{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T16:07:40Z","timestamp":1753891660295,"version":"3.41.2"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T00:00:00Z","timestamp":1686700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>Studies have shown that microbes are closely related to human health. Clarifying the relationship between microbes and diseases that cause health problems can provide new solutions for the treatment, diagnosis, and prevention of diseases, and provide strong protection for human health. Currently, more and more similarity fusion methods are available to predict potential microbe-disease associations. However, existing methods have noise problems in the process of similarity fusion. To address this issue, we propose a method called MSIF-LNP that can efficiently and accurately identify potential connections between microbes and diseases, and thus clarify the relationship between microbes and human health. This method is based on matrix factorization denoising similarity fusion (MSIF) and bidirectional linear neighborhood propagation (LNP) techniques. First, we use non-linear iterative fusion to obtain a similarity network for microbes and diseases by fusing the initial microbe and disease similarities, and then reduce noise by using matrix factorization. Next, we use the initial microbe-disease association pairs as label information to perform linear neighborhood label propagation on the denoised similarity network of microbes and diseases. This enables us to obtain a score matrix for predicting microbe-disease relationships. We evaluate the predictive performance of MSIF-LNP and seven other advanced methods through 10-fold cross-validation, and the experimental results show that MSIF-LNP outperformed the other seven methods in terms of AUC. In addition, the analysis of Cystic fibrosis and Obesity cases further demonstrate the predictive ability of this method in practical applications.<\/jats:p>","DOI":"10.3389\/fmicb.2023.1216811","type":"journal-article","created":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T05:41:43Z","timestamp":1686721303000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["MSIF-LNP: microbial and human health association prediction based on matrix factorization noise reduction for similarity fusion and bidirectional linear neighborhood label propagation"],"prefix":"10.3389","volume":"14","author":[{"given":"Hui","family":"Xiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tengjie","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2023,6,14]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1249\/JES.0000000000000096","article-title":"Exercise is a novel promoter of intestinal health and microbial diversity","volume":"45","author":"Campbell","year":"2017","journal-title":"Exerc. 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Med."},{"key":"ref9","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1007\/s12539-022-00514-2","article-title":"MVGCNMDA: multi-view graph augmentation convolutional network for uncovering disease-related microbes","volume":"14","author":"Hua","year":"2022","journal-title":"Interdiscip Sci Comput Life Sci"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"233","DOI":"10.3389\/fmicb.2017.00233","article-title":"PBHMDA: path-based human microbe-disease association prediction","volume":"8","author":"Huang","year":"2017","journal-title":"Front. Microbiol."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12967-017-1304-7","article-title":"Prediction of microbe\u2013disease association from the integration of neighbor and graph with collaborative recommendation model","volume":"15","author":"Huang","year":"2017","journal-title":"J. Transl. Med."},{"key":"ref12","doi-asserted-by":"publisher","first-page":"597","DOI":"10.3390\/ijms24010597","article-title":"Biofilm formation by Staphylococcus aureus in the specific context of cystic fibrosis","volume":"24","author":"Jean-Pierre","year":"2023","journal-title":"Int. J. Mol. Sci."},{"key":"ref13","doi-asserted-by":"publisher","first-page":"618","DOI":"10.3389\/fgene.2018.00618","article-title":"MDA-SKF: similarity kernel fusion for accurately discovering miRNA-disease association","volume":"9","author":"Jiang","year":"2018","journal-title":"Front. Genet."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.4081\/monaldi.2021.1501","article-title":"Pulmonary rehabilitation for cystic fibrosis: a narrative review of current literature","volume":"91","author":"Kalamara","year":"2021","journal-title":"Monaldi Arch. Chest Dis."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"2502","DOI":"10.1109\/TCBB.2020.2986459","article-title":"Identifying microbe-disease association based on a novel back-propagation neural network model","volume":"18","author":"Li","year":"2020","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"1414","DOI":"10.1016\/j.csbj.2022.12.053","article-title":"MNNMDA: predicting human microbe-disease association via a method to minimize matrix nuclear norm. Computational and structural","volume":"21","author":"Liu","year":"2023","journal-title":"Biotechnol. J."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"bbaa146","DOI":"10.1093\/bib\/bbaa146","article-title":"Predicting human microbe\u2013disease associations via graph attention networks with inductive matrix completion","volume":"22","author":"Long","year":"2021","journal-title":"Brief. Bioinform."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1109\/TCBB.2018.2883041","article-title":"NTSHMDA: prediction of human microbe-disease association based on random walk by integrating network topological similarity","volume":"17","author":"Luo","year":"2018","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"610","DOI":"10.3390\/genes12050610","article-title":"Achromobacter xylosoxidans and Stenotrophomonas maltophilia: emerging pathogens well-armed for life in the cystic fibrosis patients\u2019 lung","volume":"12","author":"Menetrey","year":"2021","journal-title":"Genes"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"bbac478","DOI":"10.1093\/bib\/bbac478","article-title":"DAESTB: inferring associations of small molecule\u2013miRNA via a scalable tree boosting model based on deep autoencoder","volume":"23","author":"Peng","year":"","journal-title":"Brief. Bioinform."},{"key":"ref21","doi-asserted-by":"publisher","first-page":"bbac155","DOI":"10.1093\/bib\/bbac155","article-title":"RNMFLP: predicting circRNA\u2013disease associations based on robust nonnegative matrix factorization and label propagation","volume":"23","author":"Peng","year":"","journal-title":"Brief. Bioinform."