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Diffusion Kernel based Fast Adaptive Clustering of Single Cell RNA-seq Data

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Deep Variable-Block Chain with Adaptive Variable SelectionPreprint

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Enhancing Clustering of Single-Cell RNA-Seq Data by Proximity Learning on Random Projected Spaces

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Variational Inference in Probabilistic Single-cell RNA-seq Models

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On a scalable entropic breaching of the overfitting barrier in machine learningPreprint

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Clustering Single-cell RNA-sequencing Data based on Matching Clusters Structures

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Clustering-Based Integrated Analysis of Time-Series Gene Expression Data to Identify Stress-Responsive Genes

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Elastic Coupled Co-clustering for Single-Cell Genomic DataPreprint

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AIK-Means: A Novel Clustering Method for Single-Cell RNA Sequencing Data

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One-step spectral clustering of weighted variables on single-cell RNA-sequencing data

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Derivation of stable embryonic stem cell-like, but transcriptionally heterogenous, induced pluripotent stem cells from non-permissive mouse strains

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TPK: a single-cell clustering algorithm based on novel feature selection genes

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Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis

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Towards Personalized Medicine: Computational Approaches For Drug Repurposing And Cell Type Identification

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SimBPDD: Simulating differential distributions in Beta-Poisson models, in particular for single-cell RNA sequencing data

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A Link-Based Ensemble Cluster Approach for Identification of Cell Types

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Improvement on the explanation of cluster analysis for transcriptome data

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Single cell transcriptomics and epigenomics methods provide high resolution genomics profiling of brain disorders

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Single Cell Sequencing, Its Application and Future Challenges

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miR-409-3p represses Cited2 at the evolutionary emergence of the callosal and corticospinal projectionsPreprint

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Imputation in Scrna-seq Data Using Supervised Deep Generative Networks

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scCODE: an R package for personalized differentially expressed gene detection on single-cell RNA-sequencing dataPreprint

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A Novel Prognostic Model Based on Nine-Targeted Therapeutic Response Relevant Secreted Protein Genes (Trspgs) from Single-Cell Rna Sequencing in Multiple MyelomaPreprint

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Adaptive total-variation joint learning model for analyzing single cell RNA seq data

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ScLRTC: Imputation for Single-Cell RNA-Seq Data Via Low-Rank Tensor CompletionPreprint

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Peer Review #2 of "SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization (v0.3)"

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Peer Review #3 of "SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization (v0.1)"

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Faculty Opinions recommendation of Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution.

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Peer Review #2 of "SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization (v0.1)"

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Peer Review #1 of "SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization (v0.2)"

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Faculty Opinions recommendation of A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture.

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Faculty Opinions recommendation of The human cell atlas.

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Faculty Opinions recommendation of Human cerebral organoids recapitulate gene expression programs of fetal neocortex development.

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Peer Review #2 of "SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization (v0.2)"

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Peer Review #1 of "SC-JNMF: single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization (v0.1)"

(2021) · PeerJ · doi:10.7287/peerj.12087v0.1/reviews/1

Faculty Opinions recommendation of Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution.

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SINGLE NUCLEI RNA SEQUENCING OF 5 REGIONS OF THE HUMAN PRENATAL BRAIN IMPLICATES DEVELOPING NEURON POPULATIONS IN GENETIC RISK FOR SCHIZOPHRENIA

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Simultaneous visualization of cells and marker genes from scRNA-seq studiesPreprint

Bhattacharya, N., Chakraborti, S., Gupta, K., Mittal, A., Sinha, D., Nelson, C. C., Chakraborty, T., Ahuja, G., & Sengupta, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.27.521966

IMAGE-seq and you shall find

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Gaeklrr: A Novel Clustering Method of the Low-Rank Represent Based on Graph Auto-Encoder and Relaxed K-Means for Single Cell Type IdentificationPreprint

Wang, L., Liu, J., Shang, J., Kong, X.-Z., & Wang, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4521453

Development of Cortical Neuron Heterogeneity and Impact of Neurodevelopmental Disorders

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Enabling methanol fixation of pediatric nasal wash during respiratory illness for single cell sequencing in comparison with fresh samples

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Probabilistic clustering of cells using single-cell RNA-seq dataPreprint

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Advances In Therapeutic Use of Microfluidics (Body on A Chip): A Review

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scSRL: Siamese Representation Learning-based method for analyzing single-cell RNA-seq data

Sun, Z., Liu, Y., Liu, P., Shi, W., & Luo, J. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385561

scNMF-Impute: imputation for single-cell RNA-seq data based on nonnegative matrix factorization

