Search · four archives
Search · four archives
25 papers · ranked by Valyu relevance
Kun Wang, Xiao Zhang, Hansen Cheng, Wenhao Ma + 5 more
'Liting Dong' 'Yixiong Gou' 'Jian Yang' 'Haoyang Cai'] Single-cell sequencing has shed light on previously inaccessible biological questions from different fields of research, including organism development, immune function, and disease progression. The number of single-cell-based studies increased dramatically over…
Carlos Prieto, David Barrios, Angela Villaverde
Single-cell RNA sequencing (scRNA-Seq) enables researchers to quantify the transcriptomes of individual cells. The capacity of researchers to perform this type of analysis has allowed researchers to undertake new scientific goals. The usefulness of scRNA-Seq has depended on the development of new computational biology…
Robert A. Amezquita, Vince J. Carey, Lindsay N. Carpp, Ludwig Geistlinger + 12 more
Recent developments in experimental technologies such as single-cell RNA sequencing have enabled the profiling a high-dimensional number of genome-wide features in individual cells, inspiring the formation of large-scale data generation projects quantifying unprecedented levels of biological variation at the…
Marta Bica, Karine Serre, Nuno L. Barbosa-Morais
Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity by providing detailed insights into gene expression at the individual cell level. Despite its potential, the complexity of scRNA-seq data analysis often poses challenges for researchers without computational expertise.…
Weideng Wei, Xiaoqiang Xia, Taiwen Li, Qianming Chen + 1 more
Background In recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from…
Asif Adil, Namrata Bhattacharya, Mohammed Asger
As the field of single-cell genomics continues to develop, the generation of large-scale scRNA-seq datasets has become more prevalent. While these datasets offer tremendous potential for shedding light on the complex biology of individual cells, the sheer volume of data presents significant challenges for management…
Yukie Kashima, Yoshitaka Sakamoto, Keiya Kaneko, Masahide Seki + 2 more
'Yutaka Suzuki' 'Ayako Suzuki'] Here, we review single-cell sequencing techniques for individual and multiomics profiling in single cells. We mainly describe single-cell genomic, epigenomic, and transcriptomic methods, and examples of their applications. For the integration of multilayered data sets, such as the…
Florian Wagner
Single-cell RNA-Seq is a powerful technology that enables the transcriptomic profiling of the different cell populations that make up complex tissues. However, the noisy and high-dimensional nature of the generated data poses significant challenges for its analysis and integration. Here, I describe Monet, an…
Lu Pan, Bufu Tang, Xuan Zhang, Paolo Parini + 17 more
'Joseph Loscalzo' 'Volker M. Lauschke' 'Bradley A. Maron' 'Paola Paci' 'Ingemar Ernberg' 'Nguan Soon Tan' 'Ákos Végvári' 'Zehuan Liao' 'Sundararaman Rengarajan' 'Roman Zubarev' 'Yuxuan Fan' 'Xu Zheng' 'Xinyue Jian' 'Ren Sheng' 'Zhenning Wang' 'Xuexin Li'] Title: Abstract The rapid advancement of multi-omics single-cell…
Jafar Isbarov, Elmir Mahammadov
analysis Authors: ['Jafar Isbarov' 'Elmir Mahammadov'] Single-cell analysis is an increasingly relevant approach in "omics" studies. In the last decade, it has been applied to various fields, including cancer biology, neuroscience, and, especially, developmental biology. This rise in popularity has been accompanied…
Shuang Ge, Shuqing Sun, Huan Xu, Qiang Cheng + 1 more
Advances and Challenges from a Data Science Perspective Authors: ['Shuang Ge' 'Shuqing Sun' 'Huan Xu' 'Qiang Cheng' 'Zhixiang Ren'] The development of single-cell and spatial transcriptomics has revolutionized our capacity to investigate cellular properties, functions, and interactions in both cellular and spatial…
Luke Zappia, Fabian J. Theis
Recent years have seen a revolution in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq). As the number, size and complexity of scRNA-seq datasets continue to increase, so does the number of computational methods and software tools for extracting meaning from them. Since 2016 the scRNA-tools…
Michael A. Ortega, Olivier Poirion, Xun Zhu, Sijia Huang + 3 more
It has become increasingly clear that both normal and cancer tissues are composed of heterogeneous populations. Genetic variation can be attributed to the downstream effects of inherited mutations, environmental factors, or inaccurately resolved errors in transcription and replication. When lesions occur in regions…
Laura Puente-Santamaría, Luis del Peso
Single-cell transcriptomics techniques, such as scRNA-seq, attempt to characterize gene expression profiles in each cell of a heterogeneous sample individually. Due to growing amounts of data generated and the increasing complexity of the computational protocols needed to process the resulting datasets, the demand for…
Shi-Xiong Zhang, Xiangtao Li, Qiuzhen Lin, Ka‐Chun Wong
In this study, we review the existing single-cell RNA-seq data clustering methods with critical insights into the related advantages and limitations. In addition, we also review the upstream singlecell RNA-seq data processing techniques such as quality control, normalization, and dimension reduction. We conduct…
Xinghua Pan
Single-cell analysis heralds a new era that allows “omics” analysis, notably genomics, transcriptomics, epigenomics and proteomics at the single-cell level. It enables the identification of the minor subpopulations that may play a critical role in a biological process of a population of cells, which conventionally are…
H. Robert Frost
Single cell RNA sequencing (scRNA-seq) is a powerful tool for analyzing complex tissues with recent advances enabling the transcriptomic profiling of thousands to tens-of-thousands of individual cells. Although scRNA-seq provides unprecedented insights into the biology of heterogeneous cell populations, analyzing such…
David F. Stein, Huidong Chen, Michael E. Vinyard, Luca Pinello
Single-cell assays have transformed our ability to model heterogeneity within cell populations and tissues. Virtual Reality (VR) has recently emerged as a powerful technology to dynamically explore complex data. However, expensive hardware or advanced data preprocessing skills are required to adapt such technology to…
Allen W. Zhang, Kieran R. Campbell
Single-cell technologies have revolutionized biomedical research by enabling scalable measurement of the genome, transcriptome, and proteome of multiple systems at single-cell resolution. Now widely applied to cancer models, these assays offer new insights into tumour heterogeneity, which underlies cancer initiation…
Mahnoor N. Gondal -, Syed Hamad Hassan Shah, Arul M. Chinnaiyan, Marcin Cieslik
Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of genomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on…
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…
Ionut Sebastian Mihai, Sarang Chafle, Johan Henriksson
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 advanced statistics and machine learning. This review attempts to explain the deeper…
Authors not listed
The Single-probe is a multifunctional device that can be coupled to mass spectrometry (MS) for molecular analysis of microscale samples, such as single cells, tissue slices, and multicellular spheroids, under ambient conditions. In Single-probe single cell MS (SCMS) studies, this technique leverages direct sampling and…
Authors not listed
Single-cell mass spectrometry (SCMS) has emerged as a powerful tool for analyzing metabolites in individual cells, including live cells. However, cell metabolites have rapid turnover rate, whereas maintaining metabolites’ profiles of live cells during sample transport, storage, or extended measurements can be…
Authors not listed
This paper addresses the challenges in cell line development (CLD), the lengthy and ambiguous clone screening in upstream biopharmaceutical production. Typically, only a small subset of the later stages of CLD data is used for manually selecting lead clones. Addressing this issue, we introduce a multivariate data…