Natalie Di Bartolo

15 total papers · 628 total citations
8 papers, 477 citations indexed

About

Natalie Di Bartolo is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Spectroscopy. According to data from OpenAlex, Natalie Di Bartolo has authored 8 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Spectroscopy. Recurrent topics in Natalie Di Bartolo's work include Lipid Membrane Structure and Behavior (3 papers), Photosynthetic Processes and Mechanisms (3 papers) and Photoreceptor and optogenetics research (3 papers). Natalie Di Bartolo is often cited by papers focused on Lipid Membrane Structure and Behavior (3 papers), Photosynthetic Processes and Mechanisms (3 papers) and Photoreceptor and optogenetics research (3 papers). Natalie Di Bartolo collaborates with scholars based in United Kingdom, Switzerland and Australia. Natalie Di Bartolo's co-authors include Paula J. Booth, Nelson P. Barrera, Carol V. Robinson, Stephen J. Tucker, Sheila C. Wang, Argyris Politis, Vassiliy N. Bavro, Paul Curnow, Kathleen M. Moreton and Michael R. Jones and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Natalie Di Bartolo

7 papers receiving 475 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Natalie Di Bartolo	334	295	56	36	35	8	477
Mark T. Agasid	300 0.9×	218 0.7×	36 0.6×	32 0.9×	45 1.3×	12	446
Sven Brüschweiler	391 1.2×	185 0.6×	97 1.7×	23 0.6×	16 0.5×	16	528
James E. Keener	306 0.9×	235 0.8×	16 0.3×	38 1.1×	34 1.0×	15	486
David T. Kaleta	305 0.9×	334 1.1×	32 0.6×	9 0.3×	22 0.6×	10	511
Mengxuan Jia	398 1.2×	130 0.4×	53 0.9×	20 0.6×	22 0.6×	10	529
Megan Murray Gessel	314 0.9×	203 0.7×	27 0.5×	24 0.7×	50 1.4×	9	513
Dhanashri Bagal	309 0.9×	370 1.3×	38 0.7×	7 0.2×	37 1.1×	13	520
Argyris Politis	401 1.2×	226 0.8×	70 1.3×	20 0.6×	7 0.2×	10	543
T. Chaudhary	217 0.6×	304 1.0×	20 0.4×	42 1.2×	93 2.7×	7	521
Denis Morsa	149 0.4×	384 1.3×	64 1.1×	28 0.8×	60 1.7×	18	513

Countries citing papers authored by Natalie Di Bartolo

Since Specialization

Citations

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

Fields of papers citing papers by Natalie Di Bartolo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalie Di Bartolo. 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 Natalie Di Bartolo. The network helps show where Natalie Di Bartolo may publish in the future.

Co-authorship network of co-authors of Natalie Di Bartolo

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

All Works

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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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