Results 31-40 of about 359
- scMultiSim: simulation of single-cell multi-omics and spatial data guided by gene regulatory networks and cell–cell inte... new windowSimulated single-cell data are essential for designing and evaluating computational methods in the absence of experimental ground truth. Here we present scMultiSim, a comprehensive simulator that generates multimodal single-cell data encompassing
Date: (2025) Authors: Hechen Li , Ziqi Zhang , Michael Squires , Xi Chen , Xiuwei Zhang Date: 2025-01-01 Authors: Schnormeier AK, Budeus B. Journal: Methods in molecular biology (Clifton, N.J.) - Unraveling cell–cell communication with NicheNet by inferring active ligands from transcriptomics data new windowLigand–receptor interactions constitute a fundamental mechanism of cell–cell communication and signaling. NicheNet is a well-established computational tool that infers ligand–receptor interactions that potentially regulate gene expression changes in
Date: (2025) Authors: Chananchida Sang-aram , Robin Browaeys , Ruth Seurinck , Yvan Saeys - Induced pluripotent stem cell (iPSC)-derived organoids provide models to study human organ development. Single-cell transcriptomics enables highly resolved descriptions of cell states within these systems; however, approaches are needed to directly
Date: (2025) Authors: Eugenio Gentile , Ashley Maynard , Zhisong He , Barbara Treutlein Ref: Lineage Tracing Date: 2024-12-19 Authors: Schott M, León-Periñán D, Splendiani E, Ferretti E, Macino G, Karaiskos N, Rajewsky N. Journal: STAR protocols - Cell–cell communication is essential for tissue development, function and regeneration. The revolution of single-cell genomics technologies offers an unprecedented opportunity to uncover how cells communicate in vivo within their tissue niches and
Date: (2025) Authors: Kevin Troulé , Robert Petryszak , Batuhan Cakir , James Cranley ... Roser Vento-Tormo Date: 2024-11-25 Authors: Kurowski K, Timme S, Föll MC, Backhaus C, Holzner PA, Bengsch B, Schilling O, Werner M, Bronsert P. Journal: Methods and protocols - MVCLST: A spatial transcriptome data analysis pipeline for cell type classification based on multi-view comparative lear... new window
Date: 2024-11-13 Authors: Peng W, Zhang Z, Dai W, Ping Z, Fu X, Liu L, Liu L, Yu N. Journal: Methods (San Diego, Calif.) - This chapter explores the cutting-edge field of in situ phytomicrobiome engineering, employing advanced methodologies to enhance plant–microbe interactions for sustainable agriculture. This chapter delves into the integration of “omics” technologies,
Date: (2025) Authors: Krishnan Ajith Kumar , Lokesh Ravi Ref: Plant Microbiome Engineering - SpaInGNN: Enhanced clustering and integration of spatial transcriptomics based on refined graph neural networks. new window
Date: 2024-11-13 Authors: Zhang F, Shen Z, Huang S, Zhu Y, Yi M. Journal: Methods (San Diego, Calif.)