Subir K. Chanda

919 total citations · 1 hit paper
9 papers, 727 citations indexed

About

Subir K. Chanda is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Materials Chemistry. According to data from OpenAlex, Subir K. Chanda has authored 9 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Materials Chemistry. Recurrent topics in Subir K. Chanda's work include Neuroscience and Neuropharmacology Research (3 papers), Receptor Mechanisms and Signaling (3 papers) and Neurotransmitter Receptor Influence on Behavior (3 papers). Subir K. Chanda is often cited by papers focused on Neuroscience and Neuropharmacology Research (3 papers), Receptor Mechanisms and Signaling (3 papers) and Neurotransmitter Receptor Influence on Behavior (3 papers). Subir K. Chanda collaborates with scholars based in United States. Subir K. Chanda's co-authors include Shailesh P. Banerjee, Stephen J. Riggi, Virendra K. Sharma, M. George Cherian, Alexander L. Dounce, Philip L. Townes and David J. Volkman and has published in prestigious journals such as Nature, Biochemical Journal and Brain Research.

In The Last Decade

Subir K. Chanda

9 papers receiving 657 citations

Hit Papers

Development of β-adrenergic receptor subsensitivity by an... 1977 2026 1993 2009 1977 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subir K. Chanda United States 7 473 344 172 98 95 9 727
Robert J. Stawarz United States 6 410 0.9× 305 0.9× 140 0.8× 107 1.1× 69 0.7× 9 609
H Sowińska Poland 17 616 1.3× 322 0.9× 198 1.2× 106 1.1× 117 1.2× 37 874
A.R. Green United Kingdom 17 671 1.4× 372 1.1× 186 1.1× 276 2.8× 55 0.6× 26 1.0k
R. Papeschi Canada 15 427 0.9× 230 0.7× 92 0.5× 141 1.4× 46 0.5× 24 707
J Siwanowicz Poland 18 548 1.2× 278 0.8× 89 0.5× 105 1.1× 145 1.5× 42 836
Albert J. Azzaro United States 17 408 0.9× 240 0.7× 199 1.2× 102 1.0× 179 1.9× 38 920
P. Tagliamonte Italy 14 626 1.3× 270 0.8× 99 0.6× 225 2.3× 101 1.1× 19 1.1k
Laurence A. Carr United States 18 515 1.1× 341 1.0× 183 1.1× 57 0.6× 90 0.9× 34 1.0k
M Hauptmann Poland 17 449 0.9× 227 0.7× 66 0.4× 53 0.5× 102 1.1× 33 641
Freddy De Paermentier United Kingdom 13 467 1.0× 277 0.8× 150 0.9× 76 0.8× 107 1.1× 25 664

Countries citing papers authored by Subir K. Chanda

Since Specialization
Citations

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

Fields of papers citing papers by Subir K. Chanda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Subir K. Chanda. 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 Subir K. Chanda. The network helps show where Subir K. Chanda may publish in the future.

Co-authorship network of co-authors of Subir K. Chanda

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

All Works

9 of 9 papers shown
1.
Banerjee, Shailesh P., et al.. (1979). Cocaine andd-amphetamine induce changes in central ß-adrenoceptor sensitivity: Effects of acute and chronic drug treatment. Brain Research. 175(1). 119–130. 52 indexed citations
2.
Banerjee, Shailesh P., et al.. (1978). Amphetamine induces β-adrenergic receptor supersensitivity. Nature. 271(5643). 380–381. 34 indexed citations
3.
Banerjee, Shailesh P., et al.. (1977). Development of β-adrenergic receptor subsensitivity by antidepressants. Nature. 268(5619). 455–456. 583 indexed citations breakdown →
4.
Dounce, Alexander L., et al.. (1974). A simple method for the crystallization of beef liver crotonase. Biochimica et Biophysica Acta (BBA) - Protein Structure. 342(1). 81–88. 2 indexed citations
5.
Chanda, Subir K., et al.. (1973). High total histone/deoxyribonucleic acid ratios for rat liver nuclei. Biochemical Journal. 135(1). 115–123. 3 indexed citations
6.
Dounce, Alexander L., Subir K. Chanda, & Philip L. Townes. (1973). The structure of higher eukaryotic chromosomes. Journal of Theoretical Biology. 42(2). 275–285. 10 indexed citations
7.
Chanda, Subir K. & M. George Cherian. (1973). Isolation and partial characterization of a mercury-binding nonhistone protein component from rat kidney nuclei. Biochemical and Biophysical Research Communications. 50(4). 1013–1019. 25 indexed citations
8.
Chanda, Subir K. & Alexander L. Dounce. (1971). Separation of histones from normal rat liver nuclei into easily extractable and residual histone and characterization of the fractions. Archives of Biochemistry and Biophysics. 146(2). 441–448. 7 indexed citations
9.
Chanda, Subir K., et al.. (1971). Ratios of protein fractions to DNA and electrophoretic studies of histones of diploid and polyploid nuclei of rat liver. Archives of Biochemistry and Biophysics. 145(1). 211–219. 11 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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