Using Single-Cell and Spatial Transcriptomes to Understand Stem Cell Lineage Specification During Early Embryo Development

WGCNA: an R package for weighted correlation network analysis

Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252 · see citing works

Comprehensive Integration of Single-Cell Data

Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453 · see citing works

Fast, sensitive and accurate integration of single-cell data with Harmony

Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488 · see citing works

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314 · see citing works

Spatial reconstruction of single-cell gene expression data

Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055 · see citing works

Scenic: single-cell regulatory network inference and clustering.

Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4463 · Cited by 6,520 · see citing works

Dimensionality reduction for visualizing single-cell data using UMAP

Becht, E., McInnes, L., Healy, J., Dutertre, C.-A., Kwok, I. W. H., Ng, L. G., Ginhoux, F., & Newell, E. W. (2019) · Nature Biotechnology · doi:10.1038/nbt.4314 · Cited by 5,358 · see citing works

The single-cell transcriptional landscape of mammalian organogenesis

Cao, J., Spielmann, M., Qiu, X., Huang, X., Ibrahim, D. M., Hill, A. J., Zhang, F., Mundlos, S., Christiansen, L., Steemers, F. J., et al. (2019) · Nature · doi:10.1038/s41586-019-0969-x · Cited by 4,490 · see citing works

RNA velocity of single cells

La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti, M. E., Lönnerberg, P., Furlan, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0414-6 · Cited by 4,118 · see citing works

mRNA-Seq whole-transcriptome analysis of a single cell

Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969 · see citing works

Visualization and analysis of gene expression in tissue sections by spatial transcriptomics

Ståhl, P. L., Salmén, F., Vickovic, S., Lundmark, A., Navarro, J. F., Magnusson, J., Giacomello, S., Asp, M., Westholm, J. O., Huss, M., et al. (2016) · Science · doi:10.1126/science.aaf2403 · Cited by 3,834 · see citing works

Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

Street, K., Risso, D., Fletcher, R. B., Das, D., Ngai, J., Yosef, N., Purdom, E., & Dudoit, S. (2018) · BMC Genomics · doi:10.1186/s12864-018-4772-0 · Cited by 3,159 · see citing works

Spatially resolved, highly multiplexed RNA profiling in single cells

Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S., & Zhuang, X. (2015) · Science · doi:10.1126/science.aaa6090 · Cited by 2,969 · see citing works

Tumour evolution inferred by single-cell sequencing

Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., et al. (2011) · Nature · doi:10.1038/nature09807 · Cited by 2,598 · see citing works

Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Rodriques, S. G., Stickels, R. R., Goeva, A., Martin, C. A., Murray, E., Vanderburg, C. R., Welch, J., Chen, L. M., Chen, F., & Macosko, E. Z. (2019) · Science · doi:10.1126/science.aaw1219 · Cited by 2,424 · see citing works

Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH

Eng, C.-H. L., Lawson, M., Zhu, Q., Dries, R., Koulena, N., Takei, Y., Yun, J., Cronin, C., Karp, C., Yuan, G.-C., et al. (2019) · Nature · doi:10.1038/s41586-019-1049-y · Cited by 1,754 · see citing works

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Wolf, F. A., Hamey, F. K., Plass, M., Solana, J., Dahlin, J. S., Göttgens, B., Rajewsky, N., Simon, L., & Theis, F. J. (2019) · Genome Biology · doi:10.1186/s13059-019-1663-x · Cited by 1,698 · see citing works

A comparison of single-cell trajectory inference methods

Saelens, W., Cannoodt, R., Todorov, H., & Saeys, Y. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0071-9 · Cited by 1,670 · see citing works

The Technology and Biology of Single-Cell RNA Sequencing

Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C., & Teichmann, S. A. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.04.005 · Cited by 1,487 · see citing works

Integrative single-cell analysis

Stuart, T., & Satija, R. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0093-7 · Cited by 1,460 · see citing works

Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region

Moffitt, J. R., Bambah-Mukku, D., Eichhorn, S. W., Vaughn, E., Shekhar, K., Perez, J. D., Rubinstein, N. D., Hao, J., Regev, A., Dulac, C., et al. (2018) · Science · doi:10.1126/science.aau5324 · Cited by 1,365 · see citing works

Single-cell genome sequencing: current state of the science

Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334 · see citing works

Single-cell sequencing-based technologies will revolutionize whole-organism science

Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177 · see citing works

High-definition spatial transcriptomics for in situ tissue profiling

Vickovic, S., Eraslan, G., Salmén, F., Klughammer, J., Stenbeck, L., Schapiro, D., Äijö, T., Bonneau, R., Bergenstråhle, L., Navarro, J. F., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0548-y · Cited by 1,150 · see citing works

Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations

van den Brink, S. C., Sage, F., Vértesy, Á., Spanjaard, B., Peterson-Maduro, J., Baron, C. S., Robin, C., & van Oudenaarden, A. (2017) · Nature Methods · doi:10.1038/nmeth.4437 · Cited by 1,072 · see citing works

A single-cell molecular map of mouse gastrulation and early organogenesis

Pijuan-Sala, B., Griffiths, J. A., Guibentif, C., Hiscock, T. W., Jawaid, W., Calero-Nieto, F. J., Mulas, C., Ibarra-Soria, X., Tyser, R. C. V., Ho, D. L. L., et al. (2019) · Nature · doi:10.1038/s41586-019-0933-9 · Cited by 1,033 · see citing works

