Ranadip Pal

4.5k total citations
98 papers, 2.2k citations indexed

About

Ranadip Pal is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Ranadip Pal has authored 98 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Molecular Biology, 33 papers in Computational Theory and Mathematics and 10 papers in Artificial Intelligence. Recurrent topics in Ranadip Pal's work include Gene Regulatory Network Analysis (36 papers), Computational Drug Discovery Methods (33 papers) and Bioinformatics and Genomic Networks (22 papers). Ranadip Pal is often cited by papers focused on Gene Regulatory Network Analysis (36 papers), Computational Drug Discovery Methods (33 papers) and Bioinformatics and Genomic Networks (22 papers). Ranadip Pal collaborates with scholars based in United States, India and Türkiye. Ranadip Pal's co-authors include Aniruddha Datta, Saad Haider, E.R. Dougherty, Raziur Rahman, Michael Bittner, Edward R. Dougherty, Souparno Ghosh, Ivan Ivanov, Changzhi Li and Yiran Li and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Bioinformatics.

In The Last Decade

Ranadip Pal

92 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ranadip Pal United States 25 1.5k 509 267 170 146 98 2.2k
Dan Zhao China 30 1.8k 1.2× 417 0.8× 97 0.4× 156 0.9× 135 0.9× 134 2.9k
Chunyu Wang China 29 1.5k 1.0× 254 0.5× 167 0.6× 196 1.2× 200 1.4× 169 2.8k
Pankaj Agarwal United States 22 1.8k 1.2× 853 1.7× 205 0.8× 59 0.3× 141 1.0× 81 2.6k
Gunnar W. Klau Germany 24 1.5k 1.0× 339 0.7× 313 1.2× 63 0.4× 263 1.8× 79 2.5k
Eva Balsa‐Canto Spain 31 1.4k 0.9× 334 0.7× 193 0.7× 234 1.4× 186 1.3× 99 3.0k
Bingding Huang China 18 1.1k 0.8× 543 1.1× 48 0.2× 99 0.6× 136 0.9× 59 2.1k
Salvatore Candido United States 11 1.6k 1.1× 347 0.7× 101 0.4× 119 0.7× 187 1.3× 17 2.4k
Simon Rogers United Kingdom 34 1.7k 1.1× 231 0.5× 167 0.6× 220 1.3× 386 2.6× 104 3.3k
Byung-Jun Yoon United States 20 1.2k 0.8× 267 0.5× 52 0.2× 82 0.5× 211 1.4× 131 1.7k
Ling‐Yun Wu China 29 2.4k 1.6× 471 0.9× 154 0.6× 57 0.3× 252 1.7× 94 3.6k

Countries citing papers authored by Ranadip Pal

Since Specialization
Citations

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

Fields of papers citing papers by Ranadip Pal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ranadip Pal

This figure shows the co-authorship network connecting the top 25 collaborators of Ranadip Pal. A scholar is included among the top collaborators of Ranadip Pal 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 Ranadip Pal. Ranadip Pal 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.
Welch, Nicole, Shashi Shekhar Singh, Avinash Kumar, et al.. (2021). Integrated multiomics analysis identifies molecular landscape perturbations during hyperammonemia in skeletal muscle and myotubes. Journal of Biological Chemistry. 297(3). 101023–101023. 14 indexed citations
2.
Ghosh, Souparno, et al.. (2018). Modeling of drug diffusion in a solid tumor leading to tumor cell death. Physical review. E. 98(6). 7 indexed citations
3.
Rahman, Raziur, et al.. (2018). Investigation of model stacking for drug sensitivity prediction. BMC Bioinformatics. 19(S3). 71–71. 43 indexed citations
4.
Rahman, Raziur, et al.. (2018). Application of transfer learning for cancer drug sensitivity prediction. BMC Bioinformatics. 19(S17). 497–497. 27 indexed citations
5.
Rahman, Raziur, et al.. (2017). Heterogeneity Aware Random Forest for Drug Sensitivity Prediction. Scientific Reports. 7(1). 11347–11347. 49 indexed citations
6.
Berlow, Noah, et al.. (2017). Combination therapy design for maximizing sensitivity and minimizing toxicity. BMC Bioinformatics. 18(S4). 116–116. 14 indexed citations
7.
Rahman, Raziur & Ranadip Pal. (2016). A mathematical framework for analyzing drug combination toxicity for personalized medicine applications. 17. 13–16. 2 indexed citations
8.
Haider, Saad, Raziur Rahman, Souparno Ghosh, & Ranadip Pal. (2015). A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction. PLoS ONE. 10(12). e0144490–e0144490. 27 indexed citations
9.
Halvorson, Kyle G., Kelly L. Barton, Kristin Schroeder, et al.. (2015). A High-Throughput In Vitro Drug Screen in a Genetically Engineered Mouse Model of Diffuse Intrinsic Pontine Glioma Identifies BMS-754807 as a Promising Therapeutic Agent. PLoS ONE. 10(3). e0118926–e0118926. 49 indexed citations
10.
Berlow, Noah, Lara E. Davis, Charles Keller, & Ranadip Pal. (2014). Inference of dynamic biological networks based on responses to drug perturbations. PubMed. 2014(1). 14–14. 3 indexed citations
11.
Haider, Saad & Ranadip Pal. (2013). Integrated Analysis of Transcriptomic and Proteomic Data. Current Genomics. 14(2). 91–110. 297 indexed citations
12.
Pal, Ranadip, Yufei Huang, & Yidong Chen. (2012). Selected articles from the IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS'2011). BMC Genomics. 13(Suppl 6). S1–S1. 1 indexed citations
13.
Haider, Saad & Ranadip Pal. (2012). Boolean network inference from time series data incorporating prior biological knowledge. BMC Genomics. 13(Suppl 6). S9–S9. 18 indexed citations
14.
Pal, Ranadip & Sukalyan Bhattacharya. (2012). Transient Dynamics of Reduced-Order Models of Genetic Regulatory Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 9(4). 1230–1244. 3 indexed citations
15.
Abraham, Jinu, Corrine Ying Xuan Chua, Jason Glover, et al.. (2012). An adaptive Src–PDGFRA–Raf axis in rhabdomyosarcoma. Biochemical and Biophysical Research Communications. 426(3). 363–368. 15 indexed citations
16.
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18.
Pal, Ranadip, Ivan Ivanov, Aniruddha Datta, Michael Bittner, & E.R. Dougherty. (2005). Generating Boolean networks with a prescribed attractor structure. Computer applications in the biosciences. 21(21). 4021–4025. 112 indexed citations
19.
Pal, Ranadip, Aniruddha Datta, Albert J. Fornace, Michael Bittner, & E.R. Dougherty. (2004). Boolean relationships among genes responsive to ionizing radiation in the NCI 60 ACDS. Computer applications in the biosciences. 21(8). 1542–1549. 16 indexed citations
20.
Pal, Ranadip, Aniruddha Datta, Michael Bittner, & Edward R. Dougherty. (2004). Intervention in context-sensitive probabilistic Boolean networks. Bioinformatics. 21(7). 1211–1218. 135 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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