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Single-cell technologies

Guest Editor:
David Casero:
 Research Institute at Cedars Sinai Medical Center, USA
Baohua Wang: School of Life Sciences, Nantong University, China

BMC Genomics, BMC Medical Genomics, and BMC Bioinformatics called for submissions to a Collection on Single-cell technologies. Recent years have seen rapid progress in the development of single-cell sequencing technologies. They provide valuable insights into complex biological systems as well as allow researchers to make new discoveries. These powerful methods are used, for example, to generate high resolution transcriptomes, identify complex and rare cell populations, discover regulatory relationships between genes and assess cellular heterogeneity.

Meet the Guest Editors

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David Casero: Research Institute at Cedars Sinai Medical Center, USA

Dr. Casero is an Associate Professor in the Department of Medicine and the Director of Translational Multi-omics in the Inflammatory Bowel & Immunobiology Research Institute at Cedars Sinai Medical Center (Los Angeles, California). Dr. Casero earn his B.A. in Physics and Ph.D. in Applied Mathematics at Complutense University (Spain). He joined UCLA as a postdoctoral fellow in the laboratory of Matteo Pellegrini, where he conducted work on computational biology with a focus on gene regulatory pathways in hematopoiesis, immunity, and inflammation. His work relies on methodologies for the analysis of multi-dimensional sequencing-based databases and comprises both basic studies on mouse and human stem and progenitor cells, along with translational studies for biomarker discovery in inflammatory diseases. Dr. Casero has served in the Editorial Board of BMC Bioinformatics since 2019.

Baohua Wang: School of Life Sciences, Nantong University, China

Dr. Wang is a Professor in the School of Life Sciences at Nantong University. He got his Ph.D. from Nanjing Agricultural University, and worked as a postdoctoral research fellow in the University of Georgia for three years. Currently, he serves as Editorial Board Member for two journals, namely BMC Genomics & Frontiers in Plant Science. As the project leader, he undertook more than 10 scientific research projects including a National Key R & D Project, and published more than 60 relevant academic papers. His research interests focus on molecular genetics, epigenetics, quantitative genetics especially in germplasm enhancement and improvement of crop plants.


 


Recent years have seen rapid progress in the development of single-cell sequencing technologies. They can provide valuable insights into complex biological systems as well as allow researchers to make new discoveries. These powerful methods are used, for example, to generate high resolution transcriptomes, identify complex and rare cell populations, discover regulatory relationships between genes and assess cellular heterogeneity.

This collection welcomed articles presenting novel bioinformatics analysis tools and applications for single cell RNA-Seq data as well as research looking into the potential applications and future directions of single-cell omics sequencing technologies. 

We considered submissions from all aspects of single-cell omics, from a single-cell diagnostic and tracking of human and animal diseases to an evolutionary guided-perspective of single cell tracking through different stages of development and/or species.

The scope of this cross journal collection between BMC Genomics, BMC Bioinformatics and BMC Medical Genomics encompassed all realms of life, from prokaryotes to eukaryotes.  

Image credit: © Paulista / stock.adobe.com

  1. With the growing number of single-cell datasets collected under more complex experimental conditions, there is an opportunity to leverage single-cell variability to reveal deeper insights into how cells respon...

    Authors: Jamshaid A. Shahir, Natalie Stanley and Jeremy E. Purvis
    Citation: BMC Bioinformatics 2024 25:25
  2. Cell type-specific differential gene expression analyses based on single-cell transcriptome datasets are sensitive to the presence of cell-free mRNA in the droplets containing single cells. This so-called ambi...

    Authors: Marijn Berg, Ilya Petoukhov, Inge van den Ende, Kerstin B. Meyer, Victor Guryev, Judith M. Vonk, Orestes Carpaij, Martin Banchero, Rudi W. Hendriks, Maarten van den Berge and Martijn C. Nawijn
    Citation: BMC Genomics 2023 24:722
  3. Acute myeloid leukaemia (AML) is characterised by the malignant accumulation of myeloid progenitors with a high recurrence rate after chemotherapy. Blasts (leukaemia cells) exhibit a complete myeloid different...

    Authors: Nan Shao, Chenshuo Ren, Tianyuan Hu, Dianbing Wang, Xiaofan Zhu, Min Li, Tao Cheng, Yingchi Zhang and Xian-En Zhang
    Citation: BMC Bioinformatics 2023 24:450
  4. Single-cell RNA sequencing (scRNA-seq) is a powerful tool for investigating cell abundance changes during tissue regeneration and remodeling processes. Differential cell abundance supports the initial clusteri...

