Daniel Geiszler

2.0k total citations
9 papers, 331 citations indexed

About

Daniel Geiszler is a scholar working on Spectroscopy, Molecular Biology and Cell Biology. According to data from OpenAlex, Daniel Geiszler has authored 9 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Spectroscopy, 7 papers in Molecular Biology and 3 papers in Cell Biology. Recurrent topics in Daniel Geiszler's work include Advanced Proteomics Techniques and Applications (8 papers), Mass Spectrometry Techniques and Applications (4 papers) and Biotin and Related Studies (3 papers). Daniel Geiszler is often cited by papers focused on Advanced Proteomics Techniques and Applications (8 papers), Mass Spectrometry Techniques and Applications (4 papers) and Biotin and Related Studies (3 papers). Daniel Geiszler collaborates with scholars based in United States and Türkiye. Daniel Geiszler's co-authors include Alexey I. Nesvizhskii, Fengchao Yu, Dmitry M. Avtonomov, Andy T. Kong, Guo Ci Teo, Sarah E. Haynes, Daniel A. Polasky, Felipe da Veiga Leprevost, Kai Li and Keriann M. Backus and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and Analytical Chemistry.

In The Last Decade

Daniel Geiszler

7 papers receiving 328 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Geiszler United States	7	265	160	51	40	29	9	331
Run-Qian Fang China	4	306 1.2×	118 0.7×	42 0.8×	23 0.6×	61 2.1×	7	419
Rodrigo Vargas Eguez United States	8	292 1.1×	170 1.1×	26 0.5×	27 0.7×	17 0.6×	9	399
Christopher Ashwood United States	11	322 1.2×	123 0.8×	95 1.9×	36 0.9×	46 1.6×	15	393
Anna A. Lobas Russia	14	405 1.5×	340 2.1×	38 0.7×	53 1.3×	16 0.6×	36	541
Zhen-Lin Chen China	5	287 1.1×	106 0.7×	21 0.4×	17 0.4×	55 1.9×	6	385
Yanlong Ji Germany	10	277 1.0×	148 0.9×	29 0.6×	82 2.0×	31 1.1×	14	410
Samuel L. Bader United States	9	272 1.0×	138 0.9×	25 0.5×	39 1.0×	9 0.3×	10	363
Saad Quader United States	2	307 1.2×	45 0.3×	27 0.5×	53 1.3×	31 1.1×	3	364
Wai-Kok Choong Taiwan	9	295 1.1×	206 1.3×	12 0.2×	21 0.5×	26 0.9×	19	387

Countries citing papers authored by Daniel Geiszler

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Geiszler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Geiszler

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

All Works

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9 of 9 papers shown

Geiszler, Daniel, et al.. (2025). Proximity Labeling and SILAC-Based Proteomic Approach Identifies Proteins at the Interface of Homotypic and Heterotypic Cancer Cell Interactions. Molecular & Cellular Proteomics. 24(6). 100986–100986.

Geiszler, Daniel, Daniel A. Polasky, Fengchao Yu, & Alexey I. Nesvizhskii. (2023). Detecting diagnostic features in MS/MS spectra of post-translationally modified peptides. Nature Communications. 14(1). 4132–4132. 17 indexed citations

Polasky, Daniel A., Daniel Geiszler, Fengchao Yu, et al.. (2023). MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics. Molecular & Cellular Proteomics. 22(5). 100538–100538. 18 indexed citations

Polasky, Daniel A., Tianyang Yan, Daniel Geiszler, et al.. (2023). Solid-Phase Compatible Silane-Based Cleavable Linker Enables Custom Isobaric Quantitative Chemoproteomics. Journal of the American Chemical Society. 145(39). 21303–21318. 9 indexed citations

Polasky, Daniel A., Daniel Geiszler, Fengchao Yu, & Alexey I. Nesvizhskii. (2022). Multiattribute Glycan Identification and FDR Control for Glycoproteomics. Molecular & Cellular Proteomics. 21(3). 100205–100205. 24 indexed citations

Yan, Tianyang, Daniel Geiszler, Daniel A. Polasky, et al.. (2022). Enhancing Cysteine Chemoproteomic Coverage through Systematic Assessment of Click Chemistry Product Fragmentation. Analytical Chemistry. 94(9). 3800–3810. 20 indexed citations

Polasky, Daniel A., Daniel Geiszler, Fengchao Yu, & Alexey I. Nesvizhskii. (2021). Multi-attribute Glycan Identification and FDR Control for Glycoproteomics. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

Yu, Fengchao, Guo Ci Teo, Andy T. Kong, et al.. (2020). Identification of modified peptides using localization-aware open search. Nature Communications. 11(1). 4065–4065. 161 indexed citations

Geiszler, Daniel, Andy T. Kong, Dmitry M. Avtonomov, et al.. (2020). PTM-Shepherd: Analysis and Summarization of Post-Translational and Chemical Modifications From Open Search Results. Molecular & Cellular Proteomics. 20. 100018–100018. 81 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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