Ram Rup Sarkar

2.3k total citations
65 papers, 1.7k citations indexed

About

Ram Rup Sarkar is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology and Genetics. According to data from OpenAlex, Ram Rup Sarkar has authored 65 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Public Health, Environmental and Occupational Health, 23 papers in Molecular Biology and 15 papers in Genetics. Recurrent topics in Ram Rup Sarkar's work include Mathematical and Theoretical Epidemiology and Ecology Models (16 papers), Evolution and Genetic Dynamics (13 papers) and Trypanosoma species research and implications (9 papers). Ram Rup Sarkar is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (16 papers), Evolution and Genetic Dynamics (13 papers) and Trypanosoma species research and implications (9 papers). Ram Rup Sarkar collaborates with scholars based in India, Germany and United States. Ram Rup Sarkar's co-authors include Sandip Mandal, Sandip Banerjee, Somdatta Sinha, Joydev Chattopadhyay, Saikat Chowdhury, Abhishek Subramanian, Samares Pal, Joydev Chattopadhyay, Horst Malchow and Shyam Sundar and has published in prestigious journals such as PLoS ONE, Scientific Reports and Physical Chemistry Chemical Physics.

In The Last Decade

Ram Rup Sarkar

63 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ram Rup Sarkar India 21 1.1k 447 428 367 260 65 1.7k
Patrick De Leenheer United States 24 719 0.7× 333 0.7× 498 1.2× 517 1.4× 219 0.8× 66 2.0k
Sanling Yuan China 32 2.3k 2.1× 1.4k 3.0× 1.4k 3.2× 116 0.3× 284 1.1× 139 2.9k
V. Sree Hari Rao India 16 678 0.6× 297 0.7× 566 1.3× 217 0.6× 206 0.8× 46 1.2k
Nandadulal Bairagi India 22 1.2k 1.0× 466 1.0× 870 2.0× 82 0.2× 194 0.7× 97 1.5k
Sergei S. Pilyugin United States 22 497 0.5× 274 0.6× 406 0.9× 254 0.7× 178 0.7× 57 1.3k
Samrat Chatterjee India 16 330 0.3× 115 0.3× 247 0.6× 171 0.5× 81 0.3× 88 793
Sophia R.‐J. Jang United States 18 741 0.7× 275 0.6× 530 1.2× 134 0.4× 161 0.6× 104 1.2k
Subhas Khajanchi India 32 1.7k 1.5× 2.0k 4.5× 827 1.9× 348 0.9× 145 0.6× 75 3.0k
Lionel Roques France 22 785 0.7× 392 0.9× 466 1.1× 61 0.2× 135 0.5× 68 1.5k
Bingtuan Li United States 23 1.7k 1.5× 691 1.5× 1.1k 2.5× 84 0.2× 310 1.2× 57 2.0k

Countries citing papers authored by Ram Rup Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Ram Rup Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ram Rup Sarkar. 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 Ram Rup Sarkar. The network helps show where Ram Rup Sarkar may publish in the future.

Co-authorship network of co-authors of Ram Rup Sarkar

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

All Works

20 of 20 papers shown
1.
Sarkar, Ram Rup, et al.. (2024). Dynamic cellular responses to gravitational forces: Exploring the impact on white blood cell(s). Biomicrofluidics. 18(5). 54112–54112.
2.
Sarkar, Ram Rup, et al.. (2024). Metabolic reprogramming and signalling cross-talks in tumour–immune interaction: a system-level exploration. Royal Society Open Science. 11(3). 231574–231574. 2 indexed citations
3.
Sarkar, Ram Rup, et al.. (2024). Differential cellular communication in tumor immune microenvironment during early and advanced stages of lung adenocarcinoma. Molecular Genetics and Genomics. 299(1). 100–100. 1 indexed citations
4.
Cederquist, G., Kathryn R. Tringale, Carla Hajj, et al.. (2023). Salvage Radiotherapy as a Bridge for Relapsed Secondary CNS Lymphoma. International Journal of Radiation Oncology*Biology*Physics. 117(2). e459–e459. 1 indexed citations
5.
Sarkar, Ram Rup, et al.. (2022). Identification of potential microRNAs regulating metabolic plasticity and cellular phenotypes in glioblastoma. Molecular Genetics and Genomics. 298(1). 161–181. 1 indexed citations
6.
Sarkar, Ram Rup, et al.. (2022). Emerging landscape of molecular interaction networks: Opportunities, challenges and prospects. Journal of Biosciences. 47(2). 23 indexed citations
7.
8.
Sarkar, Ram Rup, et al.. (2020). Essential gene prediction using limited gene essentiality information–An integrative semi-supervised machine learning strategy. PLoS ONE. 15(11). e0242943–e0242943. 8 indexed citations
9.
Sarkar, Ram Rup, et al.. (2020). Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI‐based approach. Chemical Biology & Drug Design. 96(3). 1005–1019. 2 indexed citations
10.
11.
Sarkar, Ram Rup, et al.. (2019). Effect of copper contamination on zooplankton epidemics. Journal of Theoretical Biology. 469. 61–74. 8 indexed citations
12.
Chowdhury, Saikat, et al.. (2019). Molecular basis of drug resistance in smoothened receptor: An in silico study of protein resistivity and specificity. Proteins Structure Function and Bioinformatics. 88(3). 514–526. 7 indexed citations
13.
Sarkar, Ram Rup, et al.. (2018). Exploring immuno-regulatory mechanisms in the tumor microenvironment: Model and design of protocols for cancer remission. PLoS ONE. 13(9). e0203030–e0203030. 4 indexed citations
14.
Chowdhury, Saikat, et al.. (2018). BIOPYDB: A Dynamic Human Cell Specific Biochemical Pathway Database with Advanced Computational Analyses Platform. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 15(3). 2 indexed citations
15.
Subramanian, Abhishek & Ram Rup Sarkar. (2018). Evolutionary Perspectives of Genotype–Phenotype Factors in Leishmania Metabolism. Journal of Molecular Evolution. 86(7). 443–456.
16.
Sarkar, Ram Rup, et al.. (2018). Machine learning prediction of interaction energies in rigid water clusters. Physical Chemistry Chemical Physics. 20(35). 22987–22996. 14 indexed citations
17.
Chowdhury, Saikat, et al.. (2017). Deciphering structural stability and binding mechanisms of potential antagonists with smoothened protein. Journal of Biomolecular Structure and Dynamics. 36(11). 2917–2937. 6 indexed citations
18.
Subramanian, Abhishek, et al.. (2017). An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features. Molecular BioSystems. 13(8). 1584–1596. 33 indexed citations
19.
Subramanian, Abhishek, et al.. (2017). Exploring the role of GS–GOGAT cycle in microcystin synthesis and regulation – a model based analysis. Molecular BioSystems. 13(12). 2603–2614. 6 indexed citations
20.
Chattopadhyay, Joydev, et al.. (2001). Uniqueness of limit cycles in a harvested predator prey system with Holling type III functional response. Nonlinear studies. 8(2). 261–282. 4 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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