Anja Nohe

4.5k total citations · 3 hit papers
63 papers, 3.5k citations indexed

About

Anja Nohe is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Anja Nohe has authored 63 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 16 papers in Oncology and 13 papers in Cell Biology. Recurrent topics in Anja Nohe's work include TGF-β signaling in diseases (24 papers), Bone Metabolism and Diseases (20 papers) and Bone health and treatments (13 papers). Anja Nohe is often cited by papers focused on TGF-β signaling in diseases (24 papers), Bone Metabolism and Diseases (20 papers) and Bone health and treatments (13 papers). Anja Nohe collaborates with scholars based in United States, Canada and Germany. Anja Nohe's co-authors include Beth Bragdon, Hemanth Akkiraju, Petra Knaus, Walter Sebald, Yoav I. Henis, Oleksandra Moseychuk, Daniel King, Daniel Halloran, JoAnne Julian and Nils O. Petersen and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Bone and Joint Surgery and Journal of Cell Science.

In The Last Decade

Anja Nohe

61 papers receiving 3.4k citations

Hit Papers

Bone Morphogenetic Proteins: A critical review 2010 2026 2015 2020 2010 2015 2020 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anja Nohe United States 24 2.1k 651 559 439 353 63 3.5k
Su‐Li Cheng United States 32 2.4k 1.1× 635 1.0× 682 1.2× 402 0.9× 478 1.4× 53 4.4k
Janet L. Crane United States 27 1.8k 0.9× 778 1.2× 697 1.2× 371 0.8× 479 1.4× 48 3.5k
Efthimia K. Basdra Greece 32 1.6k 0.8× 333 0.5× 343 0.6× 294 0.7× 295 0.8× 89 3.1k
Gabriel Mbalaviele United States 35 2.7k 1.3× 664 1.0× 816 1.5× 286 0.7× 392 1.1× 78 4.2k
Mitsuyasu Kato Japan 41 3.6k 1.7× 477 0.7× 1.0k 1.9× 290 0.7× 533 1.5× 125 5.4k
Eric Haÿ France 32 1.7k 0.8× 755 1.2× 578 1.0× 411 0.9× 357 1.0× 66 3.0k
Tatsuya Furuichi Japan 23 2.1k 1.0× 695 1.1× 676 1.2× 180 0.4× 282 0.8× 40 3.2k
Ling Qin United States 39 2.1k 1.0× 1.1k 1.7× 1.4k 2.4× 338 0.8× 601 1.7× 131 4.5k
Andrea Del Fattore Italy 30 2.2k 1.1× 362 0.6× 970 1.7× 350 0.8× 396 1.1× 74 3.7k
Guiqian Chen China 18 1.9k 0.9× 535 0.8× 463 0.8× 608 1.4× 404 1.1× 39 3.4k

Countries citing papers authored by Anja Nohe

Since Specialization
Citations

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

Fields of papers citing papers by Anja Nohe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anja Nohe

