Dipen Sangurdekar

952 total citations
24 papers, 627 citations indexed

About

Dipen Sangurdekar is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Plant Science. According to data from OpenAlex, Dipen Sangurdekar has authored 24 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Pathology and Forensic Medicine and 6 papers in Plant Science. Recurrent topics in Dipen Sangurdekar's work include Multiple Sclerosis Research Studies (6 papers), Legume Nitrogen Fixing Symbiosis (5 papers) and DNA Repair Mechanisms (4 papers). Dipen Sangurdekar is often cited by papers focused on Multiple Sclerosis Research Studies (6 papers), Legume Nitrogen Fixing Symbiosis (5 papers) and DNA Repair Mechanisms (4 papers). Dipen Sangurdekar collaborates with scholars based in United States, Switzerland and Canada. Dipen Sangurdekar's co-authors include Arkady Khodursky, Friedrich Srienc, Woo-Suk Chang, Zhigang Zhang, David W. Emerich, Eddie Cytryn, Trupti Joshi, Dong Xu, Gary Stacey and Michael J. Sadowsky and has published in prestigious journals such as Blood, PLoS ONE and Applied and Environmental Microbiology.

In The Last Decade

Dipen Sangurdekar

22 papers receiving 620 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dipen Sangurdekar United States 13 267 153 118 113 68 24 627
Raul Salinas United States 13 528 2.0× 261 1.7× 129 1.1× 59 0.5× 42 0.6× 24 869
Shaowu Li China 19 188 0.7× 33 0.2× 44 0.4× 35 0.3× 99 1.5× 54 739
C. Lu China 10 291 1.1× 16 0.1× 198 1.7× 76 0.7× 49 0.7× 12 649
Yuehong Wu China 14 372 1.4× 32 0.2× 63 0.5× 11 0.1× 41 0.6× 35 653
Carlos C. Flores United States 14 828 3.1× 470 3.1× 150 1.3× 17 0.2× 63 0.9× 24 1.1k
Christina L. Wysoczynski United States 9 325 1.2× 49 0.3× 60 0.5× 12 0.1× 42 0.6× 9 442
Floyd Wittink Netherlands 14 360 1.3× 76 0.5× 99 0.8× 9 0.1× 43 0.6× 20 654
Olga N. Borkhsenious United States 11 373 1.4× 195 1.3× 32 0.3× 20 0.2× 32 0.5× 14 780
John Wallis United States 5 320 1.2× 111 0.7× 201 1.7× 11 0.1× 25 0.4× 5 468
Alejandra Medina-Rivera Mexico 14 1.0k 3.9× 236 1.5× 227 1.9× 9 0.1× 40 0.6× 36 1.3k

Countries citing papers authored by Dipen Sangurdekar

Since Specialization
Citations

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

Fields of papers citing papers by Dipen Sangurdekar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dipen Sangurdekar

