25 papers · ranked by Valyu relevance
Nimish Magre, Ebtisam Alshehri, Fedor Grab, Yerdos Ordabayev + 3 more
Many single-cell RNA-seq annotation methods ignore the hierarchical nature of cell type classification. We present a probability propagation strategy that enforces ontological consistency and improves performance when applied to existing models without retraining. Combined with a lightweight logistic regression model…
Yinuo Xu, Yan Cui, Mingyao Li, Zhihua Huang
Identifying cell types and subtypes in routine histopathology is fundamental for understanding disease. Existing tilebased models captures nuclear detail but miss the broader tissue context that influences cell identity. Current human annotations are coarse-grained and uneven across studies, making fine-grained…
Shangru Jia, Artem Lysenko, Keith A Boroevich, Alok Sharma + 1 more
Accurate classification of immune cells is crucial for elucidating their diverse roles in health and disease. However, this task remains very challenging in single-cell RNA sequencing (scRNA-seq) data due to the complex and hierarchical relationships of immune cell types. To address this, we introduce scHDeepInsight, a…
Soham Mandal, José Guilherme de Almeida, Nickolas Papanikolaou, Trevor A Graham
Cell segmentation and phenotyping in histopathology samples are essential techniques applied across diagnostic and research workflows. However, annotation by human experts requires significant time and domain expertise and is affected by inter-observer variability. While multiple artificial intelligence methods have…
Joshua Brand, Wei Zhang, Evie Carchman, Huy Q Dinh + 1 more
High-plex immunofluorescence (IF) imaging has significantly expanded our ability to visualize and characterize cell types and subsets, offering detailed views of tissue-level biology. While these technologies have existed for years (, , ), their accessibility through commercial platforms has significantly improved.…
Suqiang Ma, Subhadeep Sengupta, Yao Lee, Beikang Gu + 6 more
Circulating blood cell clusters (CCCs) containing red blood cells (RBCs), white blood cells (WBCs), and platelets are significant biomarkers linked to conditions like thrombosis, infection, and inflammation. Flow cytometry, paired with fluorescence staining, is commonly used to analyze these cell clusters, revealing…
Frances K. Clark, Gauthier Weissbart, Xihang Wang, Kate Harline + 4 more
Arabidopsis leaf epidermal cells have a wide range of sizes and ploidies, but the mechanisms patterning their size and spatial distribution remain unclear. Here, we show that the same genetic pathway creating giant cells in sepals also regulates cell size in the leaf epidermis, leading to the formation of giant cells.…
Gita Mahmoudabadi, Lakshmi Krishnan, Tejaswini Ganapathi, James Pearce + 2 more
Accurate cross-species cell type classification remains a key evaluation task in single-cell transcriptomics. Recent foundation models trained on millions of single-cell profiles demonstrate great in-distribution and out-of-distribution performance on this task, but their large parameter counts and substantial…
Satoshi Tsutsui, Winnie Pang, Shuting He, Bihan Wen
The microscopic examination of white blood cells (WBCs) plays a fundamental role in pathology and is essential for diagnosing blood disorders such as leukemia and anemia. To support further research on WBC images, multiple datasets have been proposed. However, they mainly annotate cell categories, and lack detailed…
Stephen R. Williams, Fedor Grab, Govinda M. Kamath, Yerdos Ordabayev + 13 more
Cell type annotation in single-cell RNA sequencing (scRNA-seq) experiments is the fundamental step of assigning cell types to individual cells or clusters of cells based on their gene expression profiles. This process is crucial for developing biological insights from scRNA-seq experiments. We present a service that…
Min Huang, Rishikesan Kamaleswaran
Accurate and scalable cell type annotation remains a challenge in single-cell transcriptomics, especially when datasets exhibit strong batch effects or contain previously unseen cell populations. Here we introduce SpikGPT, a hybrid deep learning framework that integrates scGPT-derived cell embeddings with a spiking…
Raffaella Fiamma Cabini, Deborah S. Barkauskas, Guangyu Chen, Zhi-Qi Cheng + 18 more
Raffaella Fiamma Cabini1,2,\, Deborah Barkauskas 3 , Guangyu Chen 4 , Zhi-Qi Cheng 4 , David E Cicchetti 5 , Judith Drazba 6 , Rodrigo Fernandez-Gonzalez 7 , Raymond Hawkins 7 , Yujia Hu 6 , Jyoti Kini 8 , Charles LeWarne 4 , Xufeng Lin9,10 , Sai Preethi Nakkina 11 , John W Peterson 6 , Ayushi Singh 12 , Koert Schreurs…
Thomas Bonte, Oriane Pourcelot, Adham Safieddine, Floric Slimani + 5 more
