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Massive single-cell profiling efforts have accelerated our discovery of the cellular composition of the human body, while at the same time raising the need to formalise this new knowledge. Here, we review current cell ontology efforts to…

Cell Behavior · Quantitative Biology 2021-11-10 David Osumi-Sutherland , Chuan Xu , Maria Keays , Peter V. Kharchenko , Aviv Regev , Ed Lein , Sarah A. Teichmann

Single-cell omics technologies have transformed our understanding of cellular diversity by enabling high-resolution profiling of individual cells. However, the unprecedented scale and heterogeneity of these datasets demand robust frameworks…

The Human Cell Atlas (HCA) will be made up of comprehensive reference maps of all human cells - the fundamental units of life - as a basis for understanding fundamental human biological processes and diagnosing, monitoring, and treating…

Single-cell datasets often lack individual cell labels, making it challenging to identify cells associated with disease. To address this, we introduce Mixture Modeling for Multiple Instance Learning (MMIL), an expectation maximization…

Quantitative Methods · Quantitative Biology 2024-06-13 Erin Craig , Timothy Keyes , Jolanda Sarno , Maxim Zaslavsky , Garry Nolan , Kara Davis , Trevor Hastie , Robert Tibshirani

Label-free cell classification is advantageous for supplying pristine cells for further use or examination, yet existing techniques frequently fall short in terms of specificity and speed. In this study, we address these limitations through…

Image and Video Processing · Electrical Eng. & Systems 2025-02-25 Khayrul Islam , Ratul Paul , Shen Wang , Yuwen Zhao , Partho Adhikary , Qiying Li , Xiaochen Qin , Yaling Liu

Single-cell reference atlases are large-scale, cell-level maps that capture cellular heterogeneity within an organ using single cell genomics. Given their size and cellular diversity, these atlases serve as high-quality training data for…

Genomics · Quantitative Biology 2022-11-09 Jan Engelmann , Leon Hetzel , Giovanni Palla , Lisa Sikkema , Malte Luecken , Fabian Theis

Single-cell analysis is currently one of the most high-resolution techniques to study biology. The large complex datasets that have been generated have spurred numerous developments in computational biology, in particular the use of…

Genomics · Quantitative Biology 2023-04-27 Ionut Sebastian Mihai , Sarang Chafle , Johan Henriksson

Recent advances in generative models, including large language models (LLMs), vision language models (VLMs), and diffusion models, have accelerated the field of natural language and image processing in medicine and marked a significant…

Single-cell RNA-Sequencing (scRNA-Seq) has undergone major technological advances in recent years, enabling the conception of various organism-level cell atlassing projects. With increasing numbers of datasets being deposited in public…

Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another therefore is of…

Signal Processing · Electrical Eng. & Systems 2021-01-07 Hassan Raji , Muhammad Tayyab , Jianye Sui , Seyed Reza Mahmoodi , Mehdi Javanmard

Many fields, such as neuroscience, are experiencing the vast proliferation of cellular data, underscoring the need for organizing and interpreting large datasets. A popular approach partitions data into manageable subsets via hierarchical…

Quantitative Methods · Quantitative Biology 2024-03-07 Diek W. Wheeler , Giorgio A. Ascoli

Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular…

Digital Libraries · Computer Science 2012-03-05 Ludo Waltman , Nees Jan van Eck

Cell detection is a fundamental task in computational pathology that can be used for extracting high-level medical information from whole-slide images. For accurate cell detection, pathologists often zoom out to understand the tissue-level…

In this work we propose an approach to select the classification method and features, based on the state-of-the-art, with best performance for diagnostic support through peripheral blood smear images of red blood cells. In our case we used…

Machine Learning · Computer Science 2020-10-12 Nataša Petrović , Gabriel Moyà-Alcover , Antoni Jaume-i-Capó , Manuel González-Hidalgo

Over the past decade, the revolution in single-cell sequencing has enabled the simultaneous molecular profiling of various modalities across thousands of individual cells, allowing scientists to investigate the diverse functions of complex…

Computation and Language · Computer Science 2024-12-05 Junhao Liu , Siwei Xu , Lei Zhang , Jing Zhang

DNA methylation is a crucial regulator of gene transcription and has been linked to various diseases, including autoimmune diseases and cancers. However, diagnostics based on DNA methylation face challenges due to large feature sets and…

Machine Learning · Computer Science 2023-08-04 Pengcheng Xu , Jinpu Cai , Yulin Gao , Ziqi Rong

Cell differentiation in multicellular organisms is a complex process whose mechanism can be understood by a reductionist approach, in which the individual processes that control the generation of different cell types are identified.…

To understand the function of cortical circuits it is necessary to classify their underlying cellular diversity. Traditional attempts based on comparing anatomical or physiological features of neurons and glia, while productive, have not…

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