Single-cell in situ RNA profiling by sequential hybridization

Lubeck, E., Coskun, A. F., Zhiyentayev, T., Ahmad, M., & Cai, L. (2014) · Nature Methods · doi:10.1038/nmeth.2892 · Cited by 985 · see citing works

Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

Farrell, J. A., Wang, Y., Riesenfeld, S. J., Shekhar, K., Regev, A., & Schier, A. F. (2018) · Science · doi:10.1126/science.aar3131 · Cited by 876 · see citing works

Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo

Wagner, D. E., Weinreb, C., Collins, Z. M., Briggs, J. A., Megason, S. G., & Klein, A. M. (2018) · Science · doi:10.1126/science.aar4362 · Cited by 849 · see citing works

A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain

Davie, K., Janssens, J., Koldere, D., De Waegeneer, M., Pech, U., Kreft, Ł., Aibar, S., Makhzami, S., Christiaens, V., Bravo González-Blas, C., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.057 · Cited by 840 · see citing works

Making a commitment: cell lineage allocation and axis patterning in the early mouse embryo

Arnold, S. J., & Robertson, E. J. (2009) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2618 · Cited by 816 · see citing works

Lineage Tracing

Kretzschmar, K., & Watt, F. M. (2012) · Cell · doi:10.1016/j.cell.2012.01.002 · Cited by 719 · see citing works

Self-organization of the human embryo in the absence of maternal tissues

Shahbazi, M. N., Jędrusik, A., Vuoristo, S., Recher, G., Hupalowska, A., Bolton, V. N., Fogarty, N. M. E., Campbell, A., Devito, L., Ilić, D., et al. (2016) · Nature Cell Biology · doi:10.1038/ncb3347 · Cited by 695 · see citing works

SpatialDE: identification of spatially variable genes

Svensson, V., Teichmann, S. A., & Stegle, O. (2018) · Nature Methods · doi:10.1038/nmeth.4636 · Cited by 695 · see citing works

Self-organization of the in vitro attached human embryo

Deglincerti, A., Croft, G. F., Pietila, L., Zernicka‐Goetz, M., Siggia, E. D., & Brivanlou, A. H. (2016) · Nature · doi:10.1038/nature17948 · Cited by 682 · see citing works

Diffusion maps for high-dimensional single-cell analysis of differentiation data

Haghverdi, L., Buettner, F., & Theis, F. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv325 · Cited by 649 · see citing works

Mouse gastrulation: the formation of a mammalian body plan

Tam, P., & Behringer, R. R. (1997) · Mechanisms of Development · doi:10.1016/s0925-4773(97)00123-8 · Cited by 594 · see citing works

Gene function in mouse embryogenesis: get set for gastrulation

Tam, P., & Loebel, D. A. F. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2084 · Cited by 593 · see citing works

Simultaneous lineage tracing and cell-type identification using CRISPR–Cas9-induced genetic scars

Spanjaard, B., Hu, B., Mitic, N., Olivares-Chauvet, P., Janjuha, S., Ninov, N., & Junker, J. P. (2018) · Nature Biotechnology · doi:10.1038/nbt.4124 · Cited by 531 · see citing works

In toto imaging and reconstruction of post-implantation mouse development at the single-cell level

McDole, K., Guignard, L., Amat, F., Berger, A., Malandain, G., Royer, L. A., Turaga, S. C., Branson, K., & Keller, P. J. (2018) · Cell · doi:10.1016/j.cell.2018.09.031 · Cited by 522 · see citing works

A developmental coordinate of pluripotency among mice, monkeys and humans

Nakamura, T., Okamoto, I., Sasaki, K., Yabuta, Y., Iwatani, C., Tsuchiya, H., Seita, Y., Nakamura, S., Yamamoto, T., & Saitou, M. (2016) · Nature · doi:10.1038/nature19096 · Cited by 516 · see citing works

Spatially resolved transcriptomics and beyond

Crosetto, N., Bienko, M., & van Oudenaarden, A. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3832 · Cited by 509 · see citing works

Single-Cell Transcriptomics of Regulatory T Cells Reveals Trajectories of Tissue Adaptation

Miragaia, R. J., Gomes, T., Chomka, A., Jardine, L., Riedel, A., Hegazy, A. N., Whibley, N., Tucci, A., Chen, X., Lindeman, I., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.01.001 · Cited by 499 · see citing works

Whole-organism clone tracing using single-cell sequencing

Alemany, A., Florescu, M., Baron, C. S., Peterson-Maduro, J., & van Oudenaarden, A. (2018) · Nature · doi:10.1038/nature25969 · Cited by 447 · see citing works

Controlled modelling of human epiblast and amnion development using stem cells

Zheng, Y., Xue, X., Shao, Y., Wang, S., Esfahani, S. N., Li, Z., Muncie, J. M., Lakins, J. N., Weaver, V. M., Gumucio, D. L., et al. (2019) · Nature · doi:10.1038/s41586-019-1535-2 · Cited by 444 · see citing works

Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding

Lu, R., Neff, N. F., Quake, S. R., & Weissman, I. L. (2011) · Nature Biotechnology · doi:10.1038/nbt.1977 · Cited by 438 · see citing works

Gene expression divergence recapitulates the developmental hourglass model

Kalinka, A. T., Varga, K. M., Gerrard, D. T., Preibisch, S., Corcoran, D. L., Jarrells, J., Ohler, U., Bergman, C., & Tomančák, P. (2010) · Nature · doi:10.1038/nature09634 · Cited by 415 · see citing works

