Debalina Datta

1.4k total citations
21 papers, 310 citations indexed

About

Debalina Datta is a scholar working on Molecular Biology, Oncology and Physiology. According to data from OpenAlex, Debalina Datta has authored 21 papers receiving a total of 310 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Physiology. Recurrent topics in Debalina Datta's work include Alzheimer's disease research and treatments (4 papers), RNA Research and Splicing (4 papers) and Prion Diseases and Protein Misfolding (3 papers). Debalina Datta is often cited by papers focused on Alzheimer's disease research and treatments (4 papers), RNA Research and Splicing (4 papers) and Prion Diseases and Protein Misfolding (3 papers). Debalina Datta collaborates with scholars based in India, Pakistan and Norway. Debalina Datta's co-authors include Samir K. Maji, Ambuja Navalkar, Debdeep Chatterjee, Komal Patel, Satyaprakash Pandey, Laxmikant Gadhe, Namrata Singh, Pradeep Kadu, Semanti Mukherjee and Saikat Ghosh and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Biomaterials.

In The Last Decade

Debalina Datta

20 papers receiving 305 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debalina Datta India 11 162 62 43 41 28 21 310
Apoorva Mandavilli United States 10 121 0.7× 85 1.4× 21 0.5× 11 0.3× 17 0.6× 48 368
Melissa Hewitt Canada 11 172 1.1× 43 0.7× 11 0.3× 33 0.8× 55 2.0× 24 437
Mengyuan Wang China 13 145 0.9× 21 0.3× 13 0.3× 69 1.7× 57 2.0× 59 488
Yoshiteru Yamada Japan 12 225 1.4× 50 0.8× 20 0.5× 17 0.4× 3 0.1× 38 412
Guang‐chou Tu United States 13 277 1.7× 48 0.8× 15 0.3× 16 0.4× 11 0.4× 17 466
Yuyan Chen China 13 147 0.9× 95 1.5× 11 0.3× 34 0.8× 28 1.0× 43 489
Yuka Hasegawa Japan 12 188 1.2× 35 0.6× 21 0.5× 59 1.4× 5 0.2× 47 436
Emel Timuçin Türkiye 11 236 1.5× 29 0.5× 8 0.2× 15 0.4× 18 0.6× 32 392
Miho Ito Japan 10 94 0.6× 33 0.5× 5 0.1× 69 1.7× 5 0.2× 36 355
Viktor Dombrádi Hungary 13 232 1.4× 21 0.3× 7 0.2× 27 0.7× 3 0.1× 44 454

Countries citing papers authored by Debalina Datta

Since Specialization
Citations

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

Fields of papers citing papers by Debalina Datta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debalina Datta

This figure shows the co-authorship network connecting the top 25 collaborators of Debalina Datta. A scholar is included among the top collaborators of Debalina Datta 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 Debalina Datta. Debalina Datta 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.
Datta, Debalina, Ambuja Navalkar, Arunima Sakunthala, et al.. (2024). Nucleo-cytoplasmic environment modulates spatiotemporal p53 phase separation. Science Advances. 10(50). eads0427–eads0427. 7 indexed citations
2.
Sengupta, Shinjinee, Namrata Singh, Debalina Datta, et al.. (2023). p53 amyloid pathology is correlated with higher cancer grade irrespective of the mutant or wild-type form. Journal of Cell Science. 136(17). 11 indexed citations
3.
Singh, Namrata, Komal Patel, Ambuja Navalkar, et al.. (2023). Amyloid fibril-based thixotropic hydrogels for modeling of tumor spheroids in vitro. Biomaterials. 295. 122032–122032. 17 indexed citations
4.
Poudyal, Manisha, Komal Patel, Laxmikant Gadhe, et al.. (2023). Intermolecular interactions underlie protein/peptide phase separation irrespective of sequence and structure at crowded milieu. Nature Communications. 14(1). 6199–6199. 81 indexed citations
5.
Sakunthala, Arunima, Debalina Datta, Ambuja Navalkar, et al.. (2022). Direct Demonstration of Seed Size-Dependent α-Synuclein Amyloid Amplification. The Journal of Physical Chemistry Letters. 13(28). 6427–6438. 12 indexed citations
6.
Mehra, Surabhi, Harish Kumar, Debalina Datta, et al.. (2022). α-Synuclein Aggregation Intermediates form Fibril Polymorphs with Distinct Prion-like Properties. Journal of Molecular Biology. 434(19). 167761–167761. 13 indexed citations
7.
Navalkar, Ambuja, Satyaprakash Pandey, Namrata Singh, et al.. (2021). Direct evidence of cellular transformation by prion-like p53 amyloid infection. Journal of Cell Science. 134(11). 19 indexed citations
8.
Jacob, Reeba S., Subhadeep Das, Namrata Singh, et al.. (2018). Amyloids Are Novel Cell-Adhesive Matrices. Advances in experimental medicine and biology. 1112. 79–97. 10 indexed citations
9.
Mohite, Ganesh M., Rakesh Kumar, Rajlaxmi Panigrahi, et al.. (2018). Comparison of Kinetics, Toxicity, Oligomer Formation, and Membrane Binding Capacity of α-Synuclein Familial Mutations at the A53 Site, Including the Newly Discovered A53V Mutation. Biochemistry. 57(35). 5183–5187. 36 indexed citations
10.
Chakrabarti, Amit, et al.. (2015). Descriptive epidemiology and high risk behavior of male prescription opioid abusers: Cross-sectional study from Sikkim, North East India. Indian Journal of Psychiatry. 57(3). 284–284. 5 indexed citations
11.
Datta, Debalina, et al.. (2015). Role of social interaction on quality of life. SHILAP Revista de lepidopterología. 5(4). 290–292. 10 indexed citations
12.
Datta, Debalina, et al.. (2015). Association of quality of life of urban elderly with socio-demographic factors. International Journal of Medicine and Public Health. 5(4). 274–274. 15 indexed citations
13.
Mukhopadhyay, Asish K., et al.. (2013). SOCIO-DEMOGRAPHIC PROFILE AND SUICIDAL INTENT OF ATTEMPTED SUICIDE CASES: A HOSPITAL BASED STUDY IN WEST BENGAL, INDIA. SHILAP Revista de lepidopterología. 3(2). 122–125. 5 indexed citations
14.
Datta, Debalina, et al.. (2013). A STUDY ON MOTIVATION AND SATISFACTION OF EMPLOYEES IN CORPORATE HOSPITALS IN KOLKATA, INDIA. SHILAP Revista de lepidopterología. 3(1). 56–59. 7 indexed citations
15.
Datta, Debalina, et al.. (2013). Epidemiology of cervical spinal cord injury in eastern India: an autopsy-based study.. PubMed. 126(1377). 30–40. 2 indexed citations
16.
17.
Datta, Debalina, et al.. (2001). Effect of addition of proton carriers in culture medium on growth and secretion of hybridoma cell line OKT3.. PubMed. 45(3). 367–72. 2 indexed citations
18.
Datta, Debalina, et al.. (2000). Effect of Cationic Amino Acid, L-Lysine and its Polymers on the Growth and Secretion of Hybridoma Cell Line OKT-3. Hybridoma. 19(4). 339–346. 5 indexed citations
19.
Prasad, Nripesh, et al.. (1998). Monoclonal antibody: high density culture of hybridoma cells and downstream processing for IgG recovery.. PubMed. 36(2). 125–35. 5 indexed citations
20.
Prasad, Nripesh, et al.. (1998). Getting higher yields of monoclonal antibody in culture.. PubMed. 42(2). 155–71. 5 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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