Subodh Kumar

3.3k total citations
68 papers, 2.5k citations indexed

About

Subodh Kumar is a scholar working on Molecular Biology, Physiology and Cancer Research. According to data from OpenAlex, Subodh Kumar has authored 68 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 27 papers in Physiology and 26 papers in Cancer Research. Recurrent topics in Subodh Kumar's work include MicroRNA in disease regulation (23 papers), Alzheimer's disease research and treatments (23 papers) and Mitochondrial Function and Pathology (10 papers). Subodh Kumar is often cited by papers focused on MicroRNA in disease regulation (23 papers), Alzheimer's disease research and treatments (23 papers) and Mitochondrial Function and Pathology (10 papers). Subodh Kumar collaborates with scholars based in United States, India and United Kingdom. Subodh Kumar's co-authors include P. Hemachandra Reddy, Murali Vijayan, Arubala P. Reddy, Jasvinder Singh Bhatti, Jangampalli Adi Pradeepkiran, Maria Mańczak, Xiangling Yin, Ramesh Kandimalla, Chandra Sekhar Kuruva and Sahil Tonk and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Annals of Surgery.

In The Last Decade

Subodh Kumar

60 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subodh Kumar United States 24 1.4k 1.0k 931 285 259 68 2.5k
Keshen Li China 29 1.2k 0.9× 716 0.7× 524 0.6× 263 0.9× 208 0.8× 110 2.5k
Surjyadipta Bhattacharjee United States 26 1.4k 1.0× 839 0.8× 904 1.0× 526 1.8× 79 0.3× 44 2.5k
Haowei Song United States 26 1.1k 0.8× 973 1.0× 275 0.3× 234 0.8× 325 1.3× 38 2.3k
Bin Feng China 31 1.9k 1.4× 441 0.4× 889 1.0× 139 0.5× 128 0.5× 71 3.3k
Monika Pawlik United States 25 1.0k 0.7× 1.2k 1.2× 226 0.2× 335 1.2× 646 2.5× 39 2.5k
Xiangdong Sun China 24 830 0.6× 428 0.4× 261 0.3× 204 0.7× 105 0.4× 72 1.9k
Jeganathan Ramesh Babu United States 30 1.9k 1.4× 987 1.0× 236 0.3× 217 0.8× 1.0k 4.0× 79 3.8k
Deling Yin United States 29 1.3k 0.9× 247 0.2× 381 0.4× 158 0.6× 232 0.9× 63 2.4k
Duan‐Fang Liao China 32 1.6k 1.2× 321 0.3× 911 1.0× 75 0.3× 309 1.2× 106 3.1k
Wei‐Lan Yeh Taiwan 28 938 0.7× 200 0.2× 370 0.4× 342 1.2× 152 0.6× 50 2.1k

