Danielle M. Osborne

21 total papers · 445 total citations
14 papers, 369 citations indexed

About

Danielle M. Osborne is a scholar working on Behavioral Neuroscience, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Danielle M. Osborne has authored 14 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Behavioral Neuroscience, 5 papers in Genetics and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Danielle M. Osborne's work include Stress Responses and Cortisol (6 papers), Estrogen and related hormone effects (4 papers) and Neuroscience and Neuropharmacology Research (4 papers). Danielle M. Osborne is often cited by papers focused on Stress Responses and Cortisol (6 papers), Estrogen and related hormone effects (4 papers) and Neuroscience and Neuropharmacology Research (4 papers). Danielle M. Osborne collaborates with scholars based in United States. Danielle M. Osborne's co-authors include Cheryl A. Frye, Kassandra L. Edinger, Ewan C. McNay, Jiah Pearson-Leary, Carolyn J. Koonce, Alicia A. Walf, Detlev Boison, Kiran S. Toti, Antonella Ciancetta and Kenneth A. Jacobson and has published in prestigious journals such as Journal of Medicinal Chemistry, Diabetologia and Nutrients.

In The Last Decade

Danielle M. Osborne

14 papers receiving 365 citations

Author Peers

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

Author						Papers	Cites
Danielle M. Osborne	136	79	66	66	65	14	369
Erin K. Murphy	105 0.8×	96 1.2×	87 1.3×	59 0.9×	89 1.4×	14	435
Melinda G. Arnett	166 1.2×	53 0.7×	94 1.4×	66 1.0×	33 0.5×	12	394
Na Qu	90 0.7×	67 0.8×	85 1.3×	66 1.0×	78 1.2×	14	390
Jennifer R. Rainville	157 1.2×	42 0.5×	81 1.2×	57 0.9×	78 1.2×	17	441
Gianna Ragagnin	124 0.9×	54 0.7×	38 0.6×	99 1.5×	45 0.7×	9	387
Axel Mathieu	80 0.6×	48 0.6×	80 1.2×	48 0.7×	33 0.5×	18	396
Ethan H. Beckley	118 0.9×	68 0.9×	81 1.2×	151 2.3×	34 0.5×	13	386
Marjolein Gerrits	230 1.7×	55 0.7×	29 0.4×	71 1.1×	48 0.7×	10	412
Samantha J. Owens	89 0.7×	59 0.7×	83 1.3×	88 1.3×	39 0.6×	9	345
Dulce A. Velázquez-Zamora	69 0.5×	89 1.1×	61 0.9×	131 2.0×	85 1.3×	14	342

Countries citing papers authored by Danielle M. Osborne

Since Specialization

Citations

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

Fields of papers citing papers by Danielle M. Osborne

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danielle M. Osborne

This figure shows the co-authorship network connecting the top 25 collaborators of Danielle M. Osborne. A scholar is included among the top collaborators of Danielle M. Osborne 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 Danielle M. Osborne. Danielle M. Osborne 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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