},{"key":"ref22","doi-asserted-by":"publisher","first-page":"2440","DOI":"10.3389\/fmicb.2018.02440","article-title":"Human microbe-disease association prediction based on adaptive boosting","volume":"9","author":"Peng","year":"2018","journal-title":"Front. Microbiol."},{"key":"ref23","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1002\/oby.22175","article-title":"Gut microbes and health: a focus on the mechanisms linking microbes, obesity, and related disorders","volume":"26","author":"Rastelli","year":"2018","journal-title":"Obesity"},{"key":"ref24","first-page":"746","volume-title":"A novel approach based on bi-random walk to predict microbe-disease associations[C]\/\/intelligent computing methodologies: 14th international conference, ICIC 2018, Wuhan, China, august 15-18, 2018, proceedings, part III 14","author":"Shen","year":"2018"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1186\/s12859-018-2274-3","article-title":"BMCMDA: a novel model for predicting human microbe-disease associations via binary matrix completion","volume":"19","author":"Shi","year":"2018","journal-title":"BMC Bioinform."},{"key":"ref26","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1038\/nrmicro2974","article-title":"The gut microbiota\u2014masters of host development and physiology","volume":"11","author":"Sommer","year":"2013","journal-title":"Nat. Rev. Microbiol."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"bbac266","DOI":"10.1093\/bib\/bbac266","article-title":"A deep learning method for predicting metabolite\u2013disease associations via graph neural network","volume":"23","author":"Sun","year":"2022","journal-title":"Brief. Bioinform."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1007\/s12016-018-8719-7","article-title":"The human microbiota and asthma","volume":"57","author":"Ver Heul","year":"2019","journal-title":"Clin. Rev. Allergy Immunol."},{"key":"ref29","doi-asserted-by":"publisher","first-page":"7601","DOI":"10.1038\/s41598-017-08127-2","article-title":"LRLSHMDA: Laplacian regularized least squares for human microbe\u2013disease association prediction","volume":"7","author":"Wang","year":"2017","journal-title":"Sci. Rep."},{"key":"ref30","doi-asserted-by":"publisher","first-page":"2399","DOI":"10.1109\/TCBB.2021.3082183","article-title":"Predicting microbe-disease association based on multiple similarities and LINE algorithm","volume":"19","author":"Wang","year":"2021","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"ref31","doi-asserted-by":"publisher","first-page":"106464","DOI":"10.1016\/j.compbiomed.2022.106464","article-title":"Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism","volume":"153","author":"Wang","year":"2023","journal-title":"Comput. Biol. Med."},{"key":"ref32","doi-asserted-by":"publisher","first-page":"bbac080","DOI":"10.1093\/bib\/bbac080","article-title":"Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models","volume":"23","author":"Wang","year":"2022","journal-title":"Brief. 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Bioinform."},{"key":"ref36","doi-asserted-by":"publisher","first-page":"bbab431","DOI":"10.1093\/bib\/bbab431","article-title":"Ensemble of kernel ridge regression-based small molecule\u2013miRNA association prediction in human disease","volume":"23","author":"Wang","year":"2022","journal-title":"Brief. Bioinform."},{"key":"ref37","doi-asserted-by":"publisher","first-page":"bbaa157","DOI":"10.1093\/bib\/bbaa157","article-title":"A survey on predicting microbe-disease associations: biological data and computational methods","volume":"22","author":"Wen","year":"2021","journal-title":"Brief. Bioinform."},{"key":"ref38","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1111\/resp.12765","article-title":"Physical activity and health of adults with cystic fibrosis","volume":"21","author":"Williams","year":"2016","journal-title":"Respirology"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"106687","DOI":"10.1109\/ACCESS.2019.2930453","article-title":"mHMDA: human microbe-disease association prediction by matrix completion and multi-source information","volume":"7","author":"Wu","year":"2019","journal-title":"IEEE Access"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.ins.2015.02.024","article-title":"Learning similarity with cosine similarity ensemble","volume":"307","author":"Xia","year":"2015","journal-title":"Inf. Sci."},{"key":"ref41","doi-asserted-by":"publisher","first-page":"bbac595","DOI":"10.1093\/bib\/bbac595","article-title":"Predicting lncRNA\u2013disease associations based on combining selective similarity matrix fusion and bidirectional linear neighborhood label propagation","volume":"24","author":"Xie","year":"2023","journal-title":"Brief. Bioinform."},{"key":"ref42","doi-asserted-by":"publisher","first-page":"92","DOI":"10.2174\/1574893618666221118092849","article-title":"DHOSGR: lncRNA-disease association prediction based on decay high-order similarity and graph-regularized matrix completion","volume":"18","author":"Xie","year":"2023","journal-title":"Curr. Bioinforma."},{"key":"ref43","doi-asserted-by":"publisher","first-page":"2013762","DOI":"10.1080\/19490976.2021.2013762","article-title":"Dietary S. maltophilia induces supersized lipid droplets by enhancing lipogenesis and ER-LD contacts in C. elegans","volume":"14","author":"Xie","year":"2022","journal-title":"Gut Microbes"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"1644","DOI":"10.1109\/JBHI.2022.3229473","article-title":"NTBiRW: a novel neighbor model based on two-tier bi-random walk for predicting potential disease-related microbes","volume":"27","author":"Yin","year":"2023","journal-title":"IEEE J. Biomed. Health Inform."},{"article-title":"Sparse graph Cascade multi-kernel fusion contrastive learning for microbe-disease association prediction","year":"2023","author":"Yu","key":"ref45"},{"key":"ref46","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1016\/j.neucom.2017.07.065","article-title":"The linear neighborhood propagation method for predicting long non-coding RNA\u2013protein interactions","volume":"273","author":"Zhang","year":"2018","journal-title":"Neurocomputing"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"bbaa158","DOI":"10.1093\/bib\/bbaa158","article-title":"Microbes and complex diseases: from experimental results to computational models","volume":"22","author":"Zhao","year":"2021","journal-title":"Brief. 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