networks. Nature Genetics. ISSN 1546-1718 (Public Dataset)

Thompson, Mike, Martin, Mariano, Olmo, Trinidad Sanmartin, Rajesh, Chandana, Koo, Peter, Bolognesi, Benedetta, Lehner, Ben (July 2024) Interpretably deep learning amyloid nucleation by massive experimental quantification of random sequences. bioRxiv. (Submitted)

Zhou, Jessica, Guruvayurappan, Karthik, Toneyan, Shushan, Chen, Hsiuyi V, Chen, Aaron R, Koo, Peter, McVicker, Graham (July 2024) Analysis of single-cell CRISPR perturbations indicates that enhancers act multiplicatively and provides limited evidence for epistatic-like interactions. bioRxiv. (Public Dataset) (Submitted)

Seitz, EE, McCandlish, DM, Kinney, JB, Koo, PK (June 2024) Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models. Nature Machine Intelligence, 6 (6). pp. 701-713. ISSN 2522-5839 (Public Dataset)

Sarkar, Anirban, Tang, Ziqi, Zhao, Chris, Koo, Peter (May 2024) Designing DNA With Tunable Regulatory Activity Using Discrete Diffusion. bioRxiv. (Submitted)

Renton, Angela I, Dao, Thuy T, Johnstone, Tom, Civier, Oren, Sullivan, Ryan P, White, David J, Lyons, Paris, Slade, Benjamin M, Abbott, David F, Amos, Toluwani J, Bollmann, Saskia, Botting, Andy, Campbell, Megan EJ, Chang, Jeryn, Close, Thomas G, Doerig, Monika, Eckstein, Korbinian, Egan, Gary F, Evas, Stefanie, Flandin, Guillaume, Garner, Kelly G, Garrido, Marta I, Ghosh, Satrajit S, Grignard, Martin, Halchenko, Yaroslav O, Hannan, Anthony J, Heinsfeld, Anibal S, Huber, Laurentius, Hughes, Matthew E, Kaczmarzyk, Jakub R, Kasper, Lars, Kuhlmann, Levin, Lou, Kexin, Mantilla-Ramos, Yorguin-Jose, Mattingley, Jason B, Meier, Michael L, Morris, Jo, Narayanan, Akshaiy, Pestilli, Franco, Puce, Aina, Ribeiro, Fernanda L, Rogasch, Nigel C, Rorden, Chris, Schira, Mark M, Shaw, Thomas B, Sowman, Paul F, Spitz, Gershon, Stewart, Ashley W, Ye, Xincheng, Zhu, Judy D, Narayanan, Aswin, Bollmann, Steffen (May 2024) Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging. Nature Methods, 21 (2). pp. 804-808. ISSN 1548-7091

Tang, Ziqi, Koo, Peter K (March 2024) Evaluating the representational power of pre-trained DNA language models for regulatory genomics. bioRxiv. (Public Dataset) (Submitted)

Yu, Yiyang, Muthukumar, Shivani, Koo, Peter K (February 2024) EvoAug-TF: Extending evolution-inspired data augmentations for genomic deep learning to TensorFlow. Bioinformatics. ISSN 1367-4811

Yu, Yiyang, Muthukumar, Shivani, Koo, Peter K (January 2024) EvoAug-TF: Extending evolution-inspired data augmentations for genomic deep learning to TensorFlow. bioRxiv. (Submitted)

Tang, Ziqi, Toneyan, Shushan, Koo, Peter K (December 2023) Current approaches to genomic deep learning struggle to fully capture human genetic variation. Nature Genetics, 55 (12). pp. 2021-2022. ISSN 1061-4036

Seitz, Evan E, McCandlish, David M, Kinney, Justin B, Koo, Peter K (November 2023) Interpreting cis -regulatory mechanisms from genomic deep neural networks using surrogate models. bioRxiv. (Submitted)

Kaczmarzyk, Jakub R, Gupta, Rajarsi, Kurc, Tahsin M, Abousamra, Shahira, Saltz, Joel H, Koo, Peter K (September 2023) ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification. Computer Methods and Programs in Biomedicine, 239. p. 107631. ISSN 0169-2607

Toneyan, Shushan, Koo, Peter K (July 2023) Interpreting Cis -Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics. bioRxiv. (Submitted)

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

Lee, Nicholas Keone, Tang, Ziqi, Toneyan, Shushan, Koo, Peter K (May 2023) EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations. Genome Biology, 24 (1). p. 105. ISSN 1474-760X