Wang, J., Zhang, N.-N., Shang, J., & Liu, J. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385409

A Network Propagation Based Approach for Measuring Cell-Cell Similarity

Li, J., Wang, B., & Li, J. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385348

Analysis of Significant Cell Differences Between Cancer Patients and Healthy Individuals

Sun, P.-C., Yan, X. S., Li, Y., Chen, H., Li, H.-C., li, C.-Y., & Cheng, W.-S. (2024) · Communications in computer and information science · doi:10.1007/978-981-97-1714-9_18

Research on the Data Quality Factors Affecting Single-Cell Type Analysis

Qian, W., & Ge, Q. (2024) · International Conference on Bioinformatics and Intelligent Computing (BIC) · doi:10.1145/3665689.3665763

scRFR: imputation of single-cell RNA-seq data based on recurrent feature inference scRFR: scRNA-seq imputation algorithm Image restoration technology applied to scRNA-seq imputation - scRNA-seq imputation algorithm uses recurrent feature inference model

Zhu, B., Zhang, S., Li, L., & Qian, Z. (2024) · International Conference on Bioinformatics and Intelligent Computing (BIC) · doi:10.1145/3665689.3665759

Optimal sequencing budget allocation for trajectory reconstruction of single cells

Moriel, N., Memet, E., & Nitzan, M. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae258

Integrating Multiple Clustering Techniques and Performance Measures via Ranking for scRNA‐Seq Data

Visser, O., & Datta, S. (2025) · Statistics in Medicine · doi:10.1002/sim.70331

MLRR-ATV: A Robust Manifold Nonnegative Low-Rank Representation With Adaptive Total-Variation Regularization for scRNA-seq Data Clustering

Wang, G.-F., Wang, J., Yuan, S., Zheng, C.-H., & Liu, J. (2024) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2024.3432740

Hypergraph-based Clustering for Single-Cell RNA Sequencing Data

Hu, C., & Sheng, Y. (2024) · Chinese Control Conference (CCC) · doi:10.23919/ccc63176.2024.10662510

Extracellular matrix of the nervous system

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Transcriptomic Basis of Non-Specific Interstitial Pneumonia Using in Silico ApproachPreprint

Ali, M. S., Hadda, V., Kumari, K., Mittal, S., Chopra, A., Tiwari, P., Suri, T. M., Madan, K., & Mohan, A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4969494

Local-Global Graph Fusion to Enhance scRNA-Seq Clustering

Du, L., & Han, Y. (2024) · IEEE Access · doi:10.1109/access.2024.3487552 · Cited by 1

A New Method for Processing scRNA-seq Data by Coupling Low-Rank Representation and Concept Factorization

Zhang, Z., Liu, J., Li, S., & Wang, J. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10822518

scZIGVAE: A Variational Graph Attention Autoencoder Based on the Zero-Inflated Negative Binomial Distribution for Clustering Single-cell RNA-Seq Data

Wang, Y., Gao, K., Li, Z., Liu, C., Ji, C., Qiao, L., & Zheng, C.-H. (2025) · Current Bioinformatics · doi:10.2174/0115748936348851241230113213

Single Cell Clustering Based on Multi-view Generation

Wang, Y., Wu, Z., & Zhang, Q. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-1907-8_3

Compressed Representation of Extreme Learning Machine with Self-Diffusion Graph Denoising Applied for Dissecting Molecular Heterogeneity

Duan, X., Ding, X., & Lu, Y. (2025) · Journal of Computational Biology · doi:10.1089/cmb.2024.0729

Subspace clustering with self-representation sparsification and regression via connected components

Long, Z., Guan, R., Gao, Y. Q., Meng, H., & Luo, R. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.113262

Optimal Feature Non-negative Matrix Factorization (OFNMF) for Enhanced Single-Cell RNA Sequencing Analysis

Zhang, D.-J., Gao, Y.-L., Liu, J., Jing-xiu, Z., & Wang, J. (2025) · Current Bioinformatics · doi:10.2174/0115748936369856250603092735

scGECA: A Graph Embedded Representation Learning Approach with Dynamic Attention Mechanism for Single-Cell Clustering

Zhao, Z., Xie, M., Liu, Q., & Xie, R. (2025) · Lecture notes in computer science · doi:10.1007/978-981-95-0030-7_36

A single-cell RNA sequencing data imputation method based on non-negative matrix factorization and multi-kernel similarity network fusion

