Sandeep Kumar

3.8k total citations
82 papers, 2.8k citations indexed

About

Sandeep Kumar is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Immunology. According to data from OpenAlex, Sandeep Kumar has authored 82 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 49 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Immunology. Recurrent topics in Sandeep Kumar's work include Monoclonal and Polyclonal Antibodies Research (49 papers), Protein purification and stability (38 papers) and Viral Infectious Diseases and Gene Expression in Insects (17 papers). Sandeep Kumar is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (49 papers), Protein purification and stability (38 papers) and Viral Infectious Diseases and Gene Expression in Insects (17 papers). Sandeep Kumar collaborates with scholars based in United States, India and Japan. Sandeep Kumar's co-authors include Satish Kumar Singh, Patrick M. Buck, M. Michael Gromiha, Xiaoling Wang, Dheeraj S. Tomar, Puneet Rawat, Sumit Goswami, Tapan K. Das, A. Mary Thangakani and Neeraj J. Agrawal and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Bioinformatics.

In The Last Decade

Sandeep Kumar

76 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sandeep Kumar United States 32 2.4k 1.8k 406 236 222 82 2.8k
Tilman Schlothauer Germany 23 1.6k 0.7× 1.3k 0.8× 570 1.4× 124 0.5× 242 1.1× 45 2.2k
Patrik Forrer Switzerland 23 2.4k 1.0× 1.4k 0.8× 329 0.8× 100 0.4× 326 1.5× 25 3.0k
Bernhard Helk Switzerland 27 2.0k 0.8× 1.3k 0.7× 190 0.5× 301 1.3× 102 0.5× 37 2.3k
Ruei‐Min Lu Taiwan 14 1.5k 0.6× 920 0.5× 367 0.9× 308 1.3× 409 1.8× 18 2.5k
Reed J. Harris United States 27 2.9k 1.2× 1.5k 0.9× 767 1.9× 242 1.0× 197 0.9× 49 3.9k
Arvind Rajpal United States 28 1.5k 0.6× 1.4k 0.8× 874 2.2× 134 0.6× 590 2.7× 55 2.7k
Greg A. Lazar United States 24 2.1k 0.9× 2.2k 1.3× 1.2k 2.9× 163 0.7× 755 3.4× 44 3.5k
Naresh Chennamsetty United States 17 1.4k 0.6× 991 0.6× 154 0.4× 154 0.7× 98 0.4× 33 1.6k
I-Ju Liu Taiwan 12 1.1k 0.5× 841 0.5× 372 0.9× 253 1.1× 375 1.7× 22 2.0k
Stephen J. Demarest United States 25 1.6k 0.7× 1.0k 0.6× 364 0.9× 89 0.4× 309 1.4× 50 2.0k

Countries citing papers authored by Sandeep Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Sandeep Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sandeep Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Sandeep Kumar. A scholar is included among the top collaborators of Sandeep Kumar 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 Sandeep Kumar. Sandeep Kumar 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.
Rawat, Puneet, Divya Sharma, Venkata S. Mandala, et al.. (2025). Investigating Local Sequence‐Structural Attributes of Amyloidogenic Light Chain Variable Domains. Proteins Structure Function and Bioinformatics. 93(9). 1451–1464. 1 indexed citations
2.
Kumar, Sandeep, et al.. (2025). Development of bio‐lubricants from Madhuca longifolia and Ricinus communis oils via 3‐step chemical modification process for enhanced properties. The Canadian Journal of Chemical Engineering. 104(4). 1863–1876.
3.
Buchanan, Andrew, Eric M. Bennett, Andreas Evers, et al.. (2025). How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience. mAbs. 17(1). 2490790–2490790. 3 indexed citations
4.
5.
Bajpai, Anju, et al.. (2024). Identifying the causal agent of floral malformation as Fusarium complex using metagenomic and metabolomic approaches. Physiological and Molecular Plant Pathology. 136. 102556–102556. 2 indexed citations
6.
Zhang, Yulei, Matthew D. Smith, Alec A. Desai, et al.. (2024). Human antibody polyreactivity is governed primarily by the heavy-chain complementarity-determining regions. Cell Reports. 43(10). 114801–114801. 4 indexed citations
7.
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Fernández‐Quintero, Monica L., Anne Ljungars, Franz Waibl, et al.. (2023). Assessing developability early in the discovery process for novel biologics. mAbs. 15(1). 2171248–2171248. 51 indexed citations
10.
Kumar, Sandeep, et al.. (2023). Crowdfunding using Blockchain Technology. International Journal of Advanced Research in Science Communication and Technology. 148–155.
11.
Gupta, Priyanka, et al.. (2023). How can we discover developable antibody-based biotherapeutics?. Frontiers in Molecular Biosciences. 10. 1221626–1221626. 17 indexed citations
12.
Gupta, Priyanka, Emily K. Makowski, Sandeep Kumar, et al.. (2022). Antibodies with Weakly Basic Isoelectric Points Minimize Trade-offs between Formulation and Physiological Colloidal Properties. Molecular Pharmaceutics. 19(3). 775–787. 26 indexed citations
13.
Rawat, Puneet, et al.. (2021). AbsoluRATE: An in-silico method to predict the aggregation kinetics of native proteins. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1869(9). 140682–140682. 10 indexed citations
14.
Thangakani, A. Mary, Nagarajan Raju, Sandeep Kumar, et al.. (2016). CPAD, Curated Protein Aggregation Database: A Repository of Manually Curated Experimental Data on Protein and Peptide Aggregation. PLoS ONE. 11(4). e0152949–e0152949. 31 indexed citations
15.
Luo, Yin, Olga Friese, Herbert A. Runnels, et al.. (2016). The Dual Role of Lipids of the Lipoproteins in Trumenba, a Self-Adjuvanting Vaccine Against Meningococcal Meningitis B Disease. The AAPS Journal. 18(6). 1562–1575. 47 indexed citations
16.
Agrawal, Neeraj J., Bernhard Helk, Sandeep Kumar, et al.. (2015). Computational tool for the early screening of monoclonal antibodies for their viscosities. mAbs. 8(1). 43–48. 99 indexed citations
17.
Guo, Zhixiong, et al.. (2014). Assessment of Physical Stability of an Antibody Drug Conjugate by Higher Order Structure Analysis: Impact of Thiol- Maleimide Chemistry. Pharmaceutical Research. 31(7). 1710–1723. 55 indexed citations
18.
Buck, Patrick M., Sandeep Kumar, & Satish Kumar Singh. (2013). On the Role of Aggregation Prone Regions in Protein Evolution, Stability, and Enzymatic Catalysis: Insights from Diverse Analyses. PLoS Computational Biology. 9(10). e1003291–e1003291. 45 indexed citations
19.
Kumar, Sandeep, Mark A. Mitchell, Bonita Rup, & Satish Kumar Singh. (2012). Relationship Between Potential Aggregation-Prone Regions and HLA-DR-Binding T-Cell Immune Epitopes: Implications for Rational Design of Novel and Follow-on Therapeutic Antibodies. Journal of Pharmaceutical Sciences. 101(8). 2686–2701. 24 indexed citations
20.
Jindal, Charulata, et al.. (2009). Organic anion transporter protein (OATP1B1) encoded by SLCO1B1 gene polymorphism (388A>G) & susceptibility in gallstone disease.. PubMed. 129(2). 170–5. 8 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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