Markus M. Nöethen

2.8k total citations
9 papers, 218 citations indexed

About

Markus M. Nöethen is a scholar working on Genetics, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Markus M. Nöethen has authored 9 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Genetics, 2 papers in Molecular Biology and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Markus M. Nöethen's work include Genetic Associations and Epidemiology (4 papers), Bipolar Disorder and Treatment (2 papers) and Stress Responses and Cortisol (1 paper). Markus M. Nöethen is often cited by papers focused on Genetic Associations and Epidemiology (4 papers), Bipolar Disorder and Treatment (2 papers) and Stress Responses and Cortisol (1 paper). Markus M. Nöethen collaborates with scholars based in Germany, United States and Belgium. Markus M. Nöethen's co-authors include Marcella Rietschel, Francis J. McMahon, Nick Craddock, Sven Cichon, Amber E. Baum, Marian Hamshere, M. Adela Mansilla, Margaret M. Parker, Kerstin U. Ludwig and Terri H. Beaty and has published in prestigious journals such as Annals of the Rheumatic Diseases, Molecular Psychiatry and BMC Bioinformatics.

In The Last Decade

Markus M. Nöethen

8 papers receiving 214 citations

Peers

Markus M. Nöethen

GENET

MB

PMH

GENET

SURGE

Cheuk Wing Fung China

M R James United States

Matthew J. Gazzellone Canada

M. A. Mori Spain

Eugene Yu United States

Emma McCann United Kingdom

J A Hurst United Kingdom

Rani Sachdev Australia

Jin Szatkiewicz United States

Simone Schröder Germany

Cheuk Wing Fung China

Markus M. Nöethen

54 ×0.3

GENET

67 ×1.2

MB

31 ×0.8

PMH

22 ×0.6

GENET

13 ×0.6

SURGE

Citations per year, relative to Markus M. Nöethen Markus M. Nöethen (= 1×) peers Cheuk Wing Fung

Countries citing papers authored by Markus M. Nöethen

Since Specialization

Citations

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

Fields of papers citing papers by Markus M. Nöethen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus M. Nöethen. 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 Markus M. Nöethen. The network helps show where Markus M. Nöethen may publish in the future.

Co-authorship network of co-authors of Markus M. Nöethen

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

All Works

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9 of 9 papers shown

1.

Bauer, C., Pantelis Karakostas, Ramona Dolscheid‐Pommerich, et al.. (2024). POS0336 PROSPECTIVE STUDY ON PREVALENCE AND DIAGNOSTIC ALGORITHMS FOR HYPOPHOSPHATASIA DETECTION IN ADULT RHEUMATOLOGY PATIENTS - THE COHIR STUDY. Annals of the Rheumatic Diseases. 83. 472–473.

2.

Wienbergen, Harm, Andreas Fach, Jeanette Erdmann, et al.. (2020). New technologies for intensive prevention programs after myocardial infarction: rationale and design of the NET-IPP trial. Clinical Research in Cardiology. 110(2). 153–161. 5 indexed citations

3.

Lacour, André, Dmitriy Drichel, Christine Herold, et al.. (2015). Novel genetic matching methods for handling population stratification in genome-wide association studies. BMC Bioinformatics. 16(1). 84–84. 6 indexed citations

4.

Drichel, Dmitriy, Christine Herold, André Lacour, et al.. (2014). Rare Variant Testing of Imputed Data: An Analysis Pipeline Typified. Human Heredity. 78(3-4). 164–178. 1 indexed citations

5.

Beaty, Terri H., Margaret A. Taub, Alan F. Scott, et al.. (2013). Confirming genes influencing risk to cleft lip with/without cleft palate in a case–parent trio study. Human Genetics. 132(7). 771–781. 112 indexed citations

6.

Walter, Henrik, Knut Schnell, Susanne Erk, et al.. (2011). Genetic risk for schizophrenia impacts Theory-of-Mind-related brain activation. Molecular Psychiatry. 16(4). 353–353. 5 indexed citations

7.

Grigoroiu‐Serbânescu, Maria, Marcella Rietschel, Thomas G. Schulze, et al.. (2010). PW01-12 - Two or Three Age-of-Onset Groups in Bipolar I Disorder? Findings of Commingling Analysis in Romanian and German Bipolar I Patients. European Psychiatry. 25(S1). 1 indexed citations

8.

Baum, Amber E., Marian Hamshere, Sven Cichon, et al.. (2008). Meta-analysis of two genome-wide association studies of bipolar disorder reveals important points of agreement. Molecular Psychiatry. 13(5). 466–467. 78 indexed citations

9.

Henning, U., Fabio Rivas, Guillermo Hernández Orozco, et al.. (2004). Increased levels of glucocorticoid receptors and enhanced glucocorticoid receptor auto-regulation after hydrocortisone challenge in B-lymphoblastoids from patients with affective disorders. Psychoneuroendocrinology. 30(4). 325–332. 10 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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