Daniela Schlatzer

2.5k total citations
42 papers, 1.3k citations indexed

About

Daniela Schlatzer is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Daniela Schlatzer has authored 42 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 8 papers in Oncology and 8 papers in Immunology. Recurrent topics in Daniela Schlatzer's work include HIV Research and Treatment (6 papers), Advanced Proteomics Techniques and Applications (6 papers) and Ubiquitin and proteasome pathways (4 papers). Daniela Schlatzer is often cited by papers focused on HIV Research and Treatment (6 papers), Advanced Proteomics Techniques and Applications (6 papers) and Ubiquitin and proteasome pathways (4 papers). Daniela Schlatzer collaborates with scholars based in United States, United Kingdom and Austria. Daniela Schlatzer's co-authors include Mary B. Moyer, Arthur Moseley, Kevin Blackburn, Richard C. Boucher, Lawrence E. Ostrowski, Mark R. Chance, Linda Spremulli, William Burkhart, Emine C. Koc and Mehmet Koyutürk and has published in prestigious journals such as Cell, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Daniela Schlatzer

40 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniela Schlatzer United States 17 854 320 186 118 110 42 1.3k
Lisa Berglund Sweden 13 927 1.1× 97 0.3× 127 0.7× 93 0.8× 180 1.6× 22 1.5k
Peter Blattmann Switzerland 14 550 0.6× 140 0.4× 81 0.4× 259 2.2× 123 1.1× 25 1.0k
Jörg P. Müller Germany 24 1.1k 1.3× 531 1.7× 61 0.3× 233 2.0× 67 0.6× 61 1.7k
Sander H. Diks Netherlands 21 810 0.9× 92 0.3× 100 0.5× 166 1.4× 134 1.2× 46 1.4k
Alessia David United Kingdom 24 1.2k 1.4× 601 1.9× 105 0.6× 143 1.2× 27 0.2× 50 2.1k
Philippe Gonzalo France 17 661 0.8× 120 0.4× 94 0.5× 115 1.0× 31 0.3× 37 943
Yuichiro Takagi United States 25 1.5k 1.8× 136 0.4× 106 0.6× 81 0.7× 26 0.2× 63 1.9k
K. Olek Germany 25 1.1k 1.3× 282 0.9× 84 0.5× 86 0.7× 66 0.6× 103 2.2k
Yifat Merbl Israel 20 958 1.1× 118 0.4× 194 1.0× 429 3.6× 57 0.5× 42 1.5k
Yoichi Ishida Japan 21 690 0.8× 101 0.3× 142 0.8× 154 1.3× 36 0.3× 68 1.5k

Countries citing papers authored by Daniela Schlatzer

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Schlatzer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela Schlatzer