This figure shows the co-authorship network connecting the top 25 collaborators of Dipen Sangurdekar. A scholar is included among the top collaborators of Dipen Sangurdekar 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 Dipen Sangurdekar. Dipen Sangurdekar 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.
2.
Dodson, Anne E., Sol Shenker, Pamela Sullivan, et al.. (2024). Pan-Cancer Analysis of Homologous Recombination Deficiency in Cell Lines. Cancer Research Communications. 4(12). 3084–3098. 1 indexed citations
3.
Rytlewski, Julie, Deepu Madduri, Timothy Campbell, et al.. (2020). Effects of Prior Alkylating Therapies on Preinfusion Patient Characteristics and Starting Material for CAR T Cell Product Manufacturing in Late-Line Multiple Myeloma. Blood. 136(Supplement 1). 7–8. 9 indexed citations
4.
Calabresi, Peter A., Douglas L. Arnold, Dipen Sangurdekar, et al.. (2020). Temporal profile of serum neurofilament light in multiple sclerosis: Implications for patient monitoring. Multiple Sclerosis Journal. 27(10). 1497–1505. 28 indexed citations
5.
6.
Sangurdekar, Dipen, Chao Sun, Helen McLaughlin, et al.. (2019). Genetic Study of Severe Prolonged Lymphopenia in Multiple Sclerosis Patients Treated With Dimethyl Fumarate. Frontiers in Genetics. 10. 1039–1039. 3 indexed citations
7.
Kühle, Jens, Tatiana Plavina, Christian Barro, et al.. (2019). Neurofilament light levels are associated with long-term outcomes in multiple sclerosis. Multiple Sclerosis Journal. 26(13). 1691–1699. 83 indexed citations
8.
Rhead, Brooke, Tone Berge, Hong Quach, et al.. (2018). Increased DNA methylation of SLFN12 in CD4+ and CD8+ T cells from multiple sclerosis patients. PLoS ONE. 13(10). e0206511–e0206511. 34 indexed citations
9.
Calabresi, Peter A., Douglas L. Arnold, R. Philip Kinkel, et al.. (2018). Serum Neurofilament Light (NfL): Towards a Blood Test for Prognosis and Disease/Treatment Monitoring in Multiple Sclerosis Patients (S24.003). Neurology. 90(15_supplement). 6 indexed citations
10.
Franck, William L., Woo-Suk Chang, Dipen Sangurdekar, et al.. (2014). Comparative transcriptomic analysis of symbiotic Bradyrhizobium japonicum. Symbiosis. 63(3). 123–135. 6 indexed citations
11.
Edwards, Andrea L., et al.. (2013). Transient Growth Arrest in Escherichia coli Induced by Chromosome Condensation. PLoS ONE. 8(12). e84027–e84027. 6 indexed citations
12.
Lee, Hae-In, et al.. (2012). Effect of Soybean Coumestrol on Bradyrhizobium japonicum Nodulation Ability, Biofilm Formation, and Transcriptional Profile. Applied and Environmental Microbiology. 78(8). 2896–2903. 43 indexed citations
13.
Sangurdekar, Dipen, Zhigang Zhang, & Arkady Khodursky. (2011). The association of DNA damage response and nucleotide level modulation with the antibacterial mechanism of the anti-folate drug Trimethoprim. BMC Genomics. 12(1). 51 indexed citations
14.
Sangurdekar, Dipen, et al.. (2010). Thymineless death is associated with loss of essential genetic information from the replication origin. Molecular Microbiology. 75(6). 1455–1467. 39 indexed citations
15.
Zare, Hossein, Dipen Sangurdekar, Poonam Srivastava, M. Kaveh, & Arkady Khodursky. (2009). Reconstruction of Escherichia coli transcriptional regulatory networks via regulon-based associations. BMC Systems Biology. 3(1). 39–39. 22 indexed citations
16.
Gilbert, Alan, Dipen Sangurdekar, & Friedrich Srienc. (2009). Rapid strain improvement through optimized evolution in the cytostat. Biotechnology and Bioengineering. 103(3). 500–512. 25 indexed citations
17.
Cytryn, Eddie, Dipen Sangurdekar, John G. Streeter, et al.. (2007). Transcriptional and Physiological Responses of Bradyrhizobium japonicum to Desiccation-Induced Stress. Journal of Bacteriology. 189(19). 6751–6762. 138 indexed citations
18.
Cytryn, Eddie, Dipen Sangurdekar, John G. Streeter, et al.. (2007). Transcriptional and Physiological Responses of Bradyrhizobium japonicum to Desiccation-Induced Stress. Journal of Bacteriology. 189(24). 9150–9150. 3 indexed citations
19.
Sangurdekar, Dipen, Friedrich Srienc, & Arkady Khodursky. (2006). A classification based framework for quantitative description of large-scale microarray data. Genome biology. 7(4). R32–R32. 56 indexed citations
20.
Sangurdekar, Dipen, Friedrich Srienc, & Arkady Khodursky. (2005). AIChE Annual Meeting, Conference Proceedings. 16 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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