Sanjib Mukherjee

71 total papers · 1.1k total citations
44 papers, 882 citations indexed

About

Sanjib Mukherjee is a scholar working on Molecular Biology, Neurology and Endocrine and Autonomic Systems. According to data from OpenAlex, Sanjib Mukherjee has authored 44 papers receiving a total of 882 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 6 papers in Neurology and 5 papers in Endocrine and Autonomic Systems. Recurrent topics in Sanjib Mukherjee's work include Protein Structure and Dynamics (8 papers), Protein Interaction Studies and Fluorescence Analysis (7 papers) and DNA and Nucleic Acid Chemistry (7 papers). Sanjib Mukherjee is often cited by papers focused on Protein Structure and Dynamics (8 papers), Protein Interaction Studies and Fluorescence Analysis (7 papers) and DNA and Nucleic Acid Chemistry (7 papers). Sanjib Mukherjee collaborates with scholars based in United States, Germany and India. Sanjib Mukherjee's co-authors include Pramit K. Chowdhury, Lee A. Shapiro, Jayanta Kundu, Saikat Biswas, Steven M. Simasko, Roland Winter, Gabriel Maisonnave Arisi, Rosario Oliva, Maira Licia Foresti and Suzanne Zeitouni and has published in prestigious journals such as Chemical Reviews, Journal of the American Chemical Society and PLoS ONE.

In The Last Decade

Sanjib Mukherjee

41 papers receiving 876 citations

Author Peers

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

Author						Papers	Cites
Sanjib Mukherjee	426	123	108	103	92	44	882
Roger G. Biringer	443 1.0×	61 0.5×	51 0.5×	65 0.6×	47 0.5×	26	825
Ting Li	338 0.8×	58 0.5×	57 0.5×	72 0.7×	61 0.7×	58	900
Prem Prakash Tripathi	495 1.2×	119 1.0×	44 0.4×	148 1.4×	67 0.7×	33	982
Rafael Fernández-Montesinos	246 0.6×	148 1.2×	67 0.6×	164 1.6×	113 1.2×	19	868
Yoshinori Yamakawa	227 0.5×	97 0.8×	68 0.6×	146 1.4×	48 0.5×	57	831
Alexander Shirokov	252 0.6×	104 0.8×	89 0.8×	249 2.4×	65 0.7×	72	952
Randall B. Murphy	634 1.5×	84 0.7×	39 0.4×	438 4.3×	47 0.5×	48	1.0k
Hiroo Ikehira	243 0.6×	53 0.4×	52 0.5×	172 1.7×	58 0.6×	38	1.0k
Raymond E. Hulse	473 1.1×	35 0.3×	80 0.7×	217 2.1×	151 1.6×	16	935
María José Benítez	433 1.0×	69 0.6×	39 0.4×	181 1.8×	57 0.6×	39	726

Countries citing papers authored by Sanjib Mukherjee

Since Specialization

Citations

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

Fields of papers citing papers by Sanjib Mukherjee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sanjib Mukherjee

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