Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Network-based features enable prediction of essential genes across diverse organisms
Karthik Azhagesan, Balaraman Ravindran, Karthik Raman
PLoS ONE (2018) Vol. 13, Iss. 12, pp. e0208722-e0208722
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Machine learning approach to gene essentiality prediction: a review
Olufemi Aromolaran, Damilare Aromolaran, Itunuoluwa Isewon, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Open Access | Times Cited: 77
A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification
Nguyen Quoc Khanh Le, Duyen Thi, Truong Nguyen Khanh Hung, et al.
International Journal of Molecular Sciences (2020) Vol. 21, Iss. 23, pp. 9070-9070
Open Access | Times Cited: 63
Bacterial genome reductions: Tools, applications, and challenges
Nicole J. LeBlanc, Trevor C. Charles
Frontiers in Genome Editing (2022) Vol. 4
Open Access | Times Cited: 24
PRODE recovers essential and context-essential genes through neighborhood-informed scores
Thomas Cantore, Paola Gasperini, Riccardo Bevilacqua, et al.
Genome biology (2025) Vol. 26, Iss. 1
Open Access
Essential gene prediction in Drosophila melanogaster using machine learning approaches based on sequence and functional features
Olufemi Aromolaran, Thomas Beder, Marcus Oswald, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 612-621
Open Access | Times Cited: 38
Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes
Qing‐Feng Wen, Shuo Liu, Chuan Dong, et al.
Frontiers in Microbiology (2019) Vol. 10
Open Access | Times Cited: 36
Proteome-Wide Mapping and Reverse Vaccinology Approaches to Design a Multi-Epitope Vaccine against Clostridium perfringens
Fahad M. Aldakheel, Amna Abrar, Samman Munir, et al.
Vaccines (2021) Vol. 9, Iss. 10, pp. 1079-1079
Open Access | Times Cited: 28
DeeplyEssential: a deep neural network for predicting essential genes in microbes
Md. Abid Hasan, Stefano Lonardi
BMC Bioinformatics (2020) Vol. 21, Iss. S14
Open Access | Times Cited: 26
Development of a Candidate Multi-Epitope Subunit Vaccine against Klebsiella aerogenes: Subtractive Proteomics and Immuno-Informatics Approach
Ahitsham Umar, Asma Haque, Youssef Saeed Alghamdi, et al.
Vaccines (2021) Vol. 9, Iss. 11, pp. 1373-1373
Open Access | Times Cited: 21
Comprehensive host-pathogen protein-protein interaction network analysis
Babak Khorsand, Abdorreza Savadi, Mahmoud Naghibzadeh
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 23
Rational design of multimeric based subunit vaccine against Mycoplasma pneumonia: Subtractive proteomics with immunoinformatics framework
M. A. Mahmood, Anam Javaid, Farah Shahid, et al.
Infection Genetics and Evolution (2021) Vol. 91, pp. 104795-104795
Closed Access | Times Cited: 18
Identifying essential genes across eukaryotes by machine learning
Thomas Beder, Olufemi Aromolaran, Jürgen Dönitz, et al.
NAR Genomics and Bioinformatics (2021) Vol. 3, Iss. 4
Open Access | Times Cited: 18
Improving the predictability and interpretability of co‐occurrence modelling through feature‐based joint species distribution ensembles
Francisca Powell‐Romero, Nicholas M. Fountain‐Jones, Anna Norberg, et al.
Methods in Ecology and Evolution (2022) Vol. 14, Iss. 1, pp. 146-161
Open Access | Times Cited: 13
Establishment of a system for screening and identification of novel bactericide targets in the plant pathogenic bacterium Xanthomonas oryzae pv. oryzae using Tn-seq and SPR1
Chaoyue Pang, Ling Jin, Hao-Yu Zang, et al.
Journal of Integrative Agriculture (2023) Vol. 23, Iss. 5, pp. 1580-1592
Open Access | Times Cited: 4
Identification of Key Gene Modules and Novel Transcription Factors in Tetralogy of Fallot Using Machine Learning and Network Topological Features
Sona Charles, Jeyakumar Natarajan
Deleted Journal (2023) Vol. 1, Iss. 1, pp. 27-34
Open Access | Times Cited: 4
Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides
Danish Rasool, Sohail Ahmad Jan, Sumra Umer Khan, et al.
Heliyon (2024) Vol. 10, Iss. 11, pp. e31304-e31304
Open Access | Times Cited: 1
NetGenes: A Database of Essential Genes Predicted Using Features From Interaction Networks
Vimaladhasan Senthamizhan, Balaraman Ravindran, Karthik Raman
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 10
The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
Katherine James, Peter D. Olson
BMC Genomics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 9
Essential gene prediction using limited gene essentiality information–An integrative semi-supervised machine learning strategy
Sutanu Nandi, Piyali Ganguli, Ram Rup Sarkar
PLoS ONE (2020) Vol. 15, Iss. 11, pp. e0242943-e0242943
Open Access | Times Cited: 9
PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains
Hsuan-Lin Her, Po Ting Lin, Yu‐Wei Wu
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 9
DeeplyEssential: A Deep Neural Network for Predicting Essential Genes in Microbes
Md. Abid Hasan, Stefano Lonardi
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 7
Predicting essential genes of 37 prokaryotes by combining information-theoretic features
Xiao Liu, Yachuan Luo, Ting He, et al.
Journal of Microbiological Methods (2021) Vol. 188, pp. 106297-106297
Closed Access | Times Cited: 4
GENPPI: standalone software for creating protein interaction networks from genomes
William Ferreira dos Anjos, Gabriel Chagas Lanes, Vasco Azevedo, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 4
Tree based models for classification of membrane and secreted proteins in heart
Sona Charles, A. Subeesh, Jeyakumar Natarajan
Journal of Proteins and Proteomics (2024) Vol. 15, Iss. 2, pp. 147-157
Closed Access
Machine learning methods for predicting essential metabolic genes from Plasmodium falciparum genome-scale metabolic network
Itunuoluwa Isewon, Stephen Binaansim, Faith Adegoke, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0315530-e0315530
Open Access
Page 1 - Next Page

Scroll to top