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela Schlatzer. A scholar is included among the top collaborators of Daniela Schlatzer 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 Daniela Schlatzer. Daniela Schlatzer 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.
Schlatzer, Daniela, et al.. (2024). Making proteomics accessible: Rokai Xplorer for interactive analysis of phospho-proteomic data. Bioinformatics Advances. 4(1). vbae077–vbae077. 1 indexed citations
2.
Hinchliffe, Philip, Catherine L. Tooke, Christopher R. Bethel, et al.. (2022). Penicillanic Acid Sulfones Inactivate the Extended-Spectrum β-Lactamase CTX-M-15 through Formation of a Serine-Lysine Cross-Link: an Alternative Mechanism of β-Lactamase Inhibition. mBio. 13(3). e0179321–e0179321. 9 indexed citations
3.
McColl, Karen, Fernanda O. Lemos, Martijn Kerkhofs, et al.. (2022). A non-canonical role for pyruvate kinase M2 as a functional modulator of Ca2+ signalling through IP3 receptors. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1869(4). 119206–119206. 9 indexed citations
4.
Tamargo, Javier, Kenneth E. Sherman, Rafick‐Pierre Sékaly, et al.. (2022). Cocaethylene, simultaneous alcohol and cocaine use, and liver fibrosis in people living with and without HIV. Drug and Alcohol Dependence. 232. 109273–109273. 8 indexed citations
5.
Schlatzer, Daniela, et al.. (2022). Temporal and Sex-Linked Protein Expression Dynamics in a Familial Model of Alzheimer’s Disease. Molecular & Cellular Proteomics. 21(9). 100280–100280. 11 indexed citations
6.
Ayati, Marzieh, et al.. (2021). Robust inference of kinase activity using functional networks. Nature Communications. 12(1). 1177–1177. 45 indexed citations
7.
Léonard, Daniel, Wei Huang, Sudeh Izadmehr, et al.. (2020). Selective PP2A Enhancement through Biased Heterotrimer Stabilization. Cell. 181(3). 688–701.e16. 116 indexed citations
8.
Mazhar, Sahar, Daniel Léonard, Alejandro Jiménez, et al.. (2020). Challenges and Reinterpretation of Antibody-Based Research on Phosphorylation of Tyr307 on PP2Ac. Cell Reports. 30(9). 3164–3170.e3. 16 indexed citations
9.
O’Connor, Caitlin M., Daniel Léonard, Danica Wiredja, et al.. (2019). Inactivation of PP2A by a recurrent mutation drives resistance to MEK inhibitors. Oncogene. 39(3). 703–717. 27 indexed citations
10.
Ayati, Marzieh, Danica Wiredja, Daniela Schlatzer, et al.. (2019). CoPhosK: A method for comprehensive kinase substrate annotation using co-phosphorylation analysis. PLoS Computational Biology. 15(2). e1006678–e1006678. 23 indexed citations
11.
12.
Seabra, Catarina M., Serkan Erdin, Ashok Ragavendran, et al.. (2017). A novel microduplication of ARID1B: Clinical, genetic, and proteomic findings. American Journal of Medical Genetics Part A. 173(9). 2478–2484. 5 indexed citations
13.
Schlatzer, Daniela, et al.. (2017). HIV signaling through CD4 and CCR5 activates Rho family GTPases that are required for optimal infection of primary CD4+ T cells. Retrovirology. 14(1). 4–4. 20 indexed citations
14.
15.
Liu, Guiming, Mingfang Tao, Daniela Schlatzer, et al.. (2015). Tissue Specific Dysregulated Protein Subnetworks in Type 2 Diabetic Bladder Urothelium and Detrusor Muscle. Molecular & Cellular Proteomics. 14(3). 635–645. 18 indexed citations
16.
Lundberg, Kathleen C., Yi Fritz, Andrew Johnston, et al.. (2014). Proteomics of Skin Proteins in Psoriasis: From Discovery and Verification in a Mouse Model to Confirmation in Humans. Molecular & Cellular Proteomics. 14(1). 109–119. 41 indexed citations
17.
Schlatzer, Daniela, et al.. (2011). A quantitative proteomic approach for detecting protein profiles of activated human myeloid dendritic cells. Journal of Immunological Methods. 375(1-2). 39–45. 15 indexed citations
18.
Schlatzer, Daniela, Jean‐Eudes Dazard, Moyez Dharsee, et al.. (2009). Urinary Protein Profiles in a Rat Model for Diabetic Complications. Molecular & Cellular Proteomics. 8(9). 2145–2158. 23 indexed citations
19.
Ostrowski, Lawrence E., Kevin Blackburn, Mary B. Moyer, et al.. (2002). A Proteomic Analysis of Human Cilia. Molecular & Cellular Proteomics. 1(6). 451–465. 349 indexed citations
20.
Koc, Emine C., William Burkhart, Kevin Blackburn, et al.. (2001). The Large Subunit of the Mammalian Mitochondrial Ribosome. Journal of Biological Chemistry. 276(47). 43958–43969. 214 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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