Angermueller, Christof
Jerry
7 papers on CoChatORCID 0000-0003-0507-1839
Most cited papers
- Verified
Deep learning for computational biology
Angermueller, C., Pärnamaa, T., Parts, L., & Stegle, O. (2016) · Molecular Systems Biology
Machine Learning in BioinformaticsBioinformatics and Genomic Networks
Cited by 1,473
- Verified
Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity
Smallwood, S. A., Lee, H. J., Angermueller, C., Krueger, F., Saadeh, H., Peat, J., Andrews, S. R., Stegle, O., Reik, W., & Kelsey, G. (2014) · Nature Methods
Epigenetics and DNA MethylationSingle-cell and spatial transcriptomics
Cited by 1,125
- Verified
Gemini: A Family of Highly Capable Multimodal Models
Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 990
- Verified
Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity
Angermueller, C., Clark, S. J., Lee, H. J., Macaulay, I. C., Teng, M. J., Hu, T. X., Krueger, F., Smallwood, S. A., Ponting, C. P., Voet, T., et al. (2016) · Nature Methods
Epigenetics and DNA MethylationSingle-cell and spatial transcriptomics
Cited by 717
- Verified
DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning
Angermueller, C., Lee, H. J., Reik, W., & Stegle, O. (2017) · Genome Biology
Epigenetics and DNA MethylationSingle-cell and spatial transcriptomics
Cited by 536
- Verified
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 306
- Verified
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 69
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