This figure shows the co-authorship network connecting the top 25 collaborators of Anja Nohe. A scholar is included among the top collaborators of Anja Nohe 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 Anja Nohe. Anja Nohe 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.
Halloran, Daniel, et al.. (2022). Age-Related Low Bone Mineral Density in C57BL/6 Mice Is Reflective of Aberrant Bone Morphogenetic Protein-2 Signaling Observed in Human Patients Diagnosed with Osteoporosis. International Journal of Molecular Sciences. 23(19). 11205–11205. 3 indexed citations
2.
Halloran, Daniel, et al.. (2022). Differentiation of Cells Isolated from Human Femoral Heads into Functional Osteoclasts. Journal of Developmental Biology. 10(1). 6–6. 4 indexed citations
3.
Duncan, Randall L., et al.. (2018). Synthetic Peptide CK2.3 Enhances Bone Mineral Density in Senile Mice. PubMed. 6(2). 8 indexed citations
4.
Akkiraju, Hemanth, et al.. (2017). CK2.1, a bone morphogenetic protein receptor type Ia mimetic peptide, repairs cartilage in mice with destabilized medial meniscus. Stem Cell Research & Therapy. 8(1). 82–82. 20 indexed citations
5.
Akkiraju, Hemanth, et al.. (2016). CK2.1, a novel peptide, induces articular cartilage formation in vivo. Journal of Orthopaedic Research®. 35(4). 876–885. 25 indexed citations
6.
Akkiraju, Hemanth, et al.. (2016). Use of Second Harmonic Imaging and Fourier Transformation to Analyze Cartilage Repair in Mice Injected with a Novel Peptide CK2.1. Biophysical Journal. 110(3). 166a–166a. 2 indexed citations
7.
Akkiraju, Hemanth, et al.. (2015). An Improved Immunostaining and Imaging Methodology to Determine Cell and Protein Distributions within the Bone Environment. Journal of Histochemistry & Cytochemistry. 64(3). 168–178. 9 indexed citations
8.
Akkiraju, Hemanth, et al.. (2014). Synthesis and Characterization of L-Lysine Conjugated Silver Nanoparticles Smaller Than 10 nM. Advanced Science Engineering and Medicine. 6(9). 942–947. 8 indexed citations
9.
Schaefer, Rachel, et al.. (2013). 1, 25 Dihydroxyvitamin D3 Uptake is Localized at Caveolae and Requires Caveolar Function. Journal of Biomedical Nanotechnology. 9(10). 1707–1715. 5 indexed citations
10.
Bragdon, Beth, et al.. (2012). Caveolae regulate smad signaling as verified by novel imaging and system biology approaches. Journal of Cellular Physiology. 228(5). 1060–1069. 11 indexed citations
11.
Schaefer, Rachel, et al.. (2012). Design of 1,25 Dihydroxyvitamin D3 Coupled Quantum Dots, a Novel Imaging Tool. Journal of Nanoscience and Nanotechnology. 12(3). 2185–2191. 11 indexed citations
12.
Sikes, Robert A., et al.. (2012). Differential effects of vitamin D treatment on inflammatory and non-inflammatory breast cancer cell lines. Clinical & Experimental Metastasis. 29(8). 971–979. 9 indexed citations
13.
Bragdon, Beth, et al.. (2011). Bone morphogenetic protein receptor type Ia localization causes increased BMP2 signaling in mice exhibiting increased peak bone mass phenotype. Journal of Cellular Physiology. 227(7). 2870–2879. 12 indexed citations
14.
Bragdon, Beth, Oleksandra Moseychuk, Daniel King, et al.. (2010). Casein Kinase 2 β-Subunit Is a Regulator of Bone Morphogenetic Protein 2 Signaling. Biophysical Journal. 99(3). 897–904. 55 indexed citations
15.
Bragdon, Beth, et al.. (2010). Bone Morphogenetic Proteins: A critical review. Cellular Signalling. 23(4). 609–620. 533 indexed citations breakdown →
16.
Bragdon, Beth, et al.. (2009). FRET Reveals Novel Protein-Receptor Interaction of Bone Morphogenetic Proteins Receptors and Adaptor Protein 2 at the Cell Surface. Biophysical Journal. 97(5). 1428–1435. 26 indexed citations
17.
Bragdon, Beth, et al.. (2008). Molecular basis of the potential of vitamin D to prevent cancer. Current Medical Research and Opinion. 24(1). 139–149. 119 indexed citations
18.
Nohe, Anja & Nils O. Petersen. (2004). Analyzing protein–protein interactions in cell membranes. BioEssays. 26(2). 196–203. 10 indexed citations
19.
Nohe, Anja, et al.. (2003). Caveolin-1 isoform reorganization studied by image correlation spectroscopy. Faraday Discussions. 126. 185–185. 23 indexed citations
20.
Nohe, Anja, Sylke Haßel, Marcelo Ehrlich, et al.. (2002). The Mode of Bone Morphogenetic Protein (BMP) Receptor Oligomerization Determines Different BMP-2 Signaling Pathways. Journal of Biological Chemistry. 277(7). 5330–5338. 467 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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