Gao, Yuan, He, Xue-Yan, Wu, Xiaoli S, Huang, Yu-Han, Toneyan, Shushan, Ha, Taehoon, Ipsaro, Jonathan J, Koo, Peter K, Joshua-Tor, Leemor, Bailey, Kelly M, Egeblad, Mikala, Vakoc, Christopher R (January 2023) ETV6 dependency in Ewing sarcoma by antagonism of EWS-FLI1-mediated enhancer activation. Nature Cell Biology. ISSN 1465-7392 (Public Dataset)

Artz, Oliver, Ackermann, Amanda, Taylor, Laura, Koo, Peter K, Pedmale, Ullas V (January 2023) Light and temperature regulate m6A-RNA modification to regulate growth in plants. bioRxiv. (Submitted)

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

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

Toneyan, Shushan, Tang, Ziqi, Koo, Peter K (December 2022) Evaluating deep learning for predicting epigenomic profiles. Nature Machine Intelligence, 4 (12). pp. 1088-1100. ISSN 2522-5839

Petti, Samantha, Bhattacharya, Nicholas, Rao, Roshan, Dauparas, Justas, Thomas, Neil, Zhou, Juannan, Rush, Alexander M, Koo, Peter, Ovchinnikov, Sergey (November 2022) End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman. Bioinformatics. ISSN 1367-4803

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

Toneyan, Shushan, Tang, Ziqi, Koo, Peter K (May 2022) Evaluating deep learning for predicting epigenomic profiles. bioRxiv. (Unpublished)

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

Lee, Nicholas Keone, Tang, Ziqi, Toneyan, Shushan, Koo, Peter (2022) EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations. bioRxiv. (Submitted)

Bhattacharya, Nicholas, Thomas, Neil, Rao, Roshan, Dauparas, Justas, Koo, Peter K, Baker, David, Song, Yun S, Ovchinnikov, Sergey (2022) Interpreting Potts and Transformer Protein Models Through the Lens of Simplified Attention. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 27. pp. 34-45. ISSN 2335-6936

Petti, Samantha, Bhattacharya, Nicholas, Rao, Roshan, Dauparas, Justas, Thomas, Neil, Zhou, Juannan, Rush, Alexander M, Koo, Peter K, Ovchinnikov, Sergey (October 2021) End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman. BioRxiv. (Unpublished)

Zhao, Yixin, Dukler, Noah, Barshad, Gilad, Toneyan, Shushan, Danko, Charles G, Siepel, Adam (August 2021) Deconvolution of Expression for Nascent RNA sequencing data (DENR) highlights pre-RNA isoform diversity in human cells. Bioinformatics. ISSN 1367-4803

Ghotra, Rohan, Lee, Nicholas Keone, Tripathy, Rohit, Koo, Peter K (July 2021) Designing Interpretable Convolution-Based Hybrid Networks for Genomics. bioRxiv. (Submitted)

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

Kawaguchi, Risa Karakida, Tang, Ziqi, Fischer, Stephan, Tripathy, Rohit, Koo, Peter, Gillis, Jesse (April 2021) Exploiting marker genes for robust classification and characterization of single-cell chromatin accessibility. bioRxiv. (Unpublished)

Zhao, Yixin, Dukler, Noah, Barshad, Gilad, Toneyan, Shushan, Danko, Charles, Siepel, Adam (March 2021) Deconvolution of Expression for Nascent RNA Sequencing Data (DENR) Highlights Pre-RNA Isoform Diversity in Human Cells. BioRxiv. (Unpublished)

Koo, Peter K, Ploenzke, Matt (March 2021) Improving representations of genomic sequence motifs in convolutional networks with exponential activations. Nature Machine Intelligence, 3 (3). pp. 258-266. ISSN 2522-5839

Marshall, Dylan, Wang, Haobo, Stiffler, Michael, Dauparas, Justas, Koo, Peter, Ovchinnikov, Sergey (November 2020) The structure-fitness landscape of pairwise relations in generative sequence models. BioRxiv. (Unpublished)

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)

Koo, Peter, Ploenzke, Matt (June 2020) Improving representations of genomic sequence motifs in convolutional networks with exponential activations. BioRxiv. (Unpublished)

