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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Gene Expression Distribution Deconvolution in Single Cell RNA Sequencing
Jingshu Wang, Mo Huang, Eduardo de la Torre, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2017)
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Rapid and accurate identification of ribosomal RNA sequences via deep learning
Zhi-Luo Deng, Philipp C. Münch, René Mreches, et al.
Nucleic Acids Research (2022) Vol. 50, Iss. 10, pp. e60-e60
Open Access | Times Cited: 79
The interferon-stimulated gene RIPK1 regulates cancer cell intrinsic and extrinsic resistance to immune checkpoint blockade
Lisa Cucolo, Qingzhou Chen, Jingya Qiu, et al.
Immunity (2022) Vol. 55, Iss. 4, pp. 671-685.e10
Open Access | Times Cited: 65
Inference after latent variable estimation for single-cell RNA sequencing data
Anna Neufeld, Lucy L. Gao, Joshua M Popp, et al.
Biostatistics (2022) Vol. 25, Iss. 1, pp. 270-287
Open Access | Times Cited: 43
Interpreting omics data with pathway enrichment analysis
Kangmei Zhao, Seung Y. Rhee
Trends in Genetics (2023) Vol. 39, Iss. 4, pp. 308-319
Open Access | Times Cited: 41
Semisoft clustering of single-cell data
Lingxue Zhu, Jing Lei, Lambertus Klei, et al.
Proceedings of the National Academy of Sciences (2018) Vol. 116, Iss. 2, pp. 466-471
Open Access | Times Cited: 83
Discovery and characterization of variance QTLs in human induced pluripotent stem cells
Abhishek Sarkar, Po‐Yuan Tung, John Blischak, et al.
PLoS Genetics (2019) Vol. 15, Iss. 4, pp. e1008045-e1008045
Open Access | Times Cited: 69
Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing
Rishikesh Kumar Gupta, Jacek Kuźnicki
Cells (2020) Vol. 9, Iss. 8, pp. 1751-1751
Open Access | Times Cited: 57
A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks
Abicumaran Uthamacumaran
Patterns (2021) Vol. 2, Iss. 4, pp. 100226-100226
Open Access | Times Cited: 50
Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics
Songhao Luo, Zihao Wang, Zhenquan Zhang, et al.
Nucleic Acids Research (2022) Vol. 51, Iss. 1, pp. 68-83
Open Access | Times Cited: 32
Understanding the kidney one cell at a time
Jihwan Park, Chang Liu, Junhyong Kim, et al.
Kidney International (2019) Vol. 96, Iss. 4, pp. 862-870
Open Access | Times Cited: 53
Differential Expression Analysis of Single-Cell RNA-Seq Data: Current Statistical Approaches and Outstanding Challenges
Samarendra Das, Anil Rai, N. Shesh
Entropy (2022) Vol. 24, Iss. 7, pp. 995-995
Open Access | Times Cited: 27
Length biases in single-cell RNA sequencing of pre-mRNA
Gennady Gorin, Lior Pachter
Biophysical Reports (2022) Vol. 3, Iss. 1, pp. 100097-100097
Open Access | Times Cited: 23
DECENT: differential expression with capture efficiency adjustmeNT for single-cell RNA-seq data
Chengzhong Ye, Terence P. Speed, Agus Salim
Bioinformatics (2019) Vol. 35, Iss. 24, pp. 5155-5162
Open Access | Times Cited: 42
Separating measurement and expression models clarifies confusion in single-cell RNA sequencing analysis
Abhishek Sarkar, Matthew Stephens
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 35
A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies
Samarendra Das, Anil Rai, Michael L. Merchant, et al.
Genes (2021) Vol. 12, Iss. 12, pp. 1947-1947
Open Access | Times Cited: 28
SAVER: Gene expression recovery for UMI-based single cell RNA sequencing
Mo Huang, Jingshu Wang, Eduardo A. Torre, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2017)
Open Access | Times Cited: 33
Enhanced transcriptional heterogeneity mediated by NF-κB super-enhancers
Johannes Nicolaus Wibisana, Takehiko Inaba, Hisaaki Shinohara, et al.
PLoS Genetics (2022) Vol. 18, Iss. 6, pp. e1010235-e1010235
Open Access | Times Cited: 16
Method of moments framework for differential expression analysis of single-cell RNA sequencing data
Min Cheol Kim, Rachel E. Gate, David S. Lee, et al.
Cell (2024) Vol. 187, Iss. 22, pp. 6393-6410.e16
Open Access | Times Cited: 3
Minnow: a principled framework for rapid simulation of dscRNA-seq data at the read level
Hirak Sarkar, Avi Srivastava, Rob Patro
Bioinformatics (2019) Vol. 35, Iss. 14, pp. i136-i144
Open Access | Times Cited: 23
SwarnSeq: An improved statistical approach for differential expression analysis of single-cell RNA-seq data
Samarendra Das, N. Shesh
Genomics (2021) Vol. 113, Iss. 3, pp. 1308-1324
Open Access | Times Cited: 16
Single-cell Transcriptomes Reveal Characteristics of MicroRNAs in Gene Expression Noise Reduction
Tao Hu, Lei Wei, Shuailin Li, et al.
Genomics Proteomics & Bioinformatics (2021) Vol. 19, Iss. 3, pp. 394-407
Open Access | Times Cited: 10
AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification
Xiaoshu Zhu, Shuang Meng, Gaoshi Li, et al.
Bioinformatics (2024) Vol. 40, Iss. 2
Open Access | Times Cited: 1
graphsim: An R package for simulating gene expression data from graph structures of biological pathways
S. Thomas Kelly, Michael A. Black
The Journal of Open Source Software (2020) Vol. 5, Iss. 51, pp. 2161-2161
Open Access | Times Cited: 6
Single cell transcriptomes reveal characteristics of miRNA in gene expression noise reduction
Tao Hu, Lei Wei, Shuailin Li, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2018)
Open Access | Times Cited: 5
Integrating single-cell transcriptomics and microcircuit computer modeling
Vineet Reddy, Mohamed Sherif, Rammohan Shukla
Current Opinion in Pharmacology (2021) Vol. 60, pp. 34-39
Closed Access | Times Cited: 5
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