18 papers · ranked by Valyu relevance
Scott F. Daniel, Changkyu Lee, Tyler Mollenkopf, Matthew Lee + 25 more
Single-cell mapping methods convert raw, heterogeneous single-cell datasets into interpretable and comparable representations of biological identity. As reference cell-type taxonomies mature, mapping new datasets to shared references has become a central strategy for enabling cross-study integration, reproducible…
Zehua Zeng, Xuehai Wang, Hongwu Du
Single-cell RNA sequencing has revolutionized cellular biology, with atlases now encompassing over 100 million cells. However, researchers employ vastly different naming conventions when annotating cell types, creating a fragmented landscape that severely impedes data integration and comparative analysis. Here, we…
Alexander J Tarashansky, Jacob M Musser, Margarita Khariton, Pengyang Li + 5 more
'Pengyang Li' 'Detlev Arendt' 'Stephen R Quake' 'Bo Wang' 'Alex K Shalek' 'Naama Barkai'] Comparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex…
Joyce B. Kang, Aparna Nathan, Kathryn Weinand, Fan Zhang + 5 more
Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto…
Tan, Shawn Zheng Kai, Puig-Barbe, Aleix + 66 more
Shawn Zheng Kai Tan 1,2,\ , Aleix Puig-Barbe 2,\ , Damien Goutte-Gattat 3,4 , Caroline Eastwood 5 , Brian Aevermann 6 , Alida Avola 5 , James P Balhoff 7 , Ismail Ugur Bayindir 5 , Jasmine Belfiore 5 , Anita Reane Caron 2 , David S Fischer 8 , Nancy George 9 , Benjamin M Gyori 10 , Melissa A Haendel 11 , Charles Tapley…
Chuan Xu, Martin Prete, Simone Webb, Laura Jardine + 5 more
Harmonizing cell types across the single-cell community and assembling them into a common framework is central to building a standardized Human Cell Atlas. Here we present CellHint, a predictive clustering tree-based tool to resolve cell type differences in annotation resolution and technical biases across datasets.…
Mu Qiao
Identifying evolutionary correspondences between cell types across species is a fundamental challenge in comparative genomics and evolutionary biology. Existing approaches often rely on either reference-based matching, which imposes asymmetry by designating one species as the reference, or projection-based matching…
Aviv Regev, Sarah A. Teichmann, Eric S. Lander, Ido Amit + 54 more
The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body, by undertaking a Human Cell Atlas Project as an international collaborative…
Fang Yin, Qiao Jin, Guangzhi Xiong, Bowen Jin + 5 more
Cell type annotation is a key task in analyzing the heterogeneity of single-cell RNA sequencing data. Although recent foundation models automate this process, they typically annotate cells independently, without considering batch-level cellular context or providing explanatory reasoning. In contrast, human experts…
Jeongbin Park, Sumin Kim, Jiwon Kim, Dongjoo Lee + 4 more
Large-scale single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have transformed biomedical research into a data-driven field, enabling the creation of comprehensive atlases. These methodologies facilitate detailed understanding of biology and pathophysiology; however, the complexity and sheer…
Somya Mani, Tsvi Tlusty
Rapid advance of experimental techniques provides an unprecedented in-depth view into complex developmental processes. Still, little is known on how the complexity of multicellular organisms evolved by elaborating developmental programs and inventing new cell types. A hurdle to understanding developmental evolution is…
Yuling Zhu, Yunfei Hu, Manfei Bella Xie, Haoran Qin + 7 more
Spatial transcriptomics enables the quantification of gene expression within its native tissue context, providing unprecedented insight into tissue architecture, cellular ecosystems, and local cell-cell interactions at regional and single-cell resolution. Accurate cell type annotation is a critical prerequisite for…
Wang Yin, Xiaobin Wu, Linxi Chen, You Wan + 1 more
Accurate mapping between single-cell RNA sequencing (scRNA-seq) and low-resolution spatial transcriptomics (ST) data compensates for both limited resolution of ST data and missing spatial information of scRNA-seq. Celloc, a method developed for this purpose, incorporates a graph attention autoencoder and comprehensive…
Matthew N. Bernstein, Zhongjie Ma, Michael Gleicher, Colin N. Dewey
Cell type annotation is a fundamental task in the analysis of single-cell RNA-sequencing data. In this work, we present CellO, a machine learning-based tool for annotating human RNA-seq data with the Cell Ontology. CellO enables accurate and standardized cell type classification by considering the rich hierarchical…
Dmytro Rizdvanetskyi, Nathan Ross, Pavlo Lutsik
Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in computational biology. Methods that rely on epigenetic marks such as DNA methylation typically operate on aggregated methylation estimates, discarding the pattern-level…
Lucy Ham, Taylor E. Woodford, Megan A. Coomer, Michael P. H. Stumpf
Many cellular processes involve information processing and decision making. We can probe these processes at increasing molecular detail. The analysis of heterogeneous data remains a challenge that requires new ways of thinking about cells in quantitative, predictive, and mechanistic ways. We discuss the role of…
Juerg Straubhaar, Alexandria D’Souza, Zachary Niziolek, Bogdan Budnik
Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling…
Authors not listed
As the volume and diversity of bioactivity data in ChEMBL continues to grow, ensuring that assay metadata is standardized, interoperable, and machine-readable is critical for effective use in cheminformatics and ML applications. In this work, we present recent efforts to enhance the quality and granularity of bioassay…