Single-cell epigenomics: Recording the past and predicting the future

Kelsey, G., Stegle, O., & Reik, W. (2017) · Science · doi:10.1126/science.aan6826 · Cited by 415 · see citing works

The Endoderm of the Mouse Embryo Arises by Dynamic Widespread Intercalation of Embryonic and Extraembryonic Lineages

Kwon, G. S., Viotti, M., & Hadjantonakis, A.-K. (2008) · Developmental Cell · doi:10.1016/j.devcel.2008.07.017 · Cited by 402 · see citing works

High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin

Achim, K., Pettit, J.-B., Saraiva, L. R., Gavriouchkina, D., Larsson, T., Arendt, D., & Marioni, J. C. (2015) · Nature Biotechnology · doi:10.1038/nbt.3209 · Cited by 395 · see citing works

Assembly of embryonic and extraembryonic stem cells to mimic embryogenesis in vitro

Harrison, S., Sözen, B., Christodoulou, N., Kyprianou, C., & Zernicka‐Goetz, M. (2017) · Science · doi:10.1126/science.aal1810 · Cited by 393 · see citing works

Conserved Patterns of Cell Movements during Vertebrate Gastrulation

Solnica-Krezel, L. (2005) · Current Biology · doi:10.1016/j.cub.2005.03.016 · Cited by 391 · see citing works

The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing

Lein, E., Borm, L. E., & Linnarsson, S. (2017) · Science · doi:10.1126/science.aan6827 · Cited by 383 · see citing works

The emergent landscape of the mouse gut endoderm at single-cell resolution

Nowotschin, S., Setty, M., Kuo, Y.-Y., Liu, V., Garg, V., Sharma, R., Simon, C. S., Saiz, N., Gardner, R., Boutet, S. C., et al. (2019) · Nature · doi:10.1038/s41586-019-1127-1 · Cited by 383 · see citing works

The Drosophila embryo at single-cell transcriptome resolution

Karaiskos, N., Wahle, P., Alles, J., Boltengagen, A., Ayoub, S., Kipar, C., Kocks, C., Rajewsky, N., & Zinzen, R. P. (2017) · Science · doi:10.1126/science.aan3235 · Cited by 382 · see citing works

Single-Cell Transcriptomics Meets Lineage Tracing

Kester, L., & van Oudenaarden, A. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2018.04.014 · Cited by 375 · see citing works

Gastrulation: Making and Shaping Germ Layers

Solnica‐Krezel, L., & Sepich, D. S. (2011) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-092910-154043 · Cited by 366 · see citing works

Molecular recording of mammalian embryogenesis

Chan, M. M., Smith, Z. D., Grosswendt, S., Kretzmer, H., Norman, T. M., Adamson, B., Jost, M., Quinn, J. J., Yang, D., Jones, M. G., et al. (2019) · Nature · doi:10.1038/s41586-019-1184-5 · Cited by 364 · see citing works

Developmental barcoding of whole mouse via homing CRISPR

Kalhor, R., Kalhor, K., Mejia, L., Leeper, K., Graveline, A., Mali, P., & Church, G. M. (2018) · Science · doi:10.1126/science.aat9804 · Cited by 363 · see citing works

Revealing the Critical Regulators of Cell Identity in the Mouse Cell Atlas

(2018) · doi:10.1016/j.celrep.2018.10.045 · Cited by 341 · see citing works

Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq

Chen, J., Suo, S., Tam, P. P., Han, J.-D. J., Peng, G., & Jing, N. (2017) · Nature Protocols · doi:10.1038/nprot.2017.003 · Cited by 339 · see citing works

Reconstituting the transcriptome and DNA methylome landscapes of human implantation

Zhou, F., Wang, R., Yuan, P., Ren, Y., Mao, Y., Li, R., Lian, Y., Li, J., Wen, L., Yan, L., et al. (2019) · Nature · doi:10.1038/s41586-019-1500-0 · Cited by 326 · see citing works

Using networks to measure similarity between genes: association index selection

Bass, J. I. F., Diallo, A., Nelson, J., Soto, J. M., Myers, C. L., & Walhout, A. J. M. (2013) · Nature Methods · doi:10.1038/nmeth.2728 · Cited by 315 · see citing works

Self-assembly of embryonic and two extra-embryonic stem cell types into gastrulating embryo-like structures

Sözen, B., Amadei, G., Cox, A. L., Wang, R., Na, E., Czukiewska, S. M., Chappell, L., Voet, T., Michel, G., Jing, N., et al. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0147-7 · Cited by 311 · see citing works

A unifying concept: the history of cell theory

Mazzarello, P. (1999) · Nature Cell Biology · doi:10.1038/8964 · Cited by 307 · see citing works

Resolving early mesoderm diversification through single-cell expression profiling

Scialdone, A., Tanaka, Y., Jawaid, W., Moignard, V., Wilson, N. K., Macaulay, I. C., Marioni, J. C., & Göttgens, B. (2016) · Nature · doi:10.1038/nature18633 · Cited by 293 · see citing works

Exploring Single-Cell Data with Deep Multitasking Neural Networks

Amodio, M., van Dijk, D., Srinivasan, K., Chen, W. S., Mohsen, H., Moon, K. R., Campbell, A., Zhao, Y.-J., Wang, X.-M., Venkataswamy, M., et al. (2017) · Nature Methods · doi:10.1038/s41592-019-0576-7 · Cited by 288 · see citing works