Somerville, T. D. D., Xu, Y., Wu, X. S., Maia-Silva, D., Hur, S. K., de Almeida, L. M. N., Preall, J. B., Koo, P. K., Vakoc, C. R. (May 2020) ZBED2 is an antagonist of interferon regulatory factor 1 and modifies cell identity in pancreatic cancer. Proc Natl Acad Sci U S A, 117 (21). pp. 11471-11482. ISSN 0027-8424 (Print)0027-8424

Koo, Peter K, Ploenzke, Matt (February 2020) Interpreting Deep Neural Networks Beyond Attribution Methods: Quantifying Global Importance of Genomic Features. bioRxiv. (Submitted)

Koo, PK, Ploenzke, M (February 2020) Deep learning for inferring transcription factor binding sites. Current Opinion in Systems Biology, 19. pp. 16-23. ISSN 2452-3100

Rey-Suarez, Ivan, Wheatley, Brittany A, Koo, Peter, Bhanja, Anshuman, Shu, Zhou, Mochrie, Simon, Song, Wenxia, Shroff, Hari, Upadhyaya, Arpita (January 2020) WASP family proteins regulate the mobility of the B cell receptor during signaling activation. Nature Communications, 11 (1). p. 439. ISSN 2041-1723

Koo, Peter K, Eddy, Sean R (December 2019) Representation learning of genomic sequence motifs with convolutional neural networks. PLoS Computational Biology, 15 (12). e1007560. ISSN 1553-734X

Derkarabetian, S., Castillo, S., Koo, P. K., Ovchinnikov, S., Hedin, M. (October 2019) A demonstration of unsupervised machine learning in species delimitation. Mol Phylogenet Evol, 139. p. 106562. ISSN 1055-7903

Dauparas, Justas, Wang, Haobo, Swartz, Avi, Koo, Peter, Nitzan, Mor, Ovchinnikov, Sergey (June 2019) Unified framework for modeling multivariate distributions in biological sequences. arXiv e-prints. (Unpublished)

Koo, Peter K., Ploenzke, Matt (2019) Improving Convolutional Network Interpretability with Exponential Activations. bioRxiv. p. 650804. (Unpublished)

Rey-Suarez, Ivan, Wheatley, Brittany, Koo, Peter, Shu, Zhou, Mochrie, Simon, Song, Wenxia, Shroff, Hari, Upadhyaya, Arpita (2019) N-WASP regulates the mobility of the B cell receptor and co-receptors during signaling activation. bioRxiv. p. 619627. (Unpublished)

Koo, Peter K., Eddy, Sean R. (2019) Representation Learning of Genomic Sequence Motifs with Convolutional Neural Networks. bioRxiv. p. 362756. (Unpublished)

Koo, Peter K., Qian, Sharon, Kaplun, Gal, Volf, Verena, Kalimeris, Dimitris (2019) Robust Neural Networks are More Interpretable for Genomics. bioRxiv. p. 657437. (Unpublished)

Koo, P. K., Mochrie, S. G. J. (2018) Applying Perturbation Expectation-Maximization to Protein Trajectories of Rho GTPases. Methods Mol Biol, 1821. pp. 57-70. ISSN 1064-3745

Koo, Peter K., Anand, Praveen, Paul, Steffan B., Eddy, Sean R. (2018) Inferring Sequence-Structure Preferences of RNA-Binding Proteins with Convolutional Residual Networks. bioRxiv. p. 418459. (Unpublished)

Dunn, Timothy W., Koo, Peter K. (2017) Inferring Functional Neural Connectivity with Deep Residual Convolutional Networks. bioRxiv. p. 141010. (Unpublished)

Koo, P. K., Mochrie, S. G. (November 2016) Systems-level approach to uncovering diffusive states and their transitions from single-particle trajectories. Phys Rev E, 94 (5-1). 052412. ISSN 2470-0045

Koo, P. K., Setru, S. U., Mochrie, S. G. (August 2016) Erratum: "Active drift stabilization in three dimensions via image cross-correlation" [Rev. Sci. Instrum. 84, 103705 (2013)]. Rev Sci Instrum, 87 (8). 089901. ISSN 0034-6748

Zhao, Y., Schreiner, S. M., Koo, P. K., Colombi, P., King, M. C., Mochrie, S. G. (July 2016) Improved Determination of Subnuclear Position Enabled by Three-Dimensional Membrane Reconstruction. Biophys J, 111 (1). pp. 19-24. ISSN 0006-3495