Countries citing papers authored by Subodh Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Subodh Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subodh Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Subodh Kumar. A scholar is included among the top collaborators of Subodh 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 Subodh Kumar. Subodh 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.
Sharma, Bhupender, et al.. (2025). MiRNA‐501‐3p and MiRNA‐502‐3p: A promising biomarker panel for Alzheimer's disease. Clinical and Translational Medicine. 15(7). e70389–e70389. 1 indexed citations
2.
Kumar, Subodh, et al.. (2025). Integrated multi-omics analyses of synaptosomes revealed synapse-associated novel targets in Alzheimer’s disease. Molecular Psychiatry. 30(11). 5121–5136. 1 indexed citations
3.
Sharma, Bhupender, et al.. (2025). MicroRNA-based recent research developments in Alzheimer's disease. Journal of Alzheimer s Disease. 104(1). 14–31. 5 indexed citations
4.
Sharma, Bhupender, et al.. (2024). MicroRNAs and synapse turnover in Alzheimer’s disease. Ageing Research Reviews. 99. 102377–102377. 10 indexed citations
5.
Kumar, Subodh, et al.. (2024). Mitochondria-Associated MicroRNAs and Parkinson’s Disease. SHILAP Revista de lepidopterología. 19. 2318882750–2318882750. 4 indexed citations
6.
Sharma, Bhupender, et al.. (2024). MicroRNA-502-3p regulates GABAergic synapse function in hippocampal neurons. Neural Regeneration Research. 19(12). 2698–2707. 10 indexed citations
7.
Bose, Chhanda, Sudhir Kshirsagar, Murali Vijayan, et al.. (2023). The role of RLIP76 in oxidative stress and mitochondrial dysfunction: Evidence based on autopsy brains from Alzheimer's disease patients. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1870(2). 166932–166932. 6 indexed citations
8.
Gangwani, Laxman, et al.. (2023). Mitochondria Localized microRNAs: An Unexplored miRNA Niche in Alzheimer’s Disease and Aging. Cells. 12(5). 742–742. 22 indexed citations
9.
Sharma, Bhupender, et al.. (2023). Factors affecting the GABAergic synapse function in Alzheimer’s disease: Focus on microRNAs. Ageing Research Reviews. 92. 102123–102123. 12 indexed citations
10.
Kumar, Subodh, et al.. (2023). Role of MicroRNA-502-3p in Human Diseases. Pharmaceuticals. 16(4). 532–532. 17 indexed citations
11.
Kshirsagar, Sudhir, Jangampalli Adi Pradeepkiran, Ashly Hindle, et al.. (2022). A Combination Therapy of Urolithin A+EGCG Has Stronger Protective Effects than Single Drug Urolithin A in a Humanized Amyloid Beta Knockin Mice for Late-Onset Alzheimer’s Disease. Cells. 11(17). 2660–2660. 31 indexed citations
12.
Kumar, Vivek, et al.. (2022). Long-Term Health Consequences of SARS-CoV-2: Assumptions Based on SARS-CoV-1 and MERS-CoV Infections. Diagnostics. 12(8). 1852–1852. 5 indexed citations
13.
Kumar, Sunil, et al.. (2018). Determination of immunoglobulin G (IgG) concentration in buffalo colostrum and serum of new born calves by indirect ELISA. Journal of Pharmacognosy and Phytochemistry. 7(6). 1233–1235. 3 indexed citations
14.
Kumari, Priya, et al.. (2013). Molecular characterization and phylogeny based analysis of complete coding sequence of myostatin (MSTN) gene in Indian goat breeds. Small Ruminant Research. 116(2-3). 100–110. 8 indexed citations
15.
Kumar, Subodh. (2013). The safety of raw milk. 10(38). 44–49.
16.
Kumar, Nishant, Indrajit Ganguly, Rajendra Singh, et al.. (2011). DNA Polymorphism in SLC11A1 Gene and its Association with Brucellosis Resistance in Indian Zebu (Bos indicus) and Crossbred (Bos indicus×Bos taurus) Cattle. Asian-Australasian Journal of Animal Sciences. 24(7). 898–904. 16 indexed citations
17.
Kumar, Subodh, et al.. (2009). Effect of Graded Level of Dietary Energy and Protein on the Growth Performance of Cockerels. Indian Journal of Animal Nutrition. 26(1). 86–89. 2 indexed citations
18.
Verma, Naresh K., et al.. (2009). Malabari goats: characterization, management, performance and genetic variability.. The Indian Journal of Animal Sciences. 79(8). 813–818. 16 indexed citations
19.
Kumar, Subodh, et al.. (2009). An investigation on certain physical characteristics of semen in mithun.. The Indian Journal of Animal Sciences. 79(4). 375–376. 3 indexed citations
20.
Kumar, Subodh, et al.. (2001). Effect of genetic and non-genetic factors on weekly body weight of broiler rabbits in semi arid-region of Rajasthan. The Indian Journal of Animal Sciences. 71(11). 1075–1077. 6 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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