The mid-developmental transition and the evolution of animal body plans

Levin, M., Anavy, L., Cole, A. G., Winter, E. E., Mostov, N., Khair, S., Senderovich, N., Kovalev, E., Silver, D. H., Feder, M., et al. (2016) · Nature · doi:10.1038/nature16994 · Cited by 283 · see citing works

Cell fate, morphogenetic movement and population kinetics of embryonic endoderm at the time of germ layer formation in the mouse

Lawson, K. A., Pedersen, R. A., & van de Geer, S. (1987) · Development · doi:10.1242/dev.101.3.627 · Cited by 279 · see citing works

Endoderm development: from patterning to organogenesis

Grapin‐Botton, A., & Melton, D. A. (2000) · Trends in Genetics · doi:10.1016/s0168-9525(99)01957-5 · Cited by 279 · see citing works

Gene expression cartography

Nitzan, M., Karaiskos, N., Friedman, N., & Rajewsky, N. (2019) · Nature · doi:10.1038/s41586-019-1773-3 · Cited by 272 · see citing works

Using single-cell genomics to understand developmental processes and cell fate decisions

Griffiths, J. A., Scialdone, A., & Marioni, J. C. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178046 · Cited by 250 · see citing works

CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues

Stoltzfus, C. R., Filipek, J., Gern, B. H., Olin, B. E., Leal, J. M., Wu, Y., Lyons‐Cohen, M. R., Huang, J. Y., Paz-Stoltzfus, C. L., Plumlee, C. R., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107523 · Cited by 241 · see citing works

Single-cell RNA-sequencing: The future of genome biology is now

Picelli, S. (2016) · RNA Biology · doi:10.1080/15476286.2016.1201618 · Cited by 237 · see citing works

Spatial Transcriptome for the Molecular Annotation of Lineage Fates and Cell Identity in Mid-gastrula Mouse Embryo

Peng, G., Suo, S., Chen, J., Chen, W., Liu, C. X., Fang, Y., Wang, R., Chen, S., Sun, N., Cui, G., et al. (2016) · Developmental Cell · doi:10.1016/j.devcel.2016.02.020 · Cited by 235 · see citing works

Concepts and limitations for learning developmental trajectories from single cell genomics

Tritschler, S., Büttner, M., Fischer, D. S., Lange, M., Bergen, V., Lickert, H., & Theis, F. J. (2019) · Development · doi:10.1242/dev.170506 · Cited by 233 · see citing works

Molecular architecture of lineage allocation and tissue organization in early mouse embryo

Peng, G., Suo, S., Cui, G., Yu, F., Wang, R., Chen, J., Chen, S., Liu, Z., Chen, G., Qian, Y., et al. (2019) · Nature · doi:10.1038/s41586-019-1469-8 · Cited by 223 · see citing works

Deconstructing and reconstructing the mouse and human early embryo

Shahbazi, M. N., & Zernicka‐Goetz, M. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0144-x · Cited by 218 · see citing works

Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies

Lafzi, A., Moutinho, C., Picelli, S., & Heyn, H. (2018) · Nature Protocols · doi:10.1038/s41596-018-0073-y · Cited by 218 · see citing works

Single-cell transcriptomics unveils gene regulatory network plasticity

Iacono, G., Massoni-Badosa, R., & Heyn, H. (2019) · Genome Biology · doi:10.1186/s13059-019-1713-4 · Cited by 218 · see citing works

Genomic Analysis at the Single-Cell Level

Tomer Kalisky, C., Blainey, P. C., & Quake, S. R. (2011) · Annual Review of Genetics · doi:10.1146/annurev-genet-102209-163607 · Cited by 203 · see citing works

In vitro culture of cynomolgus monkey embryos beyond early gastrulation

Ma, H., Zhai, J., Wan, H., Jiang, X., Wang, X., Wang, L., Xiang, Y., He, X., Zhao, Z., Zhao, B., et al. (2019) · Science · doi:10.1126/science.aax7890 · Cited by 203 · see citing works

Using neural networks for reducing the dimensions of single-cell RNA-Seq data

Lin, C., Jain, S., Kim, H., & Bar-Joseph, Z. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx681 · Cited by 197 · see citing works

Dissecting primate early post-implantation development using long-term in vitro embryo culture

Niu, Y., Sun, N., Li, C., Lei, Y., Huang, Z., Wu, J., Si, C., Dai, X., Liu, C., Wei, J., et al. (2019) · Science · doi:10.1126/science.aaw5754 · Cited by 185 · see citing works

Unravelling cellular relationships during development and regeneration using genetic lineage tracing

Baron, C. S., & van Oudenaarden, A. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0186-3 · Cited by 180 · see citing works

Spatiotemporal transcriptomics reveals the evolutionary history of the endoderm germ layer

Hashimshony, T., Feder, M., Levin, M., Hall, B. K., & Yanai, I. (2014) · Nature · doi:10.1038/nature13996 · Cited by 170 · see citing works

A pooled single-cell genetic screen identifies regulatory checkpoints in the continuum of the epithelial-to-mesenchymal transition

McFaline‐Figueroa, J. L., Hill, A. J., Qiu, X., Jackson, D. L., Shendure, J., & Trapnell, C. (2019) · Nature Genetics · doi:10.1038/s41588-019-0489-5 · Cited by 166 · see citing works