Jang, Woo-Sik, Koo, Peter, Bryson, Kyle, Narayanan, Suresh, Sandy, Alec R., Russell, Thomas P., Mochrie, Simon G. (2016) The Static Structure and Dynamics of Cadmium Sulfide Nanoparticles within Poly(styrene-block-isoprene) Diblock Copolymer Melts. Macromolecular Chemistry and Physics, 217 (4). pp. 591-598. ISSN 1022-1352

Koo, P. K., Weitzman, M., Sabanaygam, C. R., van Golen, K. L., Mochrie, S. G. (October 2015) Extracting Diffusive States of Rho GTPase in Live Cells: Towards In Vivo Biochemistry. PLoS Comput Biol, 11 (10). e1004297. ISSN 1553-734x

Ciubotaru, M., Surleac, M. D., Metskas, L. A., Koo, P., Rhoades, E., Petrescu, A. J., Schatz, D. G. (January 2015) The architecture of the 12RSS in V(D)J recombination signal and synaptic complexes. Nucleic Acids Res, 43 (2). pp. 917-31. ISSN 0305-1048

Schreiner, Sarah M., Koo, Peter K., Zhao, Yao, Mochrie, Simon G. J., King, Megan C. (2015) The tethering of chromatin to the nuclear envelope supports nuclear mechanics. Nature Communications, 6. p. 7159.

Jang, Woo-Sik, Koo, Peter, Bryson, Kyle, Narayanan, Suresh, Sandy, Alec, Russell, Thomas P., Mochrie, Simon G. (2014) Dynamics of Cadmium Sulfide Nanoparticles within Polystyrene Melts. Macromolecules, 47 (18). pp. 6483-6490. ISSN 0024-9297

Koo, P. K., Setru, S. U., Mochrie, S. G. (October 2013) Active drift stabilization in three dimensions via image cross-correlation. Rev Sci Instrum, 84 (10). p. 103705. ISSN 0034-6748

Jang, Woo-Sik, Koo, Peter, Sykorsky, Marcin, Narayanan, Suresh, Sandy, Alec, Mochrie, Simon G. J. (2013) The Static and Dynamic Structure Factor of a Diblock Copolymer Melt via Small-Angle X-ray Scattering and X-ray Photon Correlation Spectroscopy. Macromolecules, 46 (21). pp. 8628-8637. ISSN 0024-9297

Nath, A., Trexler, A. J., Koo, P., Miranker, A. D., Atkins, W. M., Rhoades, E. (2010) Single-molecule fluorescence spectroscopy using phospholipid bilayer nanodiscs. Methods Enzymol, 472. pp. 89-117. ISSN 0076-6879

Nath, A., Koo, P. K., Rhoades, E., Atkins, W. M. (November 2008) Allosteric effects on substrate dissociation from cytochrome P450 3A4 in nanodiscs observed by ensemble and single-molecule fluorescence spectroscopy. J Am Chem Soc, 130 (47). pp. 15746-7. ISSN 0002-7863

Conference or Workshop Item

Ciubotaru, Mihai, Ionita, Elena, Koo, Peter (2023) RAG DNA recombinase mechanism investigated by single molecule assays; novel reaction mechanism derived from thermodynamics and statistical analysis. In: 25th International Analytical Ultracentrifugation Conference, July 10-15, 2022, Lethbridge, AB, Canada.

Koo, P. K., Ploenzke, Matt (June 2019) Improving Convolutional Network Interpretability with Exponential Activations. In: ICML Workshop for Computational Biology, Long Beach, CA.

Koo, Peter K., Qian, Sharon, Volf, Verena, Kalimeris, Dimitris (June 2019) Robust Neural Networks are More Interpretable for Genomics. In: ICML Workshop for Computational Biology, Long Beach, CA.

Dauparas, Justas, Wang, Haobo, Swartz, Avi, Koo, Peter K., Nitzan, Mor, Ovchinnikov, Sergey (June 2019) Unified framework for modeling multivariate distributions in biological sequences. In: ICML Workshop for Computational Biology, Long Beach, CA.

Thesis

Toneyan, Shushan (May 2024) Evaluating and interpreting genomic insights from sequence-based deep learning for regulatory genomics. PhD thesis, Cold Spring Harbor Laboratory.

Tang, Ziqi (April 2024) Exploring the Representational Power of Genomic Deep Learning Models. PhD thesis, Cold Spring Harbor Laboratory.