Nitzan, Mor

Best practices for single-cell analysis across modalities

Heumos, L., Schaar, A. C., Lance, C., Litinetskaya, A., Drost, F., Zappia, L., Lücken, M. D., Strobl, D. C., Henao, J., Curion, F., et al. (2023) · Nature Reviews Genetics

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 1,051

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram

Biancalani, T., Scalia, G., Buffoni, L., Avasthi, R., Lu, Z., Sanger, A., Tokcan, N., Vanderburg, C. R., Segerstolpe, Å., Zhang, M., et al. (2021) · Nature Methods

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 931

Systema: a framework for evaluating genetic perturbation response prediction beyond systematic variation

Viñas Torné, R., Wiatrak, M., Piran, Z., Fan, S., Jiang, L., Teichmann, S. A., Nitzan, M., & Brbić, M. (2026) · Nature Biotechnology

Gene Regulatory Network AnalysisBioinformatics and Genomic Networks

Cited by 58

Interpreting Single-Cell and Spatial Omics Data Using Deep Neural Network Training Dynamics

Karin, J., Mintz, R., Raveh, B., & Nitzan, M. (2024) · Nature Computational Science

Single-cell and spatial transcriptomicsCell Image Analysis Techniques

Cited by 16

Human brain microRNAs exhibit cell-type specificity and age dependence

Dubnov, S., Laski, L., Zchut, I., Avidan, O., Bennett, E. R., Greenberg, D. S., Turjeman, A., Nitzan, M., Paldor, I., & Soreq, H. (2026) · bioRxiv (Cold Spring Harbor Laboratory)

MicroRNA in disease regulationSingle-cell and spatial transcriptomics

Cited by 0