Single-cell 5hmC sequencing reveals chromosome-wide cell-to-cell variability and enables lineage reconstruction

Mooijman, D., Dey, S. S., Boisset, J.-C., Crosetto, N., & van Oudenaarden, A. (2016) · Nature Biotechnology · doi:10.1038/nbt.3598 · Cited by 165 · see citing works

Metabolism in Pluripotent Stem Cells and Early Mammalian Development

Zhang, J., Zhao, J., Dahan, P., Lu, V., Zhang, C., Li, H., & Teitell, M. A. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.01.008 · Cited by 163 · see citing works

AutoImpute: Autoencoder based imputation of single-cell RNA-seq data

Talwar, D., Mongia, A., Sengupta, D., & Majumdar, A. (2018) · Scientific Reports · doi:10.1038/s41598-018-34688-x · Cited by 163 · see citing works

SCORPIUS improves trajectory inference and identifies novel modules in dendritic cell developmentPreprint

Cannoodt, R., Saelens, W., Sichien, D., Tavernier, S. J., Janssens, S., Guilliams, M., Lambrecht, B. N., Preter, K. D., & Saeys, Y. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/079509 · Cited by 159 · see citing works

The developmental hourglass model: a predictor of the basic body plan?

Irie, N., & Kuratani, S. (2014) · Development · doi:10.1242/dev.107318 · Cited by 157 · see citing works

SOX17 links gut endoderm morphogenesis and germ layer segregation

Viotti, M., Nowotschin, S., & Hadjantonakis, A.-K. (2014) · Nature Cell Biology · doi:10.1038/ncb3070 · Cited by 150 · see citing works

Timing of developmental events in the early mouse embryo

Kojima, Y., Tam, O. H., & Tam, P. (2014) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2014.06.010 · Cited by 144 · see citing works

Giotto, a toolbox for integrative analysis and visualization of spatial expression dataPreprint

Dries, R., Zhu, Q., Dong, R., Eng, C.-H. L., Li, H., Liu, K., Fu, Y., Zhao, T., Sarkar, A., Bao, F., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/701680 · Cited by 138 · see citing works

Gut-like ectodermal tissue in a sea anemone challenges germ layer homology

Steinmetz, P. R. H., Aman, A. J., Kraus, J. E. M., & Technau, U. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0285-5 · Cited by 135 · see citing works

The Dynamics of Morphogenesis in the Early Mouse EmbryoPreprint

Rivera‐Pérez, J. A., & Hadjantonakis, A. (2014) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a015867 · Cited by 127 · see citing works

Cell fate decisions: emerging roles for metabolic signals and cell morphology

Tatapudy, S., Aloisio, F. M., Barber, D. L., & Nystul, T. G. (2017) · EMBO Reports · doi:10.15252/embr.201744816 · Cited by 123 · see citing works

The evolution of early animal embryos: conservation or divergence?

Kalinka, A. T., & Tomančák, P. (2012) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2012.03.007 · Cited by 122 · see citing works

Prospective isolation and global gene expression analysis of definitive and visceral endoderm

Sherwood, R. I., Jitianu, C., Cleaver, O., Shaywitz, D. A., Lamenzo, J. O., Chen, A. E., Golub, T. R., & Melton, D. A. (2007) · Developmental Biology · doi:10.1016/j.ydbio.2007.01.011 · Cited by 122 · see citing works

Deconstructing the pluripotency gene regulatory network

Li, M., & Belmonte, J. C. I. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0067-6 · Cited by 116 · see citing works

Cell segmentation-free inference of cell types from in situ transcriptomics data

Park, J., Choi, W., Tiesmeyer, S., Long, B., Borm, L. E., Garren, E. J., Nguyen, T. N., Tasic, B., Codeluppi, S., Graf, T., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23807-4 · Cited by 116 · see citing works

Power in Numbers: Single-Cell RNA-Seq Strategies to Dissect Complex Tissues

Birnbaum, K. D. (2018) · Annual Review of Genetics · doi:10.1146/annurev-genet-120417-031247 · Cited by 113 · see citing works

Single-cell technologies sharpen up mammalian stem cell research

Hoppe, P. S., Coutu, D. L., & Schroeder, T. (2014) · Nature Cell Biology · doi:10.1038/ncb3042 · Cited by 104 · see citing works

Single-Cell Transcriptional Analysis

Wu, A. R., Wang, J., Streets, A., & Huang, Y. (2017) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-061516-045228 · Cited by 104 · see citing works

How Single-Cell Genomics Is Changing Evolutionary and Developmental Biology

Marioni, J. C., & Arendt, D. (2017) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100616-060818 · Cited by 104 · see citing works

Neuroectodermal fate of epiblast cells in the distal region of the mouse egg cylinder: implication for body plan organization during early embryogenesis

Quinlan, G. A., Williams, E. A., Tan, S., & Tam, P. (1995) · Development · doi:10.1242/dev.121.1.87 · Cited by 102 · see citing works

The endoderm: a divergent cell lineage with many commonalities

Nowotschin, S., Hadjantonakis, A.-K., & Campbell, K. (2019) · Development · doi:10.1242/dev.150920 · Cited by 94 · see citing works

In toto live imaging of mouse morphogenesis and new insights into neural tube closure

Massarwa, R., & Niswander, L. A. (2012) · Development · doi:10.1242/dev.085001 · Cited by 78 · see citing works

Live Imaging of Whole Mouse Embryos during Gastrulation: Migration Analyses of Epiblast and Mesodermal Cells

