Raziur Rahman

520 total citations
19 papers, 340 citations indexed

About

Raziur Rahman is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Raziur Rahman has authored 19 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 12 papers in Computational Theory and Mathematics and 5 papers in Artificial Intelligence. Recurrent topics in Raziur Rahman's work include Computational Drug Discovery Methods (12 papers), Gene expression and cancer classification (10 papers) and Bioinformatics and Genomic Networks (6 papers). Raziur Rahman is often cited by papers focused on Computational Drug Discovery Methods (12 papers), Gene expression and cancer classification (10 papers) and Bioinformatics and Genomic Networks (6 papers). Raziur Rahman collaborates with scholars based in United States, Bangladesh and Australia. Raziur Rahman's co-authors include Ranadip Pal, Souparno Ghosh, John Otridge, Saad Haider, Rajeev Seth, Anita Mahajan, Jamal Uddin Ahmed, Farhana Afroz, Akhilesh Singh and Muhammad Abdur Rahim and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Raziur Rahman

19 papers receiving 334 citations

Peers

Raziur Rahman

CTM

George Alexandru Adam Canada

Mohan Rao United States

José Liñares-Blanco Spain

John J. Y. Lee Canada

Somayah Albaradei Saudi Arabia

Yuqi Wen China

Rachel Hodos United States

Suleiman A. Khan Finland

Jyothi Subramanian India

Kyle S. Sanchez United States

George Alexandru Adam Canada

Raziur Rahman

117 ×0.6

92 ×0.6

CTM

41 ×0.7

24 ×0.5

42 ×1.6

Citations per year, relative to Raziur Rahman Raziur Rahman (= 1×) peers George Alexandru Adam

Countries citing papers authored by Raziur Rahman

Since Specialization

Citations

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

Fields of papers citing papers by Raziur Rahman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raziur Rahman

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

All Works

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19 of 19 papers shown

Rahman, Raziur, et al.. (2023). Effectiveness of Training and Development on the Employees at Fisar Ltd. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

Rahman, Raziur, et al.. (2021). Assessment of knowledge regarding Nipah virus infection among physicians in a selected tertiary hospital, Rangpur, Bangladesh. International Journal of Community Medicine and Public Health. 8(12). 5771–5771. 3 indexed citations

Rahman, Raziur, et al.. (2019). Functional random forest with applications in dose-response predictions. Scientific Reports. 9(1). 1628–1628. 43 indexed citations

Rahman, Raziur, et al.. (2019). Recursive model for dose-time responses in pharmacological studies. BMC Bioinformatics. 20(S12). 317–317. 3 indexed citations

Rahman, Raziur, et al.. (2018). Investigation of model stacking for drug sensitivity prediction. BMC Bioinformatics. 19(S3). 71–71. 43 indexed citations

Rahman, Raziur, et al.. (2018). Application of transfer learning for cancer drug sensitivity prediction. BMC Bioinformatics. 19(S17). 497–497. 27 indexed citations

Rahman, Raziur, et al.. (2018). Evaluating the consistency of large-scale pharmacogenomic studies. Briefings in Bioinformatics. 20(5). 1734–1753. 11 indexed citations

Rahman, Raziur & Ranadip Pal. (2018). Predictive Modeling of Anti-Cancer Drug Sensitivity from Genetic Characterizations. Methods in molecular biology. 1878. 227–241. 2 indexed citations

Arora, Ramandeep Singh, Raziur Rahman, William Joe, et al.. (2018). Families of Children Newly Diagnosed With Cancer Incur Significant Out-of-Pocket Expenditure for Treatment: Report of a Multi-Site Prospective Longitudinal Study From India (INPOG-ACC-16-01). Journal of Global Oncology. 4(Supplement 2). 74s–74s. 3 indexed citations

10.

Rahman, Raziur, et al.. (2017). Heterogeneity Aware Random Forest for Drug Sensitivity Prediction. Scientific Reports. 7(1). 11347–11347. 49 indexed citations

11.

Rahman, Raziur, et al.. (2017). Sequential feature selection and inference using multi-variate random forests. Bioinformatics. 34(8). 1336–1344. 8 indexed citations

12.

Rahman, Raziur, et al.. (2017). Investigation of Model Stacking for Drug Sensitivity Prediction. 772–772. 5 indexed citations

13.

Rahman, Raziur & Ranadip Pal. (2016). A mathematical framework for analyzing drug combination toxicity for personalized medicine applications. 17. 13–16. 2 indexed citations

14.

Rahman, Raziur, et al.. (2016). Algorithms for Drug Sensitivity Prediction. Algorithms. 9(4). 77–77. 32 indexed citations

15.

Rahman, Raziur, et al.. (2016). Pattern of Bacterial Pathogens Causing Urinary Tract Infection and Their Antibiotic Sensitivity: A Tertiary Care Hospital Experience. BIRDEM Medical Journal. 5(1). 20–23. 4 indexed citations

16.

Rahman, Raziur & Ranadip Pal. (2016). Analyzing drug sensitivity prediction based on dose response curve characteristics. 67. 140–143. 7 indexed citations

17.

Rahman, Raziur, John Otridge, & Ranadip Pal. (2016). IntegratedMRF: random forest-based framework for integrating prediction from different data types. Bioinformatics. 33(9). 1407–1410. 54 indexed citations

18.

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

19.

Rahman, Raziur, Saad Haider, Souparno Ghosh, & Ranadip Pal. (2015). Design of Probabilistic Random Forests with Applications to Anticancer Drug Sensitivity Prediction. Cancer Informatics. 14s5(Suppl 5). CIN.S30794–CIN.S30794. 15 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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