Debashis Nandy

1.6k total citations
17 papers, 729 citations indexed

About

Debashis Nandy is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Surgery. According to data from OpenAlex, Debashis Nandy has authored 17 papers receiving a total of 729 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Endocrinology, Diabetes and Metabolism and 4 papers in Surgery. Recurrent topics in Debashis Nandy's work include Diabetes Management and Research (3 papers), Diabetes Treatment and Management (3 papers) and Angiogenesis and VEGF in Cancer (3 papers). Debashis Nandy is often cited by papers focused on Diabetes Management and Research (3 papers), Diabetes Treatment and Management (3 papers) and Angiogenesis and VEGF in Cancer (3 papers). Debashis Nandy collaborates with scholars based in United States, Italy and Denmark. Debashis Nandy's co-authors include Debabrata Mukhopadhyay, Ananda Basu, Rita Basu, Ananda Basu, Ahmed Saad, Claudio Cobelli, James A. Levine, Rickey E. Carter, Yogish C. Kudva and Chiara Dalla Man and has published in prestigious journals such as Journal of Clinical Oncology, Diabetes Care and Cancer Research.

In The Last Decade

Debashis Nandy

17 papers receiving 714 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debashis Nandy United States 13 289 201 190 168 102 17 729
Sanda Ljubicic Switzerland 10 177 0.6× 206 1.0× 290 1.5× 256 1.5× 117 1.1× 12 730
Attila Fintha Hungary 14 123 0.4× 95 0.5× 363 1.9× 87 0.5× 128 1.3× 39 763
C. X. Andersson Sweden 7 136 0.5× 117 0.6× 239 1.3× 57 0.3× 44 0.4× 10 507
Marta M. Swierczynska Germany 8 113 0.4× 183 0.9× 258 1.4× 109 0.6× 57 0.6× 11 642
Xitai Sun China 16 121 0.4× 182 0.9× 265 1.4× 245 1.5× 29 0.3× 40 826
Markus Langkamp Germany 12 215 0.7× 76 0.4× 172 0.9× 38 0.2× 64 0.6× 16 532
Jeanne M. Franzone United States 9 129 0.4× 170 0.8× 743 3.9× 530 3.2× 98 1.0× 29 1.1k
Morten Wøjdemann Denmark 17 579 2.0× 248 1.2× 331 1.7× 579 3.4× 63 0.6× 31 1.4k
Toshiharu Onodera Japan 14 138 0.5× 187 0.9× 141 0.7× 116 0.7× 49 0.5× 29 580
R V Campos Canada 12 346 1.2× 71 0.4× 259 1.4× 348 2.1× 66 0.6× 20 743

Countries citing papers authored by Debashis Nandy

Since Specialization
Citations

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

Fields of papers citing papers by Debashis Nandy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debashis Nandy

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

All Works

17 of 17 papers shown
1.
Donkena, Krishna Vanaja, Manish Kohli, Charles Y.F. Young, et al.. (2015). Whole blood defensin mRNA expression is a predictive biomarker of docetaxel response in castration-resistant prostate cancer. OncoTargets and Therapy. 8. 1915–1915. 6 indexed citations
2.
Elishmereni, Moran, Yuri Kheifetz, Graham H. Bevan, et al.. (2015). Predicting time to castration resistance in hormone sensitive prostate cancer by a personalization algorithm based on a mechanistic model integrating patient data. The Prostate. 76(1). 48–57. 19 indexed citations
3.
Xia, Shu, Manish Kohli, Meijun Du, et al.. (2015). Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. Oncotarget. 6(18). 16411–16421. 38 indexed citations
4.
Kohli, Manish, Debashis Nandy, Charlotte Haley, et al.. (2014). Impact of beta-blocker medication use on prostate cancer survival: Results from a single-institution cancer registry.. Journal of Clinical Oncology. 32(15_suppl). e16064–e16064. 1 indexed citations
5.
Jiménez, Rafael E., Debashis Nandy, Rui Qin, et al.. (2014). Neuroendocrine differentiation patterns in metastases from advanced prostate cancer.. Journal of Clinical Oncology. 32(15_suppl). 5085–5085. 4 indexed citations
6.
Nandy, Debashis, Christopher M. Johnson, Rita Basu, et al.. (2014). The effect of liraglutide on endothelial function in patients with type 2 diabetes. Diabetes and Vascular Disease Research. 11(6). 419–430. 46 indexed citations
7.
Hinshaw, Ling, Chiara Dalla Man, Debashis Nandy, et al.. (2013). Diurnal Pattern of Insulin Action in Type 1 Diabetes. Diabetes. 62(7). 2223–2229. 97 indexed citations
8.
Saad, Ahmed, Chiara Dalla Man, Debashis Nandy, et al.. (2012). Diurnal Pattern to Insulin Secretion and Insulin Action in Healthy Individuals. Diabetes. 61(11). 2691–2700. 214 indexed citations
9.
Manohar, Chinmay U., James A. Levine, Debashis Nandy, et al.. (2012). The Effect of Walking on Postprandial Glycemic Excursion in Patients With Type 1 Diabetes and Healthy People. Diabetes Care. 35(12). 2493–2499. 78 indexed citations
10.
Nandy, Debashis & Debabrata Mukhopadhyay. (2011). Growth Factor Mediated Signaling in Pancreatic Pathogenesis. Cancers. 3(1). 841–871. 27 indexed citations
11.
Nandy, Debashis, Rajiv Janardhanan, Debabrata Mukhopadhyay, & Ananda Basu. (2011). Effect of Hyperglycemia on Human Monocyte Activation. Journal of Investigative Medicine. 59(4). 661–667. 37 indexed citations
12.
Nandy, Debashis, Debabrata Mukhopadhyay, & Ananda Basu. (2010). Both Vascular Endothelial Growth Factor and Soluble Flt-1 are Increased in Type 2 Diabetes but not in Impaired Fasting Glucose. Journal of Investigative Medicine. 58(6). 804–806. 20 indexed citations
13.
Wang, Ling, Julie S. Lau, Chitta Ranjan Patra, et al.. (2010). RGS-GAIP–Interacting Protein Controls Breast Cancer Progression. Molecular Cancer Research. 8(12). 1591–1600. 17 indexed citations
14.
Nandy, Debashis, Debabrata Mukhopadhyay, & Ananda Basu. (2010). Both vascular endothelial growth factor and soluble Flt-1 are increased in type 2 diabetes but not in impaired fasting glucose.. PubMed. 58(6). 804–6. 20 indexed citations
15.
Nandy, Debashis, Yan W. Asmann, Debabrata Mukhopadhyay, & Ananda Basu. (2009). Role of AKT‐glycogen synthase kinase axis in monocyte activation in human beings with and without type 2 diabetes. Journal of Cellular and Molecular Medicine. 14(6b). 1396–1407. 12 indexed citations
16.
Cao, Ying, Ling Wang, Debashis Nandy, et al.. (2008). Neuropilin-1 Upholds Dedifferentiation and Propagation Phenotypes of Renal Cell Carcinoma Cells by Activating Akt and Sonic Hedgehog Axes. Cancer Research. 68(21). 8667–8672. 81 indexed citations
17.
Basu, Ananda, Michael Dam Jensen, Frances V. McCann, et al.. (2007). Lack of an Effect of Pioglitazone or Glipizide on Lipoprotein-Associated Phospholipase A2 in Type 2 Diabetes. Endocrine Practice. 13(2). 147–152. 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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