Machine learning and graph analytics in computational biomedicine
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Precision medicine has grown greatly with support from machine learning and data mining tools.
“There has been unprecedented growth in the development of precision medicine supported by ML (machine learning) approaches (Delavan et al., 2017;Peterson et al., 2013;Zou et al., 2017) and data mining tools (Chawla and Davis, 2013;Cheng et al., 2015;Margolies et al., 2016).”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Zou et al., 2017
Cited by
Sorted by citations
Using machine learning approaches for multi-omics data analysis: A review
Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903 · see citing works
Applications of multi‐omics analysis in human diseases
Chen, C., Wang, J., Pan, D., Wang, X., Xu, Y., Yan, J., Wang, L., Yang, X., Yang, M., & Liu, G. (2023) · MedComm · doi:10.1002/mco2.315 · Cited by 545 · see citing works
Self-citationManavalan, B., Basith, S., Shin, T. H., Wei, L., & Lee, G. (2019) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2019.04.019 · Cited by 219 · see citing works
Application of Machine Learning in Microbiology
Qu, K., Guo, F., Liu, X., Lin, Y., & Zou, Q. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.00827 · Cited by 199 · see citing works
Self-citationAnticancer peptides prediction with deep representation learning features
Lv, Z., Cui, F., Zou, Q., Zhang, L., & Xu, L. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab008 · Cited by 145 · see citing works
Self-citationWei, L., Hu, J., Li, F., et al. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby107 · Cited by 128 · see citing works
Self-citationELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm
Li, Y., Niu, M., & Zou, Q. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00012 · Cited by 63 · see citing works
Self-citationIdentifying Antioxidant Proteins by Using Amino Acid Composition and Protein-Protein Interactions
Zhai, Y., Chen, Y., Teng, Z., et al. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.591487 · Cited by 53 · see citing works
“, 2020), sequencing technology and computer technology, data mining and machine learning methods (Quan et al., 2017; Zou et al., 2017) are being exploited to identify antioxidant proteins, and many researchers have already done so.”
BackgroundGuo, Z., Wang, P., Liu, Z., & Zhao, Y. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.584807 · Cited by 50 · see citing works
“…in positive and negative situations, respectively, and ACC is used to evaluate the overall performance of a prediction model (Wang et al., 2008; Zou et al., 2017a,b; Cheng L. et al., 2018; Wang G. et al., 2018; Xue et al., 2018; Xu et al., 2018a, 2019; Ding et al., 2019b; Shen et al., 2019b;…”
MethodPrediction of Anticancer Peptides Using a Low-Dimensional Feature Model
Li, Q., Li, Q., Zhou, W., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00892 · Cited by 48 · see citing works
“In reality, training the machine learning model utilizing high-dimensional features usually behaves poorly, This phenomenon is called Curse of Dimensionality (Wilcox, 1961; Xu et al., 2017; Xu Y. et al., 2018; Zou et al., 2017; Wang et al., 2019).”
Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs
Xuan, P., Dong, Y., Guo, Y., Zhang, T., & Liu, Y. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19123732 · Cited by 41 · see citing works
A Method for Prediction of Thermophilic Protein Based on Reduced Amino Acids and Mixed Features
Feng, C., Ma, Z., Yang, D., Li, X., Zhang, J., & Li, Y. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00285 · Cited by 40 · see citing works
iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier
Dou, L., Li, X., Zhang, L., Xiang, H., & Xu, L. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00314 · Cited by 36 · see citing works
Christinelli, W. A., Shimizu, F. M., Facure, M. H. M., Cerri, R., Oliveira, O. N., Correa, D. S., & Mattoso, L. H. C. (2021) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2021.129696 · Cited by 31 · see citing works
Qu, Y., Zhang, H., Lyu, C., & Liang, C. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00576 · Cited by 27 · see citing works
“Chen et al. (2016a) presented another method WBSMDA to identify the associations between miRNAs and diseases by calculating Gaussian interaction profile kernel similarity for both miRNAs and diseases.”
MethodInfluentialPredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron
Li, Y., Zhang, Z., Teng, Z., & Liu, X. (2020) · Computational and Mathematical Methods in Medicine · doi:10.1155/2020/8845133 · Cited by 27 · see citing works
Self-citationLi, Q., Xu, L., Li, Q., et al. (2020) · Computational and Mathematical Methods in Medicine · doi:10.1155/2020/8852258 · Cited by 22 · see citing works
Predicting Ion Channels Genes and Their Types With Machine Learning Techniques
Han, K., Wang, M., Zhang, L., Wang, Y., Guo, M., Zhao, M. J., Zhao, Q., Zhang, Y., Zeng, N., & Wang, C. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00399 · Cited by 19 · see citing works
“In the last decade, many computational methods have been developed based on machine learning algorithms (Yu et al., 2015; Zou et al., 2017a,b; Stephenson et al., 2019), which are used in different fields, such as drug repositioning (Yu et al., 2016, 2017).”
MethodYang, C., Su, X., Liu, D., Guo, Z., Wang, F., & Lu, Y. (2020) · Frontiers in Marine Science · doi:10.3389/fmars.2020.00032 · Cited by 17 · see citing works
INTEGRATIVE MACHINE LEARNING APPROACHES FOR MULTI-OMICS DATA ANALYSIS IN CANCER RESEARCH
Shoaib, A. S. M., Nishat, N., Raasetti, M., & Arif, I. (2024) · GLOBAL MAINSTREAM JOURNAL · doi:10.62304/ijhm.v1i2.149 · Cited by 11 · see citing works
Deep-Representation-Learning-Based Classification Strategy for Anticancer Peptides
Khan, S. (2024) · Mathematics · doi:10.3390/math12091330 · Cited by 9 · see citing works
Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification
Zhong, G., Liu, H., & Deng, L. (2024) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-024-00640-z · Cited by 9 · see citing works
“Sequence-based deep representation learning embeddings for proteins have emerged with NLP and transfer learning [54].”
Progress in the Development of Antimicrobial Peptide Prediction Tools
Ao, C., Zhang, Y., Li, D., Zhao, Y., & Zou, Q. (2020) · Current Protein and Peptide Science · doi:10.2174/1389203721666200117163802 · Cited by 5 · see citing works
Self-citationIdentification of Anti-cancer Peptides Based on Multi-classifier System
Zhong, W., Zhong, B., Zhang, H., et al. (2019) · Combinatorial Chemistry & High Throughput Screening · doi:10.2174/1386207322666191203141102 · Cited by 5 · see citing works
Ghorbani, M., Swift, S., Taylor, S. J. E., et al. (2020) · Journal of Grid Computing · doi:10.1007/s10723-020-09518-y · Cited by 2 · see citing works
The multiomics revolution in the era of deep learning: Allies or enemies?
Labory, J., & Bottini, S. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13671-9.00017-x · Cited by 1 · see citing works
Contributions on Computational Intelligence in the Medical Sector
Wang, H. T. (2021) · Journal of Biomedical and Sustainable Healthcare Applications · doi:10.53759/0088/jbsha202101001 · Cited by 1 · see citing works
Tan, S., Kong, Y., Leng, S., et al. (2020) · doi:10.21203/rs.3.rs-32351/v1
“The rst possibility is that these factors are not strongly correlated with the survival time and status of patients [21].”
BackgroundTan, S., Huang, Y., Kong, Y., et al. (2020) · doi:10.21203/rs.3.rs-32351/v2
“survival time and status of patients [21].”
- Authors
- Zou, Q., Chen, L., Huang, T., Zhang, Z., & Xu, Y.
- Affiliations
- Tianjin University (CN)
- Shanghai Maritime University (CN)
- Chinese Academy of Sciences (CN)
- University of Rochester (US)
- Wake Forest University (US)
- Corresponding author
- Zou, Quan
- Venue
- Artificial Intelligence in Medicine
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 83
- Pages
- 1
- ISSN
- 0933-3657 (ISSN-L)
- OpenAlex
- W2753041129
- Cited by
- 31
- References
- 0
- Citations by year
- 2024: 4 · 2023: 1 · 2021: 5 · 2020: 12 · 2019: 5 · 2018: 4
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Artificial Intelligence in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Keywords
- machine learning, graph analysis, biomedical networks
- MeSH terms
- Machine Learning, Animals, Humans, Image Interpretation, Computer-Assisted, Computational Biology, Databases, Genetic, Data Mining
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
