D Surekha
- Co-authors
- S. VishnupriyaRaghunadharao DigumartiD. N. RaoSenthil RajappaT. PadmaNageswara Rao DunnaAmirtharaj FrancisSingh Rajender
- Topics
- Glutathione Transferases and Polymorphisms (7 papers)Estrogen and related hormone effects (7 papers)Pharmacogenetics and Drug Metabolism (5 papers)
- Cited by
- HematologyPharmacologyOncology
- Partner nations
- India
In The Last Decade
D Surekha
22 papers receiving 322 citations
Peers
Comparison fields: 5 of 53
- Molecular Biology 198
- Oncology 107
- Public Health, Environmental and Occupational Health 61
- Genetics 58
- Hematology 55
Countries citing papers authored by D Surekha
This map shows the geographic impact of D Surekha'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 D Surekha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D Surekha more than expected).
Fields of papers citing papers by D Surekha
This network shows the impact of papers produced by D Surekha. 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 D Surekha. The network helps show where D Surekha may publish in the future.
Co-authorship network of co-authors of D Surekha
This figure shows the co-authorship network connecting the top 25 collaborators of D Surekha. A scholar is included among the top collaborators of D Surekha 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 D Surekha. D Surekha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 25 | |
| 3 | 22 | |
| 4 | 15 | |
| 5 | 11 | |
| 6 | Association of Leptin receptor (LEPR) Q223R Polymorphism with breast cancer | 6 |
| 7 | 20 | |
| 8 | NQO1*2 (NAD(P)H: quinone oxidoreductase 1) polymorphism and its influence on acute leukemia risk | 2 |
| 9 | 6 | |
| 10 | Codon 72 and G13964C intron 6 polymorphisms of TP53 in relation to development and progression of breast cancer in India. | 15 |
| 11 | Association of an MDR1 gene (C3435T) polymorphism with acute leukemia in India. | 46 |
| 12 | Association of a CYP17 gene polymorphism with development of breast cancer in India. | 13 |
| 13 | CYP2D6*4 polymorphisms and breast cancer risk | 10 |
| 14 | 9 | |
| 15 | Association of CYP3A5*3 and CYP3A5*6 Polymorphisms with Breast Cancer Risk | 2 |
| 16 | 9 | |
| 17 | 21 | |
| 18 | ABCB1 (MDR1, P-Glycoprotein) C3435T Gene Polymorphism and its Possible Association with Chronic Myeloid Leukemia Prognosis | 9 |
| 19 | 18 | |
| 20 | 6 |
About D Surekha
D Surekha is a scholar working on Pharmacology, Toxicology and Genetics, having authored 22 papers that have together received 340 indexed citations. Recurring topics across this work include Glutathione Transferases and Polymorphisms (7 papers), Estrogen and related hormone effects (7 papers) and Pharmacogenetics and Drug Metabolism (5 papers). The work is most often cited by research in Hematology (55 citations), Pharmacology (36 citations) and Oncology (107 citations). D Surekha has collaborated with scholars based in India. Frequent co-authors include S. Vishnupriya, Raghunadharao Digumarti, D. N. Rao, Senthil Rajappa, T. Padma, Nageswara Rao Dunna, Amirtharaj Francis, Singh Rajender, Kapaettu Satyamoorthy and Kumarasamy Thangaraj. Their work appears in journals such as PLoS ONE, Breast Cancer Research and Treatment and Mitochondrion.
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.