Arindom Chakraborty

456 total citations
19 papers, 343 citations indexed

About

Arindom Chakraborty is a scholar working on Molecular Biology, Statistics and Probability and Oncology. According to data from OpenAlex, Arindom Chakraborty has authored 19 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Statistics and Probability and 3 papers in Oncology. Recurrent topics in Arindom Chakraborty's work include Statistical Methods and Bayesian Inference (4 papers), Allergic Rhinitis and Sensitization (3 papers) and Statistical Methods and Inference (3 papers). Arindom Chakraborty is often cited by papers focused on Statistical Methods and Bayesian Inference (4 papers), Allergic Rhinitis and Sensitization (3 papers) and Statistical Methods and Inference (3 papers). Arindom Chakraborty collaborates with scholars based in India, United States and Switzerland. Arindom Chakraborty's co-authors include Lang Li, Chien‐Wei Chiang, Jodi Skiles, Celia M. Bridges, Elizabeth Wells, Richard Ho, Jamie L. Renbarger, Elizabeth Smith, Raymond J. Hutchinson and Kashinath Bhattacharya and has published in prestigious journals such as Statistics in Medicine, Microbiology and BMC Genomics.

In The Last Decade

Arindom Chakraborty

18 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arindom Chakraborty India 9 110 80 49 43 43 19 343
Tianci Wang China 14 71 0.6× 232 2.9× 14 0.3× 13 0.3× 54 1.3× 46 535
Dora Loria Argentina 14 241 2.2× 107 1.3× 29 0.6× 39 0.9× 56 1.3× 32 762
Karthik Udupa India 13 85 0.8× 131 1.6× 18 0.4× 32 0.7× 34 0.8× 53 469
Sheng‐Jie Yu Taiwan 12 34 0.3× 126 1.6× 8 0.2× 6 0.1× 36 0.8× 35 444
Rinki Minakshi India 11 72 0.7× 163 2.0× 7 0.1× 49 1.1× 26 0.6× 15 632
Chiao-Yin Sun Taiwan 7 40 0.4× 138 1.7× 7 0.1× 21 0.5× 10 0.2× 14 380
Kumiko Watanabe Japan 10 50 0.5× 129 1.6× 7 0.1× 5 0.1× 16 0.4× 30 404
Qiufei Ma United States 10 173 1.6× 49 0.6× 9 0.2× 7 0.2× 41 1.0× 51 301
Yosr Hamdi Tunisia 10 88 0.8× 149 1.9× 17 0.3× 16 0.4× 26 0.6× 30 450

Countries citing papers authored by Arindom Chakraborty

Since Specialization
Citations

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

Fields of papers citing papers by Arindom Chakraborty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arindom Chakraborty

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

All Works

19 of 19 papers shown
1.
Molenberghs, Geert, et al.. (2021). Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective. Journal of Applied Statistics. 49(9). 2228–2245. 2 indexed citations
2.
Chakraborty, Arindom, Sandeep Ghatak, N. K. Das, et al.. (2021). BAX -248 G>A and BCL2 -938 C>A Variant Lowers the Survival in Patients with Nasopharyngeal Carcinoma and Could be Associated with Tissue-Specific Malignancies: A Multi-Method Approach. Asian Pacific Journal of Cancer Prevention. 22(4). 1171–1181. 4 indexed citations
3.
Chakraborty, Arindom, et al.. (2020). Aerobiology, epidemiology and disease forecasting of false smut disease of rice in West Bengal, India. Aerobiologia. 36(2). 299–304. 8 indexed citations
4.
Chakraborty, Arindom, et al.. (2018). Identification of airborne pollen allergens from two avenue trees of India. International Journal of Environmental Health Research. 29(4). 414–429. 6 indexed citations
5.
6.
Chakraborty, Arindom, et al.. (2017). Monitoring of airborne fungal spore load in relation to meteorological factors, air pollutants and allergic symptoms in Farakka, an unexplored biozone of eastern India. Environmental Monitoring and Assessment. 189(8). 370–370. 16 indexed citations
7.
Du, Lijun, Arindom Chakraborty, Lijun Cheng, et al.. (2015). Graphic Mining of High‐Order Drug Interactions and Their Directional Effects on Myopathy Using Electronic Medical Records. CPT Pharmacometrics & Systems Pharmacology. 4(8). 481–488. 14 indexed citations
8.
Smith, Elizabeth, Lang Li, Chien‐Wei Chiang, et al.. (2015). Patterns and severity of vincristine‐induced peripheral neuropathy in children with acute lymphoblastic leukemia. Journal of the Peripheral Nervous System. 20(1). 37–46. 152 indexed citations
9.
Chakraborty, Arindom, et al.. (2014). Experience of TBM Tunnelling in Himalaya – Prospects and Challenges. 1 indexed citations
10.
Chakraborty, Arindom. (2014). Bounded influence function based inference in joint modelling of ordinal partial linear model and accelerated failure time model. Statistical Methods in Medical Research. 25(6). 2714–2732. 3 indexed citations
11.
Jiang, Guanglong, Arindom Chakraborty, Zhiping Wang, et al.. (2013). New aQTL SNPs for the CYP2D6 Identified by a Novel Mediation Analysis of Genome-Wide SNP Arrays, Gene Expression Arrays, and CYP2D6 Activity. BioMed Research International. 2013. 1–7. 8 indexed citations
12.
13.
Chakraborty, Arindom, Guanglong Jiang, Malaz Boustani, et al.. (2013). Simultaneous inferences based on empirical Bayes methods and false discovery rates ineQTL data analysis. BMC Genomics. 14(S8). S8–S8. 4 indexed citations
14.
Chakraborty, Arindom, et al.. (2012). Spatial interaction models with individual-level data for explaining labor flows and developing local labor markets. Computational Statistics & Data Analysis. 58. 292–307. 15 indexed citations
15.
Basu, Madhumita, Ardhendu Kumar Maji, Arindom Chakraborty, et al.. (2010). Genetic association of Toll-like-receptor 4 and tumor necrosis factor-α polymorphisms with Plasmodium falciparum blood infection levels. Infection Genetics and Evolution. 10(5). 686–696. 36 indexed citations
16.
Chakraborty, Arindom & Kalyan Das. (2010). Inferences for Joint Modelling of Repeated Ordinal Scores and Time to Event Data. Computational and Mathematical Methods in Medicine. 11(3). 281–295. 8 indexed citations
17.
Chakraborty, Arindom & Kalyan Das. (2008). Mixed models for ordinal data: A pharmacokinetic study on the effectiveness of drug for the reduction of epileptic seizures. Statistics in Medicine. 27(18). 3490–3502. 1 indexed citations
18.
Chakraborty, Arindom, et al.. (2007). A Method of Finding Predictor Genes for a Particular Disease Using a Clustering Algorithm. Communications in Statistics - Simulation and Computation. 37(1). 203–211. 1 indexed citations
19.
Chakraborty, Arindom. (2005). Biclustering of gene expression data by simulated annealing. 6 pp.–632. 12 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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