Anupam Sah

38 total papers · 958 total citations
18 papers, 657 citations indexed

About

Anupam Sah is a scholar working on Cellular and Molecular Neuroscience, Neurology and Behavioral Neuroscience. According to data from OpenAlex, Anupam Sah has authored 18 papers receiving a total of 657 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cellular and Molecular Neuroscience, 8 papers in Neurology and 6 papers in Behavioral Neuroscience. Recurrent topics in Anupam Sah's work include Neuroscience and Neuropharmacology Research (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers) and Stress Responses and Cortisol (6 papers). Anupam Sah is often cited by papers focused on Neuroscience and Neuropharmacology Research (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers) and Stress Responses and Cortisol (6 papers). Anupam Sah collaborates with scholars based in Austria, Germany and United States. Anupam Sah's co-authors include Nicolas Singewald, Stefano Gaburro, Simone B. Sartori, Rainer Landgraf, Claudia Schmuckermair, Maria Kharitonova, Hans‐Christian Pape, Ludwig Aigner, Fabio Morellini and Tina B. Lonsdorf and has published in prestigious journals such as Proceedings of the National Academy of Sciences, International Journal of Molecular Sciences and Pharmacology & Therapeutics.

In The Last Decade

Anupam Sah

18 papers receiving 652 citations

Author Peers

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

Author						Papers	Cites
Anupam Sah	301	238	167	166	123	18	657
Claudia Schmuckermair	317 1.1×	253 1.1×	194 1.2×	184 1.1×	84 0.7×	15	714
Gürsel Çalışkan	368 1.2×	222 0.9×	193 1.2×	184 1.1×	73 0.6×	31	688
Reto Bisaz	246 0.8×	187 0.8×	171 1.0×	154 0.9×	69 0.6×	13	587
Francisco García‐Oscos	243 0.8×	247 1.0×	156 0.9×	93 0.6×	135 1.1×	20	658
Abha K. Rajbhandari	331 1.1×	175 0.7×	181 1.1×	153 0.9×	137 1.1×	21	718
Victoria Alexander	282 0.9×	287 1.2×	115 0.7×	113 0.7×	74 0.6×	16	587
Stephanie M. Perez	343 1.1×	206 0.9×	175 1.0×	92 0.6×	59 0.5×	26	688
Gustavo Morrone Parfitt	314 1.0×	196 0.8×	219 1.3×	104 0.6×	72 0.6×	24	668
Zheng-Yi Luo	280 0.9×	162 0.7×	253 1.5×	126 0.8×	63 0.5×	18	668
Yiu Chung Tse	252 0.8×	106 0.4×	168 1.0×	176 1.1×	142 1.2×	20	626

Countries citing papers authored by Anupam Sah

Since Specialization

Citations

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

Fields of papers citing papers by Anupam Sah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anupam Sah

This figure shows the co-authorship network connecting the top 25 collaborators of Anupam Sah. A scholar is included among the top collaborators of Anupam Sah 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 Anupam Sah. Anupam Sah 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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