Ichikawa, T., Nakazato, K., Keller, P., Kajiura‐Kobayashi, H., Stelzer, E. H. K., Mochizuki, A., & Nonaka, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064506 · Cited by 77 · see citing works

Single‐cell technologies are revolutionizing the approach to rare cells

Proserpio, V., & Lönnberg, T. (2015) · Immunology and Cell Biology · doi:10.1038/icb.2015.106 · Cited by 76 · see citing works

Regionalization of cell fates and cell movement in the endoderm of the mouse gastrula and the impact of loss of Lhx1(Lim1) function

Tam, P., Khoo, P., Wong, N., Tsang, T. E., & Behringer, R. R. (2004) · Developmental Biology · doi:10.1016/j.ydbio.2004.07.005 · Cited by 71 · see citing works

Sequential formation and resolution of multiple rosettes drive embryo remodelling after implantation

Christodoulou, N., Kyprianou, C., Weberling, A., Wang, R., Cui, G., Peng, G., Jing, N., & Zernicka‐Goetz, M. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0211-3 · Cited by 60 · see citing works

Mouse knockout models reveal largely dispensable but context-dependent functions of lncRNAs during development

Han, X., Luo, S., Peng, G., Lu, J. Y., Cui, G., Liu, L., Yan, P., Yin, Y., Liu, W., Wang, R., et al. (2018) · Journal of Molecular Cell Biology · doi:10.1093/jmcb/mjy003 · Cited by 57 · see citing works

Oct4 regulates the embryonic axis and coordinates exit from pluripotency and germ layer specification in the mouse embryo

Mulas, C., Chia, G., Jones, K., Hodgson, A. C., Stirparo, G. G., & Nichols, J. (2018) · Development · doi:10.1242/dev.159103 · Cited by 41 · see citing works

Mapping vertebrate embryos

Tam, P., & Quinlan, G. A. (1996) · Current Biology · doi:10.1016/s0960-9822(02)00432-3 · Cited by 39 · see citing works

Spatial transcriptomics: putting genome-wide expression on the map

Maynard, K. R., Jaffe, A. E., & Martinowich, K. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-019-0484-7 · Cited by 25 · see citing works

Dynamics of Wnt activity on the acquisition of ectoderm potency in epiblast stem cells

Osteil, P., Studdert, J. B., Goh, H. N., Wilkie, E. E., Fan, X., Khoo, P., Peng, G., Salehin, N., Knowles, H., Han, J. J., et al. (2019) · Development · doi:10.1242/dev.172858 · Cited by 22 · see citing works

AutoGenome: An AutoML tool for genomic research

Liu, D., Xu, C., He, W., Xu, Z., Fu, W., Zhang, L., Yang, J., Wang, Z., Liu, B., Peng, G., et al. (2021) · Artificial Intelligence in the Life Sciences · doi:10.1016/j.ailsci.2021.100017 · Cited by 19 · see citing works

Concerted cell divisions in embryonic visceral endoderm guide anterior visceral endoderm migration

Antonica, F., Orietti, L. C., Mort, R. L., & Zernicka‐Goetz, M. (2019) · Developmental Biology · doi:10.1016/j.ydbio.2019.03.016 · Cited by 12 · see citing works

The trickiest family tree in biology

Callaway, E. (2017) · Nature · doi:10.1038/547020a · Cited by 9 · see citing works

Spatial Transcriptomics: Constructing a Single-Cell Resolution Transcriptome-Wide Expression Atlas

Achim, K., Vergara, H. M., & Pettit, J. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7213-5_7 · Cited by 4 · see citing works

CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid TissuesPreprint

Stoltzfus, C. R., Filipek, J., Gern, B. H., et al. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3493253 · Cited by 3 · see citing works

The technological landscape and applications of single-cell multi-omics

Baysoy, A., Bai, Z., Satija, R., & Fan, R. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00615-w · Cited by 1,037 · see citing works

Computational principles and challenges in single-cell data integration

Argelaguet, R., Cuomo, A. S. E., Stegle, O., & Marioni, J. C. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00895-7 · Cited by 472 · see citing works

Clinical and translational values of spatial transcriptomics

Zhang, L., Chen, D., Song, D., Liu, X., Zhang, Y., Xu, X., & Wang, X. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00960-w · Cited by 212 · see citing works

Computational approaches and challenges in spatial transcriptomics

Fang, S., Chen, B., Zhang, Y., Sun, H., Liu, L., Liu, S., Li, Y., & Xu, X. (2023) · Genomics, Proteomics & Bioinformatics · doi:10.1016/j.gpb.2022.10.001 · Cited by 159 · see citing works

Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer’s disease: review, recommendation, implementation and application

Wang, M., Song, W., Chen, M., Wang, Q., Zhou, X., Xu, P., Krek, A., Yoon, Y., Ho, L., Orr, M. E., et al. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00517-z · Cited by 100 · see citing works

Connecting past and present: single-cell lineage tracing

Chen, C., Liao, Y., & Peng, G. (2022) · Protein & Cell · doi:10.1007/s13238-022-00913-7 · Cited by 93 · see citing works

Sample-multiplexing approaches for single-cell sequencing

Zhang, Y., Xu, S., Wen, Z., Gao, J., Li, S., Weissman, S. M., & Pan, X. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04482-0 · Cited by 40 · see citing works

Single-cell and spatial transcriptomics: Advances in heart development and disease applications

