Seelig, Georg

Dynamic DNA nanotechnology using strand-displacement reactions

Zhang, D. Y., & Seelig, G. (2011) · Nature Chemistry

Advanced biosensing and bioanalysis techniquesDNA and Biological Computing

Cited by 1,785

Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

Rosenberg, A. B., Roco, C. M., Muscat, R. A., Kuchina, A., Sample, P., Yao, Z., Graybuck, L. T., Peeler, D. J., Mukherjee, S., Chen, W., et al. (2018) · Science

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 1,422

Random access in large-scale DNA data storage

Organick, L., Ang, S. D., Chen, Y.-J., Lopez, R., Yekhanin, S., Makarychev, K., Racz, M. Z., Kamath, G., Gopalan, P., Nguyen, B., et al. (2018) · Nature Biotechnology

DNA and Biological ComputingAlgorithms and Data Compression

Cited by 775

DNA nanotechnology from the test tube to the cell

Chen, Y.-J., Groves, B., Muscat, R. A., & Seelig, G. (2015) · Nature Nanotechnology

Advanced biosensing and bioanalysis techniquesDNA and Biological Computing

Cited by 594

Human 5′ UTR design and variant effect prediction from a massively parallel translation assay

Sample, P. J., Wang, B., Reid, D. W., Presnyak, V., McFadyen, I. J., Morris, D. R., & Seelig, G. (2019) · Nature Biotechnology

RNA and protein synthesis mechanismsRNA Research and Splicing

Cited by 442

Variant interpretation: functional assays to the rescue

Starita, L. M., Ahituv, N., Dunham, M. J., Kitzman, J. O., Roth, F. P., Seelig, G., Shendure, J., & Fowler, D. M. (2017) · The American Journal of Human Genetics

Genomics and Rare DiseasesGenetic Associations and Epidemiology

Cited by 381

Microbial single-cell RNA sequencing by split-pool barcoding

Kuchina, A., Brettner, L. M., Paleologu, L., Roco, C. M., Rosenberg, A. B., Carignano, A., Kibler, R., Hirano, M., DePaolo, R. W., & Seelig, G. (2021) · Science

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 340

Computing in mammalian cells with nucleic acid strand exchange

Groves, B., Chen, Y.-J., Zurla, C., Pochekailov, S., Kirschman, J. L., Santangelo, P. J., & Seelig, G. (2016) · Nature Nanotechnology

Advanced biosensing and bioanalysis techniquesDNA and Biological Computing

Cited by 220

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation

Bogard, N., Linder, J., Rosenberg, A. B., & Seelig, G. (2019) · Cell

RNA Research and SplicingRNA regulation and disease

Cited by 215

Deep learning of the regulatory grammar of yeast 5′ untranslated regions from 500,000 random sequences

Cuperus, J. T., Groves, B., Kuchina, A., Rosenberg, A. B., Jojic, N., Fields, S., & Seelig, G. (2017) · Genome Research

RNA and protein synthesis mechanismsRNA Research and Splicing

Cited by 205

DNA assembly for nanopore data storage readout

Lopez, R., Chen, Y.-J., Dumas Ang, S., Yekhanin, S., Makarychev, K., Racz, M. Z., Seelig, G., Strauss, K., & Ceze, L. (2019) · Nature Communications

DNA and Biological ComputingNanopore and Nanochannel Transport Studies

Cited by 142

Quantifying Molecular Bias in DNA Data Storage

Chen, Y.-J., Takahashi, C. N., Organick, L., Stewart, K., Ang, S. D., Weiss, P., Peck, B., Seelig, G., Ceze, L., & Strauss, K. (2019) · Nature Communications

DNA and Biological ComputingAlgorithms and Data Compression

Cited by 116

A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences

Linder, J., Bogard, N., Rosenberg, A. B., & Seelig, G. (2020) · Cell Systems

RNA and protein synthesis mechanismsCRISPR and Genetic Engineering

Cited by 107

Optimizing 5’UTRs for mRNA-delivered gene editing using deep learning

Castillo-Hair, S., Fedak, S., Wang, B., Linder, J., Havens, K., Certo, M., & Seelig, G. (2024) · Nature Communications

RNA and protein synthesis mechanismsRNA Interference and Gene Delivery

Cited by 98

A DNA-Based Archival Storage System

Bornholt, J., Lopez, R., Carmean, D. M., Ceze, L., Seelig, G., & Strauss, K. (2016) · ACM SIGOPS Operating Systems Review

DNA and Biological ComputingAdvanced Data Storage Technologies

Cited by 77

Toward a DNA-Based Archival Storage System

Bornholt, J., Lopez, R., Carmean, D. M., Ceze, L., Seelig, G., & Strauss, K. (2017) · IEEE Micro

DNA and Biological ComputingAdvanced Data Storage Technologies

Cited by 75

DNA Data Storage and Hybrid Molecular–Electronic Computing

Carmean, D., Ceze, L., Seelig, G., Stewart, K., Strauss, K., & Willsey, M. (2019) · Proceedings of the IEEE

DNA and Biological ComputingAdvanced Memory and Neural Computing

Cited by 69

A comprehensive analysis of gene expression changes in a high replicate and open-source dataset of differentiating hiPSC-derived cardiomyocytes

Grancharova, T., Gerbin, K. A., Rosenberg, A. B., Roco, C. M., Arakaki, J. E., DeLizo, C. M., Dinh, S. Q., Donovan-Maiye, R. M., Hirano, M., Nelson, A. M., et al. (2021) · Scientific Reports

Pluripotent Stem Cells ResearchSingle-cell and spatial transcriptomics

Cited by 61

Cell states beyond transcriptomics: integrating structural organization and gene expression in hiPSC-derived cardiomyocytes

Gerbin, K. A., Grancharova, T., Donovan-Maiye, R., Hendershott, M. C., Brown, J., Dinh, S. Q., Gehring, J. L., Hirano, M., Johnson, G. R., Nath, A., et al. (2020) · Cell Systems

Single-cell and spatial transcriptomicsPluripotent Stem Cells Research

Cited by 59

A DNA-Based Archival Storage System

Bornholt, J., Lopez, R., Carmean, D. M., Ceze, L., Seelig, G., & Strauss, K. (2016) · ACM SIGPLAN Notices

DNA and Biological ComputingAdvanced Data Storage Technologies

Cited by 54

Deciphering the impact of genetic variation on human polyadenylation using APARENT2

Linder, J., Koplik, S. E., Kundaje, A., & Seelig, G. (2022) · Genome Biology

RNA Research and SplicingGenetic Associations and Epidemiology

Cited by 49