Michael Yu

2.8k total citations
23 papers, 1.4k citations indexed

About

Michael Yu is a scholar working on Molecular Biology, Infectious Diseases and Physiology. According to data from OpenAlex, Michael Yu has authored 23 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 3 papers in Infectious Diseases and 3 papers in Physiology. Recurrent topics in Michael Yu's work include Bioinformatics and Genomic Networks (10 papers), Gut microbiota and health (5 papers) and Biomedical Text Mining and Ontologies (4 papers). Michael Yu is often cited by papers focused on Bioinformatics and Genomic Networks (10 papers), Gut microbiota and health (5 papers) and Biomedical Text Mining and Ontologies (4 papers). Michael Yu collaborates with scholars based in United States, Germany and United Kingdom. Michael Yu's co-authors include Trey Ideker, Jason F. Kreisberg, Jianzhu Ma, Roded Sharan, Keiichiro Ono, Barry Demchak, Samson Fong, Justin K. Huang, Wei Zhang and Daniel E. Carlin and has published in prestigious journals such as Cell, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Michael Yu

23 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael Yu United States	15	1.0k	172	137	121	90	23	1.4k
Kanae Oda Japan	10	1.2k 1.2×	117 0.7×	144 1.1×	192 1.6×	63 0.7×	26	1.9k
Michele Magrane United Kingdom	14	1.7k 1.6×	211 1.2×	80 0.6×	163 1.3×	116 1.3×	21	2.2k
Mónica Chagoyen Spain	21	1.5k 1.4×	151 0.9×	186 1.4×	117 1.0×	70 0.8×	56	2.2k
Bernard de Bono United Kingdom	18	1.6k 1.5×	200 1.2×	136 1.0×	221 1.8×	105 1.2×	54	2.1k
Misha Kapushesky United Kingdom	17	1.4k 1.4×	219 1.3×	175 1.3×	93 0.8×	142 1.6×	24	1.8k
Thomas Jensen Denmark	15	2.2k 2.1×	330 1.9×	153 1.1×	137 1.1×	33 0.4×	26	2.7k
Martijn van Iersel Netherlands	13	1.5k 1.5×	160 0.9×	169 1.2×	198 1.6×	53 0.6×	22	1.9k
Emily Dimmer United Kingdom	14	1.4k 1.3×	177 1.0×	109 0.8×	122 1.0×	138 1.5×	19	1.7k
Andrew Hayes United Kingdom	28	2.0k 2.0×	226 1.3×	115 0.8×	54 0.4×	39 0.4×	56	2.5k
Sandra Orchard United Kingdom	31	2.6k 2.6×	185 1.1×	333 2.4×	183 1.5×	75 0.8×	118	3.2k

Countries citing papers authored by Michael Yu

Since Specialization

Citations

This map shows the geographic impact of Michael Yu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Yu more than expected).

Fields of papers citing papers by Michael Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Yu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Yu. The network helps show where Michael Yu may publish in the future.

Co-authorship network of co-authors of Michael Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Yu. A scholar is included among the top collaborators of Michael Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Yu. Michael Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Veseli, Iva, Matthew S. Schechter, Chiara Vanni, et al.. (2025). Microbes with higher metabolic independence are enriched in human gut microbiomes under stress. eLife. 12. 3 indexed citations

Yu, Michael, Emily C. Fogarty, & A. Murat Eren. (2024). Diverse plasmid systems and their ecology across human gut metagenomes revealed by PlasX and MobMess. Nature Microbiology. 9(3). 830–847. 28 indexed citations

Fogarty, Emily C., Matthew S. Schechter, Karen Lolans, et al.. (2024). A cryptic plasmid is among the most numerous genetic elements in the human gut. Cell. 187(5). 1206–1222.e16. 27 indexed citations

Veseli, Iva, Matthew S. Schechter, Chiara Vanni, et al.. (2023). Microbes with higher metabolic independence are enriched in human gut microbiomes under stress. eLife. 12. 8 indexed citations

Watson, Andrea R., Jessika Füssel, Iva Veseli, et al.. (2023). Metabolic independence drives gut microbial colonization and resilience in health and disease. Genome biology. 24(1). 78–78. 47 indexed citations

Yu, Michael, et al.. (2021). How to use a multicriteria comparison procedure to improve modeling competitions: A comment on Erev et al. (2017).. Psychological Review. 128(5). 995–1005. 4 indexed citations

Haar, Joris van de, Sander Canisius, Michael Yu, et al.. (2019). Identifying Epistasis in Cancer Genomes: A Delicate Affair. Cell. 177(6). 1375–1383. 59 indexed citations

Yu, Michael, Jianzhu Ma, Keiichiro Ono, et al.. (2019). DDOT: A Swiss Army Knife for Investigating Data-Driven Biological Ontologies. Cell Systems. 8(3). 267–273.e3. 12 indexed citations

Huang, Justin K., Daniel E. Carlin, Michael Yu, et al.. (2018). Systematic Evaluation of Molecular Networks for Discovery of Disease Genes. Cell Systems. 6(4). 484–495.e5. 180 indexed citations

10.

Ma, Jianzhu, Michael Yu, Samson Fong, et al.. (2018). Using deep learning to model the hierarchical structure and function of a cell. Nature Methods. 15(4). 290–298. 267 indexed citations

11.

Zhang, Wei, Ana Bojorquez-Gomez, Daniel Ortiz Velez, et al.. (2018). A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nature Genetics. 50(4). 613–620. 85 indexed citations

12.

Huang, Justin K., Daniel E. Carlin, Michael Yu, et al.. (2018). Abstract 1310: Systematic evaluation of gene networks for discovery of disease genes. Cancer Research. 78(13_Supplement). 1310–1310. 1 indexed citations

13.

Yu, Michael, Jianzhu Ma, Jasmin Fisher, et al.. (2018). Visible Machine Learning for Biomedicine. Cell. 173(7). 1562–1565. 100 indexed citations

14.

Kramer, Michael H., Jean‐Claude Farré, Michael Yu, et al.. (2017). Active Interaction Mapping Reveals the Hierarchical Organization of Autophagy. Molecular Cell. 65(4). 761–774.e5. 21 indexed citations

15.

Wang, Tina, Brian Tsui, Jason F. Kreisberg, et al.. (2017). Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment. Genome biology. 18(1). 57–57. 205 indexed citations

16.

Wang, Sheng, Jianzhu Ma, Michael Yu, et al.. (2017). Annotating gene sets by mining large literature collections with protein networks. PubMed. 23. 602–613. 12 indexed citations

17.

Yu, Michael, Michael H. Kramer, Janusz Dutkowski, et al.. (2016). Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems. Cell Systems. 2(2). 77–88. 52 indexed citations

18.

Will, Sebastian, Michael Yu, & Bonnie Berger. (2013). Structure-based whole-genome realignment reveals many novel noncoding RNAs. Genome Research. 23(6). 1018–1027. 31 indexed citations

19.

Dutkowski, Janusz, Keiichiro Ono, Michael H. Kramer, et al.. (2013). NeXO Web: the NeXO ontology database and visualization platform. Nucleic Acids Research. 42(D1). D1269–D1274. 10 indexed citations

20.

Williamson, Michael P., et al.. (2008). BEOL parametric variation control with FDC data. 291–293. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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