Katheryn M. Sanchez

896 total citations
7 papers, 685 citations indexed

About

Katheryn M. Sanchez is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Microbiology. According to data from OpenAlex, Katheryn M. Sanchez has authored 7 papers receiving a total of 685 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Microbiology. Recurrent topics in Katheryn M. Sanchez's work include Lipid Membrane Structure and Behavior (5 papers), Protein Structure and Dynamics (4 papers) and Photoreceptor and optogenetics research (2 papers). Katheryn M. Sanchez is often cited by papers focused on Lipid Membrane Structure and Behavior (5 papers), Protein Structure and Dynamics (4 papers) and Photoreceptor and optogenetics research (2 papers). Katheryn M. Sanchez collaborates with scholars based in United States. Katheryn M. Sanchez's co-authors include Judy E. Kim, Yuping Lai, Richard L. Gallo, Victor Nizet, Kenshi Yamasaki, Anna L. Cogen, Michaël Otto, Robert A. Dorschner, Daniel T. MacLeod and Justin W. Torpey and has published in prestigious journals such as PLoS ONE, The Journal of Physical Chemistry B and Biochemistry.

In The Last Decade

Katheryn M. Sanchez

7 papers receiving 670 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katheryn M. Sanchez United States 7 333 255 132 121 74 7 685
Bernhard Paetzold Spain 12 425 1.3× 454 1.8× 61 0.5× 87 0.7× 48 0.6× 16 1.0k
Stacey L. Kolar United States 12 357 1.1× 62 0.2× 99 0.8× 283 2.3× 14 0.2× 14 635
Tejinder Kaur India 11 209 0.6× 72 0.3× 21 0.2× 120 1.0× 12 0.2× 42 634
Shuai Nie Australia 17 303 0.9× 67 0.3× 13 0.1× 28 0.2× 111 1.5× 51 801
Heather L. Rocchetta Canada 8 449 1.3× 58 0.2× 64 0.5× 26 0.2× 6 0.1× 11 725
Renu Garg India 14 197 0.6× 9 0.0× 22 0.2× 98 0.8× 14 0.2× 29 611
Yasuko Doi Japan 10 862 2.6× 28 0.1× 21 0.2× 420 3.5× 21 0.3× 15 1.7k
Yoshihisa Iwamoto Japan 15 165 0.5× 34 0.1× 19 0.1× 75 0.6× 8 0.1× 50 530
Elżbieta Kamysz Poland 20 559 1.7× 8 0.0× 584 4.4× 80 0.7× 7 0.1× 61 1.0k
C. Shipman United States 11 207 0.6× 47 0.2× 13 0.1× 161 1.3× 5 0.1× 19 691

Countries citing papers authored by Katheryn M. Sanchez

Since Specialization
Citations

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

Fields of papers citing papers by Katheryn M. Sanchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Katheryn M. Sanchez. 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 Katheryn M. Sanchez. The network helps show where Katheryn M. Sanchez may publish in the future.

Co-authorship network of co-authors of Katheryn M. Sanchez

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

All Works

7 of 7 papers shown
1.
Sanchez, Katheryn M., et al.. (2011). Tryptophan-Lipid Interactions in Membrane Protein Folding Probed by Ultraviolet Resonance Raman and Fluorescence Spectroscopy. Biophysical Journal. 100(9). 2121–2130. 77 indexed citations
2.
Cogen, Anna L., Kenshi Yamasaki, Jun Muto, et al.. (2010). Staphylococcus epidermidis Antimicrobial δ-Toxin (Phenol-Soluble Modulin-γ) Cooperates with Host Antimicrobial Peptides to Kill Group A Streptococcus. PLoS ONE. 5(1). e8557–e8557. 172 indexed citations
3.
Cogen, Anna L., Kenshi Yamasaki, Katheryn M. Sanchez, et al.. (2009). Selective Antimicrobial Action Is Provided by Phenol-Soluble Modulins Derived from Staphylococcus epidermidis, a Normal Resident of the Skin. Journal of Investigative Dermatology. 130(1). 192–200. 316 indexed citations
4.
Shafaat, Hannah S., et al.. (2009). Ultraviolet resonance Raman spectroscopy of a β‐sheet peptide: a model for membrane protein folding. Journal of Raman Spectroscopy. 40(8). 1060–1064. 22 indexed citations
5.
Sanchez, Katheryn M., et al.. (2008). Ultraviolet Resonance Raman Spectroscopy of Folded and Unfolded States of an Integral Membrane Protein. The Journal of Physical Chemistry B. 112(31). 9507–9511. 33 indexed citations
6.
Sanchez, Katheryn M., Diana E. Schlamadinger, Jonathan E. Gable, & Judy E. Kim. (2008). Förster Resonance Energy Transfer and Conformational Stability of Proteins. An Advanced Biophysical Module for Physical Chemistry Students. Journal of Chemical Education. 85(9). 1253–1253. 25 indexed citations
7.
Sanchez, Katheryn M., Jonathan E. Gable, Diana E. Schlamadinger, & Judy E. Kim. (2008). Effects of Tryptophan Microenvironment, Soluble Domain, and Vesicle Size on the Thermodynamics of Membrane Protein Folding: Lessons from the Transmembrane Protein OmpA. Biochemistry. 47(48). 12844–12852. 40 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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2026