Mario Probst

692 total citations
8 papers, 560 citations indexed

About

Mario Probst is a scholar working on Surgery, Molecular Biology and Oncology. According to data from OpenAlex, Mario Probst has authored 8 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Surgery, 6 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in Mario Probst's work include Cholesterol and Lipid Metabolism (6 papers), Drug Transport and Resistance Mechanisms (6 papers) and Advanced Fluorescence Microscopy Techniques (2 papers). Mario Probst is often cited by papers focused on Cholesterol and Lipid Metabolism (6 papers), Drug Transport and Resistance Mechanisms (6 papers) and Advanced Fluorescence Microscopy Techniques (2 papers). Mario Probst collaborates with scholars based in Germany, Poland and Czechia. Mario Probst's co-authors include Gerd Schmitz, Thomas Langmann, Christoph Moehle, Wolfgang Stremmel, Richard Mauerer, Alexandra Zahn, Danuta Kielar, Charalampos Aslanidis, Wolfgang Dietmaier and Marek Naruszewicz and has published in prestigious journals such as Journal of Biological Chemistry, Biochemical and Biophysical Research Communications and Clinical Chemistry.

In The Last Decade

Mario Probst

8 papers receiving 546 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mario Probst Germany 8 310 293 291 49 44 8 560
Judit Cserepes Hungary 7 174 0.6× 416 1.4× 472 1.6× 21 0.4× 62 1.4× 10 786
Mohan V. Chari United States 12 144 0.5× 139 0.5× 126 0.4× 26 0.5× 46 1.0× 19 476
Rudy N. Van Coster Belgium 13 151 0.5× 434 1.5× 56 0.2× 52 1.1× 26 0.6× 18 723
S. Harigae Japan 10 70 0.2× 183 0.6× 178 0.6× 28 0.6× 34 0.8× 11 370
L.W. Estes United States 7 265 0.9× 219 0.7× 109 0.4× 31 0.6× 10 0.2× 9 563
Sumedha Bhagat United States 8 65 0.2× 256 0.9× 371 1.3× 24 0.5× 17 0.4× 8 528
Peter Ward United Kingdom 13 81 0.3× 212 0.7× 93 0.3× 15 0.3× 61 1.4× 32 516
Peng Duan China 15 53 0.2× 266 0.9× 120 0.4× 23 0.5× 104 2.4× 31 549
Akira Kamei Japan 18 231 0.7× 399 1.4× 105 0.4× 23 0.5× 37 0.8× 89 923
Andy Chao Hsuan Lee United States 11 159 0.5× 89 0.3× 70 0.2× 37 0.8× 28 0.6× 27 400

Countries citing papers authored by Mario Probst

Since Specialization
Citations

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

Fields of papers citing papers by Mario Probst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mario Probst

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

All Works

8 of 8 papers shown
1.
Gruber, Michaela, et al.. (2003). Set of fluorochromophores in the wavelength range from 450 to 700 nm and suitable for labeling proteins and amino-modified DNA. Journal of Chromatography B. 793(1). 83–92. 23 indexed citations
2.
Langmann, Thomas, Richard Mauerer, Alexandra Zahn, et al.. (2003). Real-Time Reverse Transcription-PCR Expression Profiling of the Complete Human ATP-Binding Cassette Transporter Superfamily in Various Tissues. Clinical Chemistry. 49(2). 230–238. 212 indexed citations
3.
Buechler, Christa, Alfred Boettcher, Salim Maa Bared, Mario Probst, & Gerd Schmitz. (2002). The carboxyterminus of the ATP-binding cassette transporter A1 interacts with a β2-syntrophin/utrophin complex. Biochemical and Biophysical Research Communications. 293(2). 759–765. 56 indexed citations
4.
Langmann, Thomas, Mustafa Özçürümez, Susanne Heimerl, et al.. (2002). Identification of Sterol-independent Regulatory Elements in the Human ATP-binding Cassette Transporter A1 Promoter. Journal of Biological Chemistry. 277(17). 14443–14450. 57 indexed citations
5.
Bodzioch, Marek, Matthias Krüll, Danuta Kielar, et al.. (2001). Homogeneous assay based on 52 primer sets to scan for mutations of the ABCA1 gene and its application in genetic analysis of a new patient with familial high-density lipoprotein deficiency syndrome. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1537(1). 42–48. 24 indexed citations
6.
Brousseau, Margaret E., Marek Bodzioch, Ernst J. Schaefer, et al.. (2001). Common variants in the gene encoding ATP-binding cassette transporter 1 in men with low HDL cholesterol levels and coronary heart disease. Atherosclerosis. 154(3). 607–611. 76 indexed citations
7.
Kielar, Danuta, Wolfgang Dietmaier, Thomas Langmann, et al.. (2001). Rapid Quantification of Human ABCA1 mRNA in Various Cell Types and Tissues by Real-Time Reverse Transcription-PCR. Clinical Chemistry. 47(12). 2089–2097. 89 indexed citations
8.

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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