Liu, P., Chen, C., Liu, H., Gu, J., Chen, X., Su, Y., Cheng, Z., Lv, X., & Chen, C. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112313

BiAEImpute: a robust bidirectional autoencoder framework for High-fidelity dropout imputation in single-cell transcriptomics

Zhang, Y., Liu, X., Wang, Y., & Wang, Y. (2025) · BMC Genomics · doi:10.1186/s12864-025-11988-x

Interpretable Multi-task Analysis of Single-Cell RNA-seq Data Through Topological Structure Preservation and Data Denoising

Yu, S., Yang, Z., Liu, T., Liang, C., & Wang, H. (2025) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-025-00765-9

Clustering of Single-cell RNA-seq Data using Multi-hop Graph Embedding Autoencoder

Yi, X., Wu, T., Yu, Z., & Li, X. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11229423

D3Impute: Dropout-aware discrimination, distribution-aware modeling, and density-guide imputation for scRNA-seq data

Huang, S., Jiang, L., Yi, M., & Zhu, Y. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013744

Additional file 1 of Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model

Ono, H., Arai, Y., Furukawa, E., Narushima, D., Matsuura, T., Nakamura, H., Shiokawa, D., Nagai, M., Imai, T., Mimori, K., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16655589

Additional file 3 of scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

Sun, T., Song, D., Li, W. V., & Li, J. J. (2021) · Figshare · doi:10.6084/m9.figshare.14677034

Additional file 2 of ZetaSuite: computational analysis of two-dimensional high-throughput data from multi-target screens and single-cell transcriptomics

Hao, Y., Zhang, S., Shao, C., Li, J., Zhao, G., Zhang, D., & Fu, X.-D. (2022) · Figshare · doi:10.6084/m9.figshare.20372774

Additional file 1 of baredSC: Bayesian approach to retrieve expression distribution of single-cell data

Lopez‐Delisle, L., & Delisle, J.-B. (2022) · Figshare · doi:10.6084/m9.figshare.18318368

Additional file 1 of ccImpute: an accurate and scalable consensus clustering based algorithm to impute dropout events in the single-cell RNA-seq data

Malec, M., Kurban, H., & Dalkilic, M. M. (2022) · Figshare · doi:10.6084/m9.figshare.20364792

Additional file 2 of scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

Sun, T., Song, D., Li, W. V., & Li, J. J. (2021) · Figshare · doi:10.6084/m9.figshare.14677031

Additional file 1 of scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

Sun, T., Song, D., Li, W. V., & Li, J. J. (2021) · Figshare · doi:10.6084/m9.figshare.14677028

Additional file 1 of ZetaSuite: computational analysis of two-dimensional high-throughput data from multi-target screens and single-cell transcriptomics

Hao, Y., Zhang, S., Shao, C., Li, J., Zhao, G., Zhang, D., & Fu, X.-D. (2022) · Figshare · doi:10.6084/m9.figshare.20372771

RF-SCGFS: A Feature Selection Method Based on Secuer and Random Forest Model for Single-cell RNA-Seq Data

Wang, Y., Liu, C., Ji, C., Ma, Z., Liu, Z., Qiao, L., & Zheng, C. (2026) · Current Bioinformatics · doi:10.2174/0115748936401797251030055501

Molecular and Cellular Underpinnings of Spatial Heterogeneity in Fetal Cortical FoldingPreprint

Xu, X., Chen, R., Zheng, T., Zhao, Z., Li, M., & Wu, D. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.20.700501 · Cited by 1

scAURA: Alignment- and Uniformity-based Graph Debiased Contrastive Representation Architecture for Self-Supervised Clustering of Single-Cell TranscriptomicsPreprint

Rifat, J. I. M., Engala, S., & Bozdag, S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.25.701579

An Adaptive Single-Cell Sequencing Data Cluster Method Under Weight Fusion Constraint

Wang, Z., Yuan, S., Li, F., & Wang, J. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356638

A Dual-Graph-Driven Non-Negative Matrix Factorization Model for Single-Cell Omics Analysis

Lan, J., Wang, N., & Deng, J. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11357023

sxFusion: A Novel Single-Cell Clustering Tool Based on Feature Fusion and Co-Optimization of Low-Rank Representation

Wang, L., Wu, J., Wang, J., Zhang, J., Xu, H., Xiong, K., Bai, X., Ning, K., & Xia, L. C. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356976

RareCapsNet: An explainable capsule networks enable robust discovery of rare cell populations from large-scale single-cell transcriptomicsPreprint

Ray, S., & Lall, S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.02.703229