    Authors: Juan Domingo, Oleksandra Kutsyr-Kolesnyk, Teresa Leon, Raul Perez-Moraga, Guillermo Ayala and Beatriz Roson
    Citation: BMC Bioinformatics 2023 24:440
  5. Deep generative models naturally become nonlinear dimension reduction tools to visualize large-scale datasets such as single-cell RNA sequencing datasets for revealing latent grouping patterns or identifying o...

    Authors: Gwangwoo Kim and Hyonho Chun
    Citation: BMC Bioinformatics 2023 24:432
  6. High-throughput experiments provide deep insight into the molecular biology of different species, but more tools need to be developed to handle this type of data. At the transcriptomics level, quantitative Pol...

    Authors: Alexis Germán Murillo Carrasco, Tatiane Katsue Furuya, Miyuki Uno, Tharcisio Citrangulo Tortelli Jr and Roger Chammas
    Citation: BMC Bioinformatics 2023 24:402
  7. The cellular and molecular dynamics of human prepuce are crucial for understanding its biological and physiological functions, as well as the prevention of related genital diseases. However, the cellular compo...

    Authors: Fei Tan, Yuan Xuan, Lan Long, Yang Yu, Chunhua Zhang, Pengchen Liang, Yaoqun Wang, Meiyu Chen, Jiling Wen and Geng Chen
    Citation: BMC Genomics 2023 24:514
  8. Here we present scSNPdemux, a sample demultiplexing pipeline for single-cell RNA sequencing data using natural genetic variations in humans. The pipeline requires alignment files from Cell Ranger (10× Genomics...

    Authors: John K. L. Wong, Lena Jassowicz, Christel Herold-Mende, Martina Seiffert, Jan-Philipp Mallm, Peter Lichter and Marc Zapatka
    Citation: BMC Bioinformatics 2023 24:326
  9. A common feature of single-cell RNA-seq (scRNA-seq) data is that the number of cells in a cell cluster may vary widely, ranging from a few dozen to several thousand. It is not clear whether scRNA-seq data from...

    Authors: Yong Liu, Jing Huang, Rajan Pandey, Pengyuan Liu, Bhavika Therani, Qiongzi Qiu, Sridhar Rao, Aron M. Geurts, Allen W. Cowley Jr, Andrew S. Greene and Mingyu Liang
    Citation: BMC Genomics 2023 24:371
  10. The primary pathological alterations of Pendred syndrome are endolymphatic pH acidification and luminal enlargement of the inner ear. However, the molecular contributions of specific cell types remain poorly c...

    Authors: Jin-Young Koh, Corentin Affortit, Paul T. Ranum, Cody West, William D. Walls, Hidekane Yoshimura, Jian Q. Shao, Brian Mostaert and Richard J.H. Smith
    Citation: BMC Medical Genomics 2023 16:133
  11. Some bladder-related diseases, such as bladder urinary tract infection (UTI) and bladder cancer (BCa), have significant six differences in incidence and prognosis. However, the molecular mechanisms underlying ...

    Authors: Ribao Wu, Xiahong Teng, Qiong Song, Shuai Chen, Lihui Wang, Jinling Liao and Chunlin Zou
    Citation: BMC Medical Genomics 2023 16:122
  12. Single-cell RNA sequencing is a state-of-the-art technology to understand gene expression in complex tissues. With the growing amount of data being generated, the standardization and automation of data analysi...

    Authors: Kejie Li, Yu H. Sun, Zhengyu Ouyang, Soumya Negi, Zhen Gao, Jing Zhu, Wanli Wang, Yirui Chen, Sarbottam Piya, Wenxing Hu, Maria I. Zavodszky, Hima Yalamanchili, Shaolong Cao, Andrew Gehrke, Mark Sheehan, Dann Huh…
    Citation: BMC Genomics 2023 24:228
  13. It is now possible to analyze cellular heterogeneity at the single-cell level thanks to the rapid developments in single-cell sequencing technologies. The clustering of cells is a fundamental and common step i...

    Authors: Saeedeh Akbari Rokn Abadi, Seyed Pouria Laghaee and Somayyeh Koohi
    Citation: BMC Genomics 2023 24:227