The cell cycle is a series of regulated stages during which a cell grows, replicates its DNA, and divides. It consists of four phases - two growth phases (G1 and G2), a replication phase (S), and a division phase (M) - each characterized by distinct transcriptional programs and impacting most other cellular processes.…
Yuji Takeda, Junji Yokozawa, Risako Yamaguchi, Shinichi Saitoh + 1 more
Biological phenomena include unrecognized events. These unrecognized events often unknowingly increase observer bias, which inhibits open and reproducible science. In this study, we focused on the recognition procedures underlying primary data and modeled cell population behavior. Using agent-based modeling (ABM), we…
Florian Bürger, Gomes, Martim Dias, Nica Gutu + 3 more
Tracking cells in time-lapse videos is an essential technique for monitoring cell population dynamics at a single-cell level. Current methods for cell tracking are developed on videos with mostly single, constant signals and do not detect pivotal events such as cell death. Here, we present TransientTrack, a deep…
Nora Ghenciulescu, Marcel J. Reinders, Ahmed Mahfouz
Transcriptomic differences between individuals and sexes are well-documented across tissues, affecting cell-type identity. Single-cell atlases often have skewed sex ratios or limited donor diversity, potentially leading to sex- or donor-biased annotations using automatic classification methods. This might cause models…
Martin Radvanský, Markéta Vašinková, Miloš Kudělka, Eva Kriegová + 1 more
Accurate quantification of spindle-shaped cells in bright-field microscopy remains challenging due to low contrast, noise, and highly variable cell morphology. Conventional approaches often rely on fluorescent staining or deep learning models, which may introduce phototoxic effects, require extensive training data, or…
Kaden Stillwagon, Alexandra Dunnum VandeLoo, Benjamin Magondu, Craig R. Forest
Instance segmentation enables the analysis of spatial and temporal properties of cells in microscopy images by identifying the pixels belonging to each cell. However, progress is constrained by the scarcity of high-quality labeled microscopy datasets. Many recent approaches address this challenge by initializing models…
Alexandre Porcher Fernandes, Renske M. A. Vroomans, Enrico Sandro Colizzi
During the transition to multicellularity, nascent multicellular organisms evolved reproductive strategies that relied on coordinating behaviour across cells in the group. Cell-cell interactions that once occurred between independent single-celled organisms in an ecological context were integrated into the…
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Vertex models have been established as powerful tools for the cell-based simulation of epithelial tissues as they allow a detailed description of their mechanical development with respect to the properties of individual cells. Thus, they suit the challenges of simulating intestinal organoids which arise from the…
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The Golgi apparatus (GA) orchestrates protein modification, trafficking, and secretion through highly dynamic remodeling, yet its proteomic complexity remains difficult to resolve in living systems. Here, we report CAT-Golgi, a genetically independent and light-controlled photocatalytic proximity labeling strategy for…
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Terminally labeled DNA oligonucleotides have wide applications in modern biology and biotechnological applications. It has been observed that the fluorescent intensity of light released from these fluorescent labels is heavily influenced by the terminal sequence of nucleotides. Recent studies have assayed and published…
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Photosynthetic biohybrids, often in the form of biophotoelectrochemical devices, aim to achieve solar-to-chemical conversion by pairing biotic and abiotic materials, leveraging the beneficial attributes of both. Numerous works have highlighted the importance of a well-tuned bio-electrode interface for high…
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The ability to track therapeutic cells is critical for advancing adoptive cell therapy (ACT). Positron emission tomography (PET) offers sensitive and quantitative imaging, yet improved cell radiolabeling strategies are sorely needed. We report a metabolic glycoengineering (MGE) approach that installs azide moieties on…
Paul Van Liedekerke, Jiří Pešek, Kévin Alessandri, Dirk Drasdo
The fundamental understanding of how cells physically interact with each other and their environment is key to understanding their organisation in living tissues. Over the past decades several computational methods have been developed to decipher emergent multi-cellular behaviors. In particular agent-based (or…