Margit Pacher

813 total citations
7 papers, 694 citations indexed

About

Margit Pacher is a scholar working on Molecular Biology, Oncology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Margit Pacher has authored 7 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Margit Pacher's work include Protein Kinase Regulation and GTPase Signaling (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers) and Molecular Biology Techniques and Applications (2 papers). Margit Pacher is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers) and Molecular Biology Techniques and Applications (2 papers). Margit Pacher collaborates with scholars based in Austria, Germany and Switzerland. Margit Pacher's co-authors include Klaus Podar, Manuela Baccarini, Markus Kubicek, Martin Schreiber, Dietmar Abraham, Christian Stratowa, Wolfgang Sommergruber, E. Kubista, Stephen M. Dilworth and Harald Mischak and has published in prestigious journals such as Journal of Biological Chemistry, Cancer Research and Clinical Cancer Research.

In The Last Decade

Margit Pacher

7 papers receiving 689 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Margit Pacher Austria	7	517	172	131	69	56	7	694
Peterson Pathrose United States	14	399 0.8×	173 1.0×	97 0.7×	68 1.0×	63 1.1×	20	660
Anne Chotteau‐Lelièvre France	16	547 1.1×	175 1.0×	120 0.9×	64 0.9×	36 0.6×	21	749
Francisco E. Gago Argentina	13	348 0.7×	234 1.4×	169 1.3×	112 1.6×	26 0.5×	20	568
Susanne Radke United States	10	526 1.0×	204 1.2×	84 0.6×	113 1.6×	47 0.8×	11	695
Moulun Luo United States	17	649 1.3×	134 0.8×	78 0.6×	81 1.2×	33 0.6×	32	830
Isabel Martínez-Lacaci Spain	20	698 1.4×	409 2.4×	131 1.0×	141 2.0×	54 1.0×	30	992
Huajun Yan United States	11	872 1.7×	188 1.1×	88 0.7×	89 1.3×	112 2.0×	13	1.0k
Nilotpal Roy United States	17	682 1.3×	386 2.2×	160 1.2×	58 0.8×	71 1.3×	20	1.1k
Nagendra K. Chaturvedi United States	18	482 0.9×	144 0.8×	148 1.1×	47 0.7×	86 1.5×	42	775
Angelo Boccia Italy	15	566 1.1×	228 1.3×	119 0.9×	50 0.7×	48 0.9×	26	837

Countries citing papers authored by Margit Pacher

Since Specialization

Citations

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

Fields of papers citing papers by Margit Pacher

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Margit Pacher

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

All Works

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7 of 7 papers shown

Pacher, Margit, Michael J. Seewald, Mario Mikula, et al.. (2006). Impact of constitutive IGF1/IGF2 stimulation on the transcriptional program of human breast cancer cells. Carcinogenesis. 28(1). 49–59. 60 indexed citations

Vinatzer, Ursula, Brigitta Dampier, Berthold Streubel, et al.. (2005). Expression of HER2 and the Coamplified Genes GRB7 and MLN64 in Human Breast Cancer: Quantitative Real-time Reverse Transcription-PCR as a Diagnostic Alternative to Immunohistochemistry and Fluorescence In situ Hybridization. Clinical Cancer Research. 11(23). 8348–8357. 82 indexed citations

Amatschek, Stefan, Ulrich Koenig, Herbert Auer, et al.. (2004). Tissue-Wide Expression Profiling Using cDNA Subtraction and Microarrays to Identify Tumor-Specific Genes. Cancer Research. 64(3). 844–856. 203 indexed citations

Singer, Christian F., W. Koestler, Margit Pacher, et al.. (2004). Insulin-Like Growth Factor (IGF)-I and IGF-II Serum Concentrations in Patients with Benign and Malignant Breast Lesions. Clinical Cancer Research. 10(12). 4003–4009. 33 indexed citations

Kubicek, Markus, Margit Pacher, Dietmar Abraham, et al.. (2002). Dephosphorylation of Ser-259 Regulates Raf-1 Membrane Association. Journal of Biological Chemistry. 277(10). 7913–7919. 100 indexed citations

Schmetterer, Georg, Ana Valladares, Dietmar Pils, et al.. (2001). The coxBAC Operon Encodes a Cytochrome c Oxidase Required for Heterotrophic Growth in the Cyanobacterium Anabaena variabilis Strain ATCC 29413. Journal of Bacteriology. 183(21). 6429–6434. 25 indexed citations

Abraham, Dietmar, Klaus Podar, Margit Pacher, et al.. (2000). Raf-1-associated Protein Phosphatase 2A as a Positive Regulator of Kinase Activation. Journal of Biological Chemistry. 275(29). 22300–22304. 191 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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