Long, X., Yuan, X., & Du, J. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.04.007 · Cited by 37 · see citing works

Spatial molecular anatomy of germ layers in the gastrulating cynomolgus monkey embryo

Cui, G., Feng, S., Yan, Y., Wang, L., He, X., Li, X., Duan, Y., Chen, J., Tang, K., Zheng, P., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111285 · Cited by 35 · see citing works

Spatially resolved transcriptomics: advances and applications

Duan, H., Cheng, T., & Cheng, H. (2022) · Blood Science · doi:10.1097/bs9.0000000000000141 · Cited by 34 · see citing works

Three-dimensional molecular architecture of mouse organogenesis

Qu, F., Li, W., Xu, J., Zhang, R., Ke, J., Ren, X.-D., Meng, X., Qin, L., Zhang, J., Lu, F., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40155-7 · Cited by 28 · see citing works

Time space and single-cell resolved tissue lineage trajectories and laterality of body plan at gastrulation

Wang, R., Yang, X., Chen, J., Zhang, L., Griffiths, J. A., Cui, G., Chen, Y., Qian, Y., Peng, G., Li, J., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41482-5 · Cited by 28 · see citing works

Integration of Computational Analysis and Spatial Transcriptomics in Single-Cell Studies

Wang, R., Peng, G., Tam, P., & Jing, N. (2022) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2022.06.006 · Cited by 26 · see citing works

Potential applications of deep learning in single-cell RNA sequencing analysis for cell therapy and regenerative medicine

Yan, R., Fan, C., Yin, Z., Wang, T., & Chen, X. (2021) · Stem Cells · doi:10.1002/stem.3336 · Cited by 26 · see citing works

Noninvasive metabolic profiling of cumulus cells, oocytes, and embryos via fluorescence lifetime imaging microscopy: a mini-review

Venturas, M., Yang, X., Sakkas, D., & Needleman, D. (2023) · Human Reproduction · doi:10.1093/humrep/dead063 · Cited by 26 · see citing works

Significance of single-cell and spatial transcriptomes in cell biology and toxicology

Wu, D., Liu, X., Zhang, J., Li, L., & Wang, X. (2021) · Cell Biology and Toxicology · doi:10.1007/s10565-020-09576-8 · Cited by 20 · see citing works

Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Ascensión, A. M., Araúzo-Bravo, M. J., & Izeta, A. (2022) · Life · doi:10.3390/life12010067 · Cited by 19 · see citing works

AutoGenome: An AutoML tool for genomic research

Liu, D., Xu, C., He, W., Xu, Z., Fu, W., Zhang, L., Yang, J., Wang, Z., Liu, B., Peng, G., et al. (2021) · Artificial Intelligence in the Life Sciences · doi:10.1016/j.ailsci.2021.100017 · Cited by 19 · see citing works

Single‐cell and spatial transcriptomics: Discovery of human placental development and disease

Tang, M., Xiong, L., Cai, J., Li, F., Huang, C., Zhang, S., Jin, Y., Luo, E., Xing, S., & Yang, X. (2024) · FASEB BioAdvances · doi:10.1096/fba.2024-00133 · Cited by 15 · see citing works

Advances in CRISPR ‐Cas9 in lineage tracing of model animals

Cao, J., Guo, Z., Xu, X., Li, P., Fang, Y., & Deng, S. (2025) · Animal Models and Experimental Medicine · doi:10.1002/ame2.70033 · Cited by 14 · see citing works

Multi-omics in exploring the pathophysiology of diabetic retinopathy

Li, X., Dong, X., Zhang, W., Shi, Z., Liu, Z., Sa, Y., Li, L., Ni, N., & Mei, Y. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1500474 · Cited by 12 · see citing works

Spatial Omics Sequencing Based on Microfluidic Array Chips

Shi, J., Pan, Y., Liu, X., Cao, W., Mu, Y., & Zhu, Q. (2023) · Biosensors · doi:10.3390/bios13070712 · Cited by 9 · see citing works

DenoiseST: A dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomicsPreprint

Cui, Y., Wang, R., Zeng, X., Cui, Y., Zhu, Z., Nakai, K., Ye, X., Sakurai, T., & Wei, L. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.04.583438 · Cited by 10 · see citing works

Extrapolating heterogeneous time-series gene expression data using Sagittarius

Woicik, A., Zhang, M., Chan, J., Ma, J., & Wang, S. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00679-5 · Cited by 8 · see citing works

Single‐Cell Sequencing to Unveil the Mystery of Embryonic Development

Li, Z., Lin, F., Zhong, C., Wang, S., Xue, X., & Shao, Y. (2021) · Advanced Biology · doi:10.1002/adbi.202101151 · Cited by 8 · see citing works

Cloning by SCNT: Integrating Technical and Biology-Driven Advances

Moura, M. T. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-3064-8_1 · Cited by 7 · see citing works

Decoding and recoding plant development

Guiziou, S., Chu, J. C., & Nemhauser, J. L. (2021) · PLANT PHYSIOLOGY · doi:10.1093/plphys/kiab336 · Cited by 7 · see citing works

A Unified Probabilistic Framework for Modeling and Inferring Spatial Transcriptomic Data

Huang, Z., Luo, S., Zhang, Z., Wang, Z., Zhou, T., & Zhang, J. (2023) · Current Bioinformatics · doi:10.2174/1574893618666230529145130 · Cited by 6 · see citing works

