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:

RFCM3 : Computational Method for Identification of miRNA-mRNA Regulatory Modules in Cervical Cancer
Sushmita Paul, Madhumita Madhumita
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2019) Vol. 17, Iss. 5, pp. 1729-1740
Closed Access | Times Cited: 11

Showing 11 citing articles:

miRModuleNet: Detecting miRNA-mRNA Regulatory Modules
Malik Yousef, Gökhan Göy, Burcu Bakır-Güngör
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 35

Capturing the latent space of an Autoencoder for multi-omics integration and cancer subtyping
Madhumita Madhumita, Sushmita Paul
Computers in Biology and Medicine (2022) Vol. 148, pp. 105832-105832
Closed Access | Times Cited: 19

A review on methods for predicting miRNA–mRNA regulatory modules
Madhumita Madhumita, Sushmita Paul
Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics (2022) Vol. 19, Iss. 3
Open Access | Times Cited: 15

Deciphering microRNA-mRNA regulatory network in adult T-cell leukemia/lymphoma; the battle between oncogenes and anti-oncogenes
Mohadeseh Zarei Ghobadi, Rahman Emamzadeh, Sayed‐Hamidreza Mozhgani
PLoS ONE (2021) Vol. 16, Iss. 2, pp. e0247713-e0247713
Open Access | Times Cited: 16

Autoencoder Assisted Cancer Subtyping by Integrating Multi-omics Data
Madhumita Madhumita, Sushmita Paul
Lecture notes in computer science (2024), pp. 127-136
Closed Access

MDA-TOEPGA: A novel method to identify miRNA-disease association based on two-objective evolutionary programming genetic algorithm
Buwen Cao, Jiawei Luo, Sainan Xiao, et al.
Biocell (2022) Vol. 46, Iss. 8, pp. 1925-1933
Open Access | Times Cited: 2

miRCoop: Identifying Cooperating miRNAs via Kernel Based Interaction Tests
Gülden Olgun, Öznur Taştan
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 19, Iss. 3, pp. 1760-1771
Open Access | Times Cited: 1

Recursive integration of synergised graph representations of multi-omics data for cancer subtypes identification
Madhumita Madhumita, Archit Dwivedi, Sushmita Paul
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 1

Computational Methods for Identifying MicroRNA-Gene Regulatory Modules
Yin Liu
Springer handbooks of computational statistics (2022), pp. 187-208
Closed Access | Times Cited: 1

An Effective Cervical Cancer Detection Approaches - A Comparative Analysis
S. Uma Maheswari, C. N. Marimuthu, B. Deepa, et al.
(2023), pp. 372-377
Closed Access

Recursive Multi-view Integration for Subtypes Identification of Cervical Cancer
Madhumita Madhumita, Archit Dwivedi, Sushmita Paul
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2021), pp. 706-709
Closed Access

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