Volkhard Rippe

931 total citations
26 papers, 673 citations indexed

About

Volkhard Rippe is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Genetics. According to data from OpenAlex, Volkhard Rippe has authored 26 papers receiving a total of 673 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 11 papers in Endocrinology, Diabetes and Metabolism and 6 papers in Genetics. Recurrent topics in Volkhard Rippe's work include Thyroid Cancer Diagnosis and Treatment (11 papers), MicroRNA in disease regulation (4 papers) and RNA modifications and cancer (4 papers). Volkhard Rippe is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (11 papers), MicroRNA in disease regulation (4 papers) and RNA modifications and cancer (4 papers). Volkhard Rippe collaborates with scholars based in Germany, Italy and United States. Volkhard Rippe's co-authors include Jörn Bullerdiek, Gazanfer Belge, Norbert Drieschner, Ulrich Bonk, Bernd Kazmierczak, H. Hameister, Monika Wilda, Klaus Drechsler, Piere Rogalla and J. Bullerdiek and has published in prestigious journals such as PLoS ONE, Oncogene and Biochemical and Biophysical Research Communications.

In The Last Decade

Volkhard Rippe

26 papers receiving 663 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Volkhard Rippe Germany 13 401 302 99 91 68 26 673
Antoine Daunay France 15 508 1.3× 172 0.6× 206 2.1× 52 0.6× 50 0.7× 26 796
Sevilhan Artan Türkiye 18 308 0.8× 106 0.4× 187 1.9× 26 0.3× 61 0.9× 84 760
Pamela Mamers Australia 17 459 1.1× 121 0.4× 86 0.9× 55 0.6× 25 0.4× 22 912
Qianren Jin Sweden 8 460 1.1× 142 0.5× 122 1.2× 40 0.4× 74 1.1× 10 600
GEETHA PERINCHERY United States 15 459 1.1× 144 0.5× 171 1.7× 73 0.8× 87 1.3× 23 796
Murilo Vieira Geraldo Brazil 15 457 1.1× 390 1.3× 28 0.3× 120 1.3× 30 0.4× 36 798
Marga Schepens Netherlands 14 539 1.3× 112 0.4× 336 3.4× 49 0.5× 33 0.5× 20 779
Paola Romeo Italy 12 275 0.7× 195 0.6× 23 0.2× 140 1.5× 25 0.4× 32 560
Xiaobing Niu China 16 686 1.7× 575 1.9× 80 0.8× 27 0.3× 29 0.4× 37 979
Ilze Štrumfa Latvia 13 171 0.4× 107 0.4× 48 0.5× 53 0.6× 24 0.4× 55 580

Countries citing papers authored by Volkhard Rippe

Since Specialization
Citations

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

Fields of papers citing papers by Volkhard Rippe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Volkhard Rippe

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

All Works

20 of 20 papers shown
1.
Stracke, Sylvia, Rainer Rettig, Uwe Lendeckel, et al.. (2017). Identification of miR-16 as an endogenous reference gene for the normalization of urinary exosomal miRNA expression data from CKD patients. PLoS ONE. 12(8). e0183435–e0183435. 98 indexed citations
2.
Rippe, Volkhard, et al.. (2012). Activation of the two microRNA clusters C19MC and miR-371-3 does not play prominent role in thyroid cancer. Molecular Cytogenetics. 5(1). 40–40. 7 indexed citations
3.
Sendt, Wolfgang, Volkhard Rippe, Inga Flor, Norbert Drieschner, & Jörn Bullerdiek. (2012). Monosomy and ring chromosome 13 in a thyroid nodular goiter—do we underestimate its relevance in benign thyroid lesions?. Cancer Genetics. 205(3). 128–130. 2 indexed citations
4.
Flor, Inga, et al.. (2012). Abundant expression and hemimethylation of C19MC in cell cultures from placenta-derived stromal cells. Biochemical and Biophysical Research Communications. 422(3). 411–416. 32 indexed citations
5.
Belge, Gazanfer, Siegfried Loeschke, Werner Wosniok, et al.. (2011). Decrease in thyroid adenoma associated (THADA) expression is a marker of dedifferentiation of thyroid tissue. BMC Clinical Pathology. 11(1). 13–13. 9 indexed citations
6.
7.
Drieschner, Norbert, et al.. (2011). On the prevalence of the PAX8-PPARG fusion resulting from the chromosomal translocation t(2;3)(q13;p25) in adenomas of the thyroid. Cancer Genetics. 204(6). 334–339. 12 indexed citations
8.
Rippe, Volkhard, Verena Lorenz, Norbert Drieschner, et al.. (2010). The Two Stem Cell MicroRNA Gene Clusters C19MC and miR-371-3 Are Activated by Specific Chromosomal Rearrangements in a Subgroup of Thyroid Adenomas. PLoS ONE. 5(3). e9485–e9485. 87 indexed citations
9.
10.
Drieschner, Norbert, et al.. (2006). Evidence for a 3p25 Breakpoint Hot Spot Region in Thyroid Tumors of Follicular Origin. Thyroid. 16(11). 1091–1096. 17 indexed citations
11.
Rensing, Ludger, et al.. (2005). Mensch im Stress. 18 indexed citations
12.
Rippe, Volkhard, Norbert Drieschner, Hugo Murua Escobar, et al.. (2003). Identification of a gene rearranged by 2p21 aberrations in thyroid adenomas. Oncogene. 22(38). 6111–6114. 50 indexed citations
13.
Belge, Gazanfer, et al.. (2001). Delineation of a 150-kb breakpoint cluster in benign thyroid tumors with 19q13.4 aberrations. Cytogenetic and Genome Research. 93(1-2). 48–51. 14 indexed citations
14.
Belge, Gazanfer, et al.. (2001). Molecular cytogenetic investigations define a subgroup of thyroid adenomas with 2p21 breakpoints clustered to a region of less than 450 kb. Cytogenetic and Genome Research. 95(3-4). 189–191. 6 indexed citations
15.
Kazmierczak, Bernd, Roberta Napolitano, Gennaro Chiappetta, et al.. (2000). A 12q13 Translocation Involving the HMGI-C Gene in Richter Transformation of a Chronic Lymphocytic Leukemia. Cancer Genetics and Cytogenetics. 119(1). 70–73. 18 indexed citations
16.
Rippe, Volkhard, et al.. (1999). A KRAB zinc finger protein gene is the potential target of 19q13 translocation in benign thyroid tumors. Genes Chromosomes and Cancer. 26(3). 229–236. 3 indexed citations
17.
Wilda, Monika, et al.. (1998). The expression pattern of theHmgic gene during development. Genes Chromosomes and Cancer. 23(4). 350–357. 96 indexed citations
18.
Rogalla, Piere, Klaus Drechsler, Bernd Kazmierczak, et al.. (1997). Expression ofHMGI-C, a member of the high mobility group protein family, in a subset of breast cancers: Relationship to histologic grade. Molecular Carcinogenesis. 19(3). 153–156. 95 indexed citations
19.
Belge, Gazanfer, Emilio García García, Volkhard Rippe, et al.. (1997). Breakpoints of 19q13 translocations of benign thyroid tumors map within a 400 kilobase region. Genes Chromosomes and Cancer. 20(2). 201–203. 6 indexed citations
20.
Belge, Gazanfer, et al.. (1994). A characteristic sequence of trisomies starting with trisomy 7 in benign thyroid tumors. Human Genetics. 94(2). 198–202. 37 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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