Spatially and Temporally Distributed Complexity—A Refreshed Framework for the Study of GRN Evolution

Minelli, A., & Valero‐Gracia, A. (2022) · Cells · doi:10.3390/cells11111790 · Cited by 5 · see citing works

The molecular and cellular choreography of early mammalian lung development

Yang, X., Chen, Y., Yang, Y., Li, S., Mi, P., & Jing, N. (2024) · Medical Review · doi:10.1515/mr-2023-0064 · Cited by 3 · see citing works

Understanding the Transcriptomic Landscape to Drive New Innovations in Musculoskeletal Regenerative Medicine

Thomas, S. M., Ackert‐Bicknell, C. L., Zuscik, M. J., & Payne, K. A. (2022) · Current Osteoporosis Reports · doi:10.1007/s11914-022-00726-x · Cited by 3 · see citing works

Spatial and Molecular Anatomy of Germ Layers in the Gastrulating Cynomolgus Monkey EmbryoPreprint

Cui, G., Feng, S., Yan, Y., Wang, L., He, X., Li, X., Duan, Y., Chen, J., Tam, P., Tang, K., et al. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4022697 · Cited by 2 · see citing works

MCFST: spatial domain identification method based on multi-view graph convolutional network and graph fusion network

Zhang, Z., Duan, H., & Gao, X. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag469 · Cited by 1 · see citing works

A Comparative Study of Computational Methods for Multimodal Single-Cell Data Integration

Tran, B., Pham, T. N., Huynh, T. V., & Hoàng, K. V. (2023) · International Conference on Multimedia Analysis and Pattern Recognition (MAPR) · doi:10.1109/mapr59823.2023.10289050 · Cited by 1 · see citing works

Time, Space and Single-Cell Resolved Molecular Trajectory of Cell Populations and the Laterality of the Body Plan at GastrulationPreprint

Wang, R., Yang, X., Chen, J., Zhang, L., Griffiths, J. A., Cui, G., Chen, Y., Qian, Y., Peng, G., Li, J., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.19.537134

Photolabile oligonucleotides combined with topologically imposed light gradients enable spatially resolved single-cell transcriptomics and epigenomicsPreprint

Piscopio, R. A., Chialastri, A., Wang, C. R., Godzik, M., Heom, K. A., Wang, W., Wilson, M. Z., & Dey, S. S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.01.679703

Multi-omics analyses reveal DjTcf4 critical for proper timing of differentiation in planarian regeneration

Wang, H., Lu, M., Huang, L., Zou, X., Liu, H., Gao, Y., Song, X., Li, M., Zhou, Y., Guo, Z., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116551

Constructing the spatiotemporal atlas of single-cell lineage trajectories in stereotypic biological structures

Wang, R., Yang, X., Lian, C., Wang, J., Chen, J., Qian, Y., Xu, Y., Wang, L., Marioni, J. C., Tam, P., et al. (2025) · iScience · doi:10.1016/j.isci.2025.114307

Single-cell atlas links epithelial state transitions and inferred microenvironmental signaling to pyloric caeca expansion, a digestion-related trait, in mandarin fish (Siniperca chuatsi)

Feng, J., Wang, J., Xu, G., Tao, Y., Miao, X., Wang, R., Xu, H., & Li, Y. (2026) · Aquaculture · doi:10.1016/j.aquaculture.2026.744112

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Cui, Y., Cui, Y., Wang, R., Zeng, X., Zhu, Z., Yi, D., Guo, R., Sakurai, T., Nakai, K., Ye, X., et al. (2026) · Advanced Intelligent Systems · doi:10.1002/aisy.70429

Single Cell and Spatial Omics Korea (SCSOK)-Institute for Basic Science (IBS) Joint Symposium

Park, J., Kim, J., & Lee, H. (2026) · KOBRA Reports · doi:10.64066/kobrareports.26.0009

Photolabile oligonucleotides with topological light gradients enable spatially resolved single-cell transcriptomics and epigenomics

Piscopio, R. A., Chialastri, A., Wang, C., Godzik, M., Heom, K. A., Wang, W., Li, L., Saxena, N., Wilson, M. Z., & Dey, S. S. (2026) · Nature Biotechnology · doi:10.1038/s41587-026-03328-5

Resolving Cell Fate: Experimental, computational and mathematical methods in single cell transcriptomic analysis

Jawaid, W. (2019) · Apollo (University of Cambridge) · doi:10.17863/cam.45316

Spatial Transcriptome for the Molecular Annotation of Lineage Fates and Cell Identity in Mid-gastrula Mouse Embryo

Peng, G., Suo, S., Chen, J., Chen, W., Liu, C. X., Fang, Y., Wang, R., Chen, S., Sun, N., Cui, G., et al. (2016) · Developmental Cell · doi:10.1016/j.devcel.2016.02.020 · Cited by 235 · see citing works

Comments on ‘Molecular architecture of lineage allocation and tissue organization in early mouse embryo’

Cui, G., Jing, N., & Peng, G. (2019) · Journal of Molecular Cell Biology · doi:10.1093/jmcb/mjz101

Single-cell transcriptional profiling: a window into embryonic cell-type specification

Pijuan-Sala, B., Guibentif, C., & Göttgens, B. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0002-5 · Cited by 57 · see citing works

Regulatory network characterization in development: challenges and opportunities

Peng, G., & Han, J.-D. J. (2018) · F1000Research · doi:10.12688/f1000research.15271.1 · Cited by 5 · see citing works