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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:

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
Maxat Kulmanov, Robert Hoehndorf
PLoS Computational Biology (2020) Vol. 16, Iss. 11, pp. e1008453-e1008453
Open Access | Times Cited: 20

Showing 20 citing articles:

Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion
Qianmu Yuan, Junjie Xie, Jiancong Xie, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Open Access | Times Cited: 46
Semantic similarity and machine learning with ontologies
Maxat Kulmanov, Fatima Zohra Smaili, Xin Gao, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 4
Open Access | Times Cited: 130
DeepViral: prediction of novel virus–host interactions from protein sequences and infectious disease phenotypes
Wang Liu-Wei, Şenay Kafkas, Jun Chen, et al.
Bioinformatics (2021) Vol. 37, Iss. 17, pp. 2722-2729
Open Access | Times Cited: 49
Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches
Yuguo Zha, Hui Chong, H. Qiu, et al.
Genome Medicine (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 15
Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
Azza Althagafi, Fernando Zhapa-Camacho, Robert Hoehndorf
Bioinformatics (2024) Vol. 40, Iss. 5
Open Access | Times Cited: 2
Ontology-Based decision tree model for prediction of fatty liver diseases
Seyed Yashar Banihashem, Saman Shishehchi
Computer Methods in Biomechanics & Biomedical Engineering (2022) Vol. 26, Iss. 6, pp. 639-649
Closed Access | Times Cited: 11
Ontologies related to livestock for the Global Burden of Animal Diseases programme: a review
Mieghan Bruce, Jonathan Rushton, K. RAYMOND, et al.
Revue Scientifique et Technique de l OIE (2024) Vol. 43, pp. 69-78
Open Access | Times Cited: 2
Breaking bad news in the era of artificial intelligence and algorithmic medicine: an exploration of disclosure and its ethical justification using the hedonic calculus
Benjamin Post, Cosmin Badea, A. Aldo Faisal, et al.
AI and Ethics (2022) Vol. 3, Iss. 4, pp. 1215-1228
Open Access | Times Cited: 10
Computational Methods for Prediction of Human Protein-Phenotype Associations: A Review
Lizhi Liu, Shanfeng Zhu
Phenomics (2021) Vol. 1, Iss. 4, pp. 171-185
Open Access | Times Cited: 13
DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning
Azza Althagafi, Lamia Alsubaie, Nagarajan Kathiresan, et al.
Bioinformatics (2021) Vol. 38, Iss. 6, pp. 1677-1684
Open Access | Times Cited: 13
Contribution of model organism phenotypes to the computational identification of human disease genes
Sarah M. Alghamdi, Paul N. Schofield, Robert Hoehndorf
Disease Models & Mechanisms (2022) Vol. 15, Iss. 7
Open Access | Times Cited: 9
HPODNets: deep graph convolutional networks for predicting human protein–phenotype associations
Lizhi Liu, Hiroshi Mamitsuka, Shanfeng Zhu
Bioinformatics (2021) Vol. 38, Iss. 3, pp. 799-808
Closed Access | Times Cited: 6
Ontology Pre-training for Poison Prediction
Martin Glauer, Fabian Neuhaus, Till Mossakowski, et al.
Lecture notes in computer science (2023), pp. 31-45
Closed Access | Times Cited: 2
SSLpheno: a self-supervised learning approach for gene–phenotype association prediction using protein–protein interactions and gene ontology data
Xuehua Bi, Weiyang Liang, Qichang Zhao, et al.
Bioinformatics (2023) Vol. 39, Iss. 11
Open Access | Times Cited: 2
Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
Azza Althagafi, Fernando Zhapa-Camacho, Robert Hoehndorf
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
IMPROVE-DD: Integrating multiple phenotype resources optimizes variant evaluation in genetically determined developmental disorders
Stuart Aitken, Helen V. Firth, Caroline F. Wright, et al.
Human Genetics and Genomics Advances (2022) Vol. 4, Iss. 1, pp. 100162-100162
Open Access | Times Cited: 3
IMPROVE-DD: Integrating Multiple Phenotype Resources Optimises Variant Evaluation in genetically determined Developmental Disorders
Stuart Aitken, Helen V. Firth, Caroline F. Wright, et al.
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
Seq_B_LSTM_CNN_HPO: Rare Mendelian Diseases to Genotypes Associations from Multiple Data Sources
Mohamed Elhajabdou, Amr Maged Ehelw, Hassan Eldib, et al.
Applied Cell Biology (2022) Vol. 10, Iss. 3
Closed Access | Times Cited: 1
DeepSVP: Integration of genotype and phenotype for structural variant prioritization using deep learning
Azza Althagafi, Lamia Alsubaie, Nagarajan Kathiresan, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 1
Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes
Morteza Pourreza Shahri, Indika Kahanda
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 1
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