BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Fukui H, Nishida A, Matsuda S, Kira F, Watanabe S, Kuriyama M, Kawakami K, Aikawa Y, Oda N, Arai K, Matsunaga A, Nonaka M, Nakai K, Shinmura W, Matsumoto M, Morishita S, Takeda AK, Miwa H. Usefulness of Machine Learning-Based Gut Microbiome Analysis for Identifying Patients with Irritable Bowels Syndrome. J Clin Med 2020;9:E2403. [PMID: 32727141 DOI: 10.3390/jcm9082403] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Saa P, Urrutia A, Silva-Andrade C, Martín AJ, Garrido D. Modeling approaches for probing cross-feeding interactions in the human gut microbiome. Comput Struct Biotechnol J 2022;20:79-89. [PMID: 34976313 DOI: 10.1016/j.csbj.2021.12.006] [Reference Citation Analysis]
2 Oka A, Ishimura N, Ishihara S. A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology. Diagnostics (Basel) 2021;11:1719. [PMID: 34574060 DOI: 10.3390/diagnostics11091719] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
3 Sabater C, Ruiz L, Margolles A. A Machine Learning Approach to Study Glycosidase Activities from Bifidobacterium. Microorganisms 2021;9:1034. [PMID: 34064844 DOI: 10.3390/microorganisms9051034] [Reference Citation Analysis]
4 Young RB, Marcelino VR, Chonwerawong M, Gulliver EL, Forster SC. Key Technologies for Progressing Discovery of Microbiome-Based Medicines. Front Microbiol 2021;12:685935. [PMID: 34239510 DOI: 10.3389/fmicb.2021.685935] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
5 Wang X, Fukui H, Ran Y, Xu X, Ebisutani N, Nakanishi T, Tanaka Y, Maeda A, Makizaki Y, Tomita T, Oshima T, Miwa H. Probiotic Bifidobacterium bifidum G9-1 Has a Preventive Effect on the Acceleration of Colonic Permeability and M1 Macrophage Population in Maternally Separated Rats. Biomedicines 2021;9:641. [PMID: 34204993 DOI: 10.3390/biomedicines9060641] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Phan J, Nair D, Jain S, Montagne T, Flores DV, Nguyen A, Dietsche S, Gombar S, Cotter P. Alterations in Gut Microbiome Composition and Function in Irritable Bowel Syndrome and Increased Probiotic Abundance with Daily Supplementation. mSystems 2021;:e0121521. [PMID: 34726487 DOI: 10.1128/mSystems.01215-21] [Reference Citation Analysis]
7 Okuda S, Shimada Y, Tajima Y, Yuza K, Hirose Y, Ichikawa H, Nagahashi M, Sakata J, Ling Y, Miura N, Sugai M, Watanabe Y, Takeuchi S, Wakai T. Profiling of host genetic alterations and intra-tumor microbiomes in colorectal cancer. Comput Struct Biotechnol J 2021;19:3330-8. [PMID: 34188781 DOI: 10.1016/j.csbj.2021.05.049] [Reference Citation Analysis]
8 Marcos-Zambrano LJ, Karaduzovic-Hadziabdic K, Loncar Turukalo T, Przymus P, Trajkovik V, Aasmets O, Berland M, Gruca A, Hasic J, Hron K, Klammsteiner T, Kolev M, Lahti L, Lopes MB, Moreno V, Naskinova I, Org E, Paciência I, Papoutsoglou G, Shigdel R, Stres B, Vilne B, Yousef M, Zdravevski E, Tsamardinos I, Carrillo de Santa Pau E, Claesson MJ, Moreno-Indias I, Truu J. Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment. Front Microbiol 2021;12:634511. [PMID: 33737920 DOI: 10.3389/fmicb.2021.634511] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 10.0] [Reference Citation Analysis]
9 Barone M, D'Amico F, Fabbrini M, Rampelli S, Brigidi P, Turroni S. Over-feeding the gut microbiome: A scoping review on health implications and therapeutic perspectives. World J Gastroenterol 2021; 27(41): 7041-7064 [PMID: 34887627 DOI: 10.3748/wjg.v27.i41.7041] [Reference Citation Analysis]