Frontiers in Bioinformatics | Single Cell Bioinformatics

Review

Published on 27 Jan 2026

Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges

in Single Cell Bioinformatics

Boris Tchatchoua Ngassam
Huilin Niu
Sunny Pang
Valeryia Shydlouskaya
Tallulah S. Andrews

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1715821

643 views

Original Research

Published on 12 Jan 2026

SpaLLM: a general framework for spatial domain identification with large language models

in Single Cell Bioinformatics

Zeyu Zou
Ziheng Duan

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1713975

379 views

Original Research

Published on 12 Jan 2026

Integrative transcriptomic analysis reveals microglial metabolic-inflammatory crosstalk of HK2–HSPA5–TNF axis after intracerebral hemorrhage

in Single Cell Bioinformatics

Yi Zhang
Yongqian Liu
Wei Meng
Xiaobo Yu
Xiaojun Xu

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1740715

392 views

Original Research

Published on 12 Jan 2026

High-dimensional co-expression network analysis reveals persistent TRH gene expression throughout axolotl telencephalon regeneration

in Single Cell Bioinformatics

Iveth Gómez-Morales
Adriana P. Mendizabal-Ruiz
J. Alejandro Morales
Teresa Romero-Gutiérrez

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1697212

450 views

Technology and Code

Published on 11 Dec 2025

Celline: a flexible tool for one-step retrieval and integrative analysis of public single-cell RNA sequencing data

in Single Cell Bioinformatics

Yuya Sato
Toru Asahi
Kosuke Kataoka

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1684227

1,671 views

Original Research

Published on 13 Nov 2025

Comprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms

in Single Cell Bioinformatics

Aanya Gupta
Koji Abe
Holden T. Maecker

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1636240

1,367 views

Methods

Published on 18 Sep 2025

Quantitative measures to assess the quality of cellular indexing of transcriptomes and epitopes by sequencing data

in Single Cell Bioinformatics

Jie Sun
Robert Morrison
Soyeon Kim
Kairuo Yan
Hyun Jung Park

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1630161

2,562 views

Technology and Code

Published on 05 Sep 2025

TCRscape: a single-cell multi-omic TCR profiling toolkit

in Single Cell Bioinformatics

Roman Perik-Zavodskii
Olga Perik-Zavodskaia
Marina Volynets
Saleh Alrhmoun
Sergey Sennikov

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1641491

2,882 views
1 citation

Original Research

Published on 18 Jul 2025

Analysis of histone modifications in key cellular subpopulations in the context of azoospermia using spermatogenic single-cell RNA-seq data

in Single Cell Bioinformatics

Qiu Wang
Hong Yang
Fang Li
Song Ge
Ling Ji
Xiaofeng Li

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1626153

2,422 views

Original Research

Published on 11 Jun 2025

Optimization of clustering parameters for single-cell RNA analysis using intrinsic goodness metrics

in Single Cell Bioinformatics

Nicolina Sciaraffa
Antonino Gagliano
Luigi Augugliaro
Claudia Coronnello

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1562410

3,246 views
1 citation

Mini Review

Published on 17 Apr 2025

Primer on machine learning applications in brain immunology

in Single Cell Bioinformatics

Niklas Binder
Ashkan Khavaran
Roman Sankowski

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1554010

3,371 views
1 citation

Technology and Code

Published on 12 Feb 2025

Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation

in Single Cell Bioinformatics

Mikhail Arbatsky
Ekaterina Vasilyeva
Veronika Sysoeva
Ekaterina Semina
Valeri Saveliev
Kseniya Rubina

Frontiers in Bioinformatics

doi 10.3389/fbinf.2025.1519468

4,221 views
5 citations

Editorial

Published on 08 Oct 2024

Editorial: Women in bioinformatics

in Single Cell Bioinformatics

Irma Martínez-Flores
Constanza Cárdenas Carvajal
Viviana Monje-Galvan

Frontiers in Bioinformatics

doi 10.3389/fbinf.2024.1499514

1,924 views

Mini Review

Published on 08 Jul 2024

A systematic overview of single-cell transcriptomics databases, their use cases, and limitations

in Single Cell Bioinformatics

Mahnoor N. Gondal
Saad Ur Rehman Shah
Arul M. Chinnaiyan
Marcin Cieslik

Frontiers in Bioinformatics

doi 10.3389/fbinf.2024.1417428

10,936 views
14 citations

Original Research

Published on 04 Mar 2024

Predicting cell population-specific gene expression from genomic sequence

in Single Cell Bioinformatics

Lieke Michielsen
Marcel J. T. Reinders
Ahmed Mahfouz

Frontiers in Bioinformatics

doi 10.3389/fbinf.2024.1347276

5,070 views
1 citation

Original Research

Published on 04 Mar 2024

Detecting subtle transcriptomic perturbations induced by lncRNAs knock-down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

in Single Cell Bioinformatics

Marin Truchi
Caroline Lacoux
Cyprien Gille
Julien Fassy
Virginie Magnone
Rafael Lopes Goncalves
Cédric Girard-Riboulleau
Iris Manosalva-Pena
Marine Gautier-Isola
Kevin Lebrigand

Frontiers in Bioinformatics

doi 10.3389/fbinf.2024.1340339

3,911 views
3 citations

Methods

Published on 10 Aug 2023

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

in Single Cell Bioinformatics

Wanxin Li
Jules Mirone
Ashok Prasad
Nina Miolane
Carine Legrand
Khanh Dao Duc

Frontiers in Bioinformatics

doi 10.3389/fbinf.2023.1211819

2,800 views
1 citation

Original Research

Published on 15 May 2023

Gene representation in scRNA-seq is correlated with common motifs at the 3′ end of transcripts

in Single Cell Bioinformatics

Xinling Li
Greg Gibson
Peng Qiu

Frontiers in Bioinformatics

doi 10.3389/fbinf.2023.1120290

5,178 views
2 citations

Original Research

Published on 12 Apr 2023

Gene length is a pivotal feature to explain disparities in transcript capture between single transcriptome techniques

in Single Cell Bioinformatics

Ricardo R. Pavan
Fabiola Diniz
Samir El-Dahr
Giovane G. Tortelote

Frontiers in Bioinformatics

doi 10.3389/fbinf.2023.1144266

4,426 views
2 citations

19 articles

articles

Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges

SpaLLM: a general framework for spatial domain identification with large language models

Integrative transcriptomic analysis reveals microglial metabolic-inflammatory crosstalk of HK2–HSPA5–TNF axis after intracerebral hemorrhage

High-dimensional co-expression network analysis reveals persistent TRH gene expression throughout axolotl telencephalon regeneration

Celline: a flexible tool for one-step retrieval and integrative analysis of public single-cell RNA sequencing data

Comprehensive analysis of multi-omics vaccine response data using MOFA and Stabl algorithms

Quantitative measures to assess the quality of cellular indexing of transcriptomes and epitopes by sequencing data

TCRscape: a single-cell multi-omic TCR profiling toolkit

Analysis of histone modifications in key cellular subpopulations in the context of azoospermia using spermatogenic single-cell RNA-seq data

Optimization of clustering parameters for single-cell RNA analysis using intrinsic goodness metrics

Primer on machine learning applications in brain immunology

Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation

Editorial: Women in bioinformatics

A systematic overview of single-cell transcriptomics databases, their use cases, and limitations

Predicting cell population-specific gene expression from genomic sequence

Detecting subtle transcriptomic perturbations induced by lncRNAs knock-down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

Gene representation in scRNA-seq is correlated with common motifs at the 3′ end of transcripts

Gene length is a pivotal feature to explain disparities in transcript capture between single transcriptome techniques