GAEKLRR: A novel clustering method of the low-rank representation based on graph auto-encoder and relaxed k-means for single-cell type identification

Wang, L., Shang, J., Dai, L., & Wang, J. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11400609

ANTIPODE Provides a Global View of Cell Type Homology and Transcriptomic Divergence in the Developing Mammalian BrainPreprint

Schmitz, M. T., Ding, J. W., Nolbrant, S., McMullen, R., Kim, C. N., Pavlovic, B. J., Nowakowski, T. J., Bakken, T. E., Ye, C., & Pollen, A. A. (2026) · eLife · doi:10.7554/elife.109659.1

ANTIPODE Provides a Global View of Cell Type Homology and Transcriptomic Divergence in the Developing Mammalian BrainPreprint

Schmitz, M. T., Ding, J. W., Nolbrant, S., McMullen, R., Kim, C. N., Pavlovic, B. J., Nowakowski, T. J., Bakken, T. E., Ye, C., & Pollen, A. A. (2026) · eLife · doi:10.7554/elife.109659

scTGCL: A Transformer-Based Graph Contrastive Learning Approach for Efficiently Clustering Single-Cell RNA-seq DataPreprint

Khan, M. S. A., Faisal, M. M., & Faisal, M. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.28.714542

Étude des cellules souches germinales : caractérisation des cellules souches germinales humaines et effets de l'hypoxie

Givelet, M. (2018) · theses.fr (ABES) · doi:10.70675/548b758fzc017z40d4z913fzacdaa8d2f1ac

Catching cellular heterogeneity and differentiation dynamics of normal and pathological airway epithelia through single cell transcriptional profiling

García, S. R. (2018) · theses.fr (ABES) · doi:10.70675/67876ef0zf5dcz40acza191z2631d60927b2

Mechanistic study and prediction of influenza A virus genetic reassortment

Chen, K. (2019) · doi:10.70675/6bb882e3z6248z42f5zb987z2f2e1d7457cd

Hétérogénéité de la réactivité astrocytaire dans la maladie d'Alzheimer

Guillemaud, O. (2020) · theses.fr (ABES) · doi:10.70675/038d98c5z55ccz4754z9af9z417e3826d282

Fonction d'un régulateur du cycle cellulaire, la phosphatase CDC25B, au cours de la neurogenèse chez les Mammifères

Roussat, M. (2020) · theses.fr (ABES) · doi:10.70675/6b63c059z5722z4467z9ef5z40e0164ade70

Retinoblastoma heterogeneity : a comprehensive multi-omic and single-cell transcriptomic analysis

Liu, J. (2022) · theses.fr (ABES) · doi:10.70675/d2639275z9862z4f1fz87d3ze2d7ca5decfa

Développement d'un système de microfluidique de gouttes pour l'analyse d'échantillons complexes

Richerd, M. (2021) · theses.fr (ABES) · doi:10.70675/502160d7z5a1dz4178zbebfz3424707cda14

Application of functional genomics to colorectal cancer liver metastases and blastic plasmacytoid dendritic cell neoplasms

Giguelay, A. (2021) · theses.fr (ABES) · doi:10.70675/c3d8d759z3dcbz4e69z801az73e678f14edd

Rôle de la phosphodiestérase 2A dans la physiopathologie du syndrome de l’X fragile

Delhaye, S. (2021) · theses.fr (ABES) · doi:10.70675/e0fac395z63d4z46a4z944aza4037215ca98

ShinyCortex: Exploring Single-Cell Transcriptome Data From the Developing Human Cortex

Kageyama, J., Wollny, D., Treutlein, B., & Camp, J. G. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00315 · Cited by 9

Identification of cell types in a mouse brain single-cell atlas using low sampling coverage

Bhaduri, A., Nowakowski, T. J., Pollen, A. A., & Kriegstein, A. R. (2018) · BMC Biology · doi:10.1186/s12915-018-0580-x · Cited by 15

The Technology and Biology of Single-Cell RNA Sequencing

Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C., & Teichmann, S. A. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.04.005 · Cited by 1,487

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Feng, W., Przysinda, A., & Li, G. (2020) · Journal of Visualized Experiments · doi:10.3791/60647-v · Cited by 2

Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

Rosenberg, A. B., Roco, C. M., Muscat, R. A., Kuchina, A., Sample, P., Yao, Z., Graybuck, L. T., Peeler, D. J., Mukherjee, S., Chen, W., et al. (2018) · Science · doi:10.1126/science.aam8999 · Cited by 1,422