Michael Tschannen

3.0k total citations · 1 hit paper
17 papers, 1.3k citations indexed

About

Michael Tschannen is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Michael Tschannen has authored 17 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Genetics and 6 papers in Cancer Research. Recurrent topics in Michael Tschannen's work include Genetic Mapping and Diversity in Plants and Animals (6 papers), Genetic Associations and Epidemiology (3 papers) and Mitochondrial Function and Pathology (3 papers). Michael Tschannen is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (6 papers), Genetic Associations and Epidemiology (3 papers) and Mitochondrial Function and Pathology (3 papers). Michael Tschannen collaborates with scholars based in United States, United Kingdom and China. Michael Tschannen's co-authors include Meijun Du, Liang Wang, Howard J. Jacob, Manish Kohli, Tiezheng Yuan, Rachel L. Dittmar, Stephen N. Thibodeau, Xiaoyi Huang, Lisa A. Boardman and Meihua Liang and has published in prestigious journals such as Cancer Research, Diabetes and Genetics.

In The Last Decade

Michael Tschannen

17 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Characterization of human plasma-derived exosomal RNAs by deep sequencing

2013 846 citations Xiaoyi Huang, Tiezheng Yuan et al. BMC Genomics profile →

Peers

Michael Tschannen

GENET

PRM

CMN

Cord Stähler Germany

Timur R. Samatov Russia

Xu Ding China

Syed-Rehan A. Hussain United States

Zhijun Han China

Miguel Alejandro Lopez‐Ramirez United States

Giuseppina Turturici Italy

Tianqing Kong United States

Bing Su China

Zebin Mao China

Cord Stähler Germany

Michael Tschannen

1.3k ×1.3

1.1k ×1.5

102 ×0.9

GENET

45 ×0.5

PRM

27 ×0.4

CMN

Citations per year, relative to Michael Tschannen Michael Tschannen (= 1×) peers Cord Stähler

Countries citing papers authored by Michael Tschannen

Since Specialization

Citations

This map shows the geographic impact of Michael Tschannen'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 Tschannen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Tschannen more than expected).

Fields of papers citing papers by Michael Tschannen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Tschannen. 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 Tschannen. The network helps show where Michael Tschannen may publish in the future.

Co-authorship network of co-authors of Michael Tschannen

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Tschannen. A scholar is included among the top collaborators of Michael Tschannen 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 Tschannen. Michael Tschannen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Crouse, Wesley L., Gregory R. Keele, Katie Holl, et al.. (2022). Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats. Diabetes. 72(1). 135–148. 7 indexed citations

Zimmermann, Michael T., Angela Mathison, Douglas B. Evans, et al.. (2021). Interpreting Sequence Variation in PDAC-Predisposing Genes Using a Multi-Tier Annotation Approach Performed at the Gene, Patient, and Cohort Level. Frontiers in Oncology. 11. 606820–606820. 4 indexed citations

Cumming, Sarah A., Mark Hamilton, Helen Gregory, et al.. (2018). De novo repeat interruptions are associated with reduced somatic instability and mild or absent clinical features in myotonic dystrophy type 1. European Journal of Human Genetics. 26(11). 1635–1647. 69 indexed citations

Ferdinandusse, Sacha, Joy D. Cogan, D.N. Cooper, et al.. (2018). Clinical heterogeneity of mitochondrial NAD kinase deficiency caused by a NADK2 start loss variant. American Journal of Medical Genetics Part A. 176(3). 692–698. 23 indexed citations

Du, Meijun, Karthik V. Giridhar, Yijun Tian, et al.. (2017). Plasma exosomal miRNAs-based prognosis in metastatic kidney cancer. Oncotarget. 8(38). 63703–63714. 56 indexed citations

Wang, Liang, Shu Xia, Meijun Du, et al.. (2015). Abstract 5231: Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. Cancer Research. 75(15_Supplement). 5231–5231. 1 indexed citations

Xia, Shu, Manish Kohli, Meijun Du, et al.. (2015). Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. Oncotarget. 6(18). 16411–16421. 38 indexed citations

Tsaih, Shirng‐Wern, Katie Holl, Shuang Jia, et al.. (2014). Identification of a Novel Gene for Diabetic Traits in Rats, Mice, and Humans. Genetics. 198(1). 17–29. 38 indexed citations

Du, Meijun, Tiezheng Yuan, Kala F. Schilter, et al.. (2014). Prostate cancer risk locus at 8q24 as a regulatory hub by physical interactions with multiple genomic loci across the genome. Human Molecular Genetics. 24(1). 154–166. 44 indexed citations

10.

Huang, Xiaoyi, Tiezheng Yuan, Michael Tschannen, et al.. (2013). Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genomics. 14(1). 319–319. 846 indexed citations breakdown →

11.

Hall, Cherisse L., Michael Tschannen, Elizabeth A. Worthey, & Christopher J. Kristich. (2013). IreB, a Ser/Thr Kinase Substrate, Influences Antimicrobial Resistance in Enterococcus faecalis. Antimicrobial Agents and Chemotherapy. 57(12). 6179–6186. 43 indexed citations

12.

Worthey, Elizabeth A., David Bick, David Dimmock, et al.. (2012). Clinical diagnostic whole genome sequencing in a paediatric population: experience from our WGS genetics clinic. BMC Proceedings. 6(S6). 2 indexed citations

13.

Woods, Leah C. Solberg, Katie Holl, Michael Tschannen, & William Valdar. (2010). Fine-mapping a locus for glucose tolerance using heterogeneous stock rats. Physiological Genomics. 41(1). 102–108. 36 indexed citations

14.

Bilušić, Marijo, Carol Moreno, Michael Tschannen, et al.. (2008). Genetically Hypertensive Brown Norway Congenic Rat Strains Suggest Intermediate Traits Underlying Genetic Hypertension. Croatian Medical Journal. 49(5). 586–599. 7 indexed citations

15.

Kwitek, Anne E., Norbert Hübner, Michael Tschannen, et al.. (2008). Effects of chromosome 17 on features of the metabolic syndrome in the Lyon hypertensive rat. Physiological Genomics. 33(2). 212–217. 15 indexed citations

16.

Hessner, Martin J., et al.. (2004). Utilization of a labeled tracking oligonucleotide for visualization and quality control of spotted 70-mer arrays. BMC Genomics. 5(1). 12–12. 29 indexed citations

17.

Bilušić, Marijo, Alain Bataillard, Michael Tschannen, et al.. (2004). Mapping the Genetic Determinants of Hypertension, Metabolic Diseases, and Related Phenotypes in the Lyon Hypertensive Rat. Hypertension. 44(5). 695–701. 46 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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