Ankit Jain

2.1k total citations
35 papers, 720 citations indexed

About

Ankit Jain is a scholar working on Molecular Biology, Oncology and Plant Science. According to data from OpenAlex, Ankit Jain has authored 35 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Oncology and 7 papers in Plant Science. Recurrent topics in Ankit Jain's work include Agricultural pest management studies (4 papers), Genetic and Environmental Crop Studies (4 papers) and Advanced Proteomics Techniques and Applications (3 papers). Ankit Jain is often cited by papers focused on Agricultural pest management studies (4 papers), Genetic and Environmental Crop Studies (4 papers) and Advanced Proteomics Techniques and Applications (3 papers). Ankit Jain collaborates with scholars based in India, United States and Australia. Ankit Jain's co-authors include Rajeev K. Varshney, Manish Roorkiwal, Sandip M. Kale, Poonam Piplani, Harsha Gowda, Akhilesh Pandey, Annapurna Chitikineni, Aditi Chatterjee, Gajanan Sathe and Vanika Garg and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ankit Jain

33 papers receiving 705 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ankit Jain India 16 319 259 124 90 52 35 720
Chunhua Huang China 15 193 0.6× 414 1.6× 55 0.4× 168 1.9× 42 0.8× 37 777
Yanfen Liu China 12 213 0.7× 430 1.7× 55 0.4× 56 0.6× 20 0.4× 24 867
Qingxin Liu China 16 150 0.5× 369 1.4× 38 0.3× 134 1.5× 35 0.7× 37 657
Hongli Dong China 17 175 0.5× 572 2.2× 86 0.7× 50 0.6× 22 0.4× 26 777
Qianwen Cao China 15 108 0.3× 193 0.7× 137 1.1× 94 1.0× 77 1.5× 32 703
Makoto Kihara Japan 13 229 0.7× 530 2.0× 72 0.6× 64 0.7× 29 0.6× 29 841
Qun Zhu China 17 474 1.5× 633 2.4× 48 0.4× 119 1.3× 18 0.3× 29 1.1k
Wei Ma China 19 78 0.2× 612 2.4× 114 0.9× 35 0.4× 23 0.4× 53 1.1k
Guido Leoni Italy 17 109 0.3× 388 1.5× 149 1.2× 61 0.7× 23 0.4× 47 829

Countries citing papers authored by Ankit Jain

Since Specialization
Citations

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

Fields of papers citing papers by Ankit Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ankit Jain

This figure shows the co-authorship network connecting the top 25 collaborators of Ankit Jain. A scholar is included among the top collaborators of Ankit Jain 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 Ankit Jain. Ankit Jain 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
2.
Jain, Ankit, et al.. (2024). Identification of dysregulation of sphingolipids in retinoblastoma using liquid chromatography-mass spectrometry. Experimental Eye Research. 240. 109798–109798.
3.
Jain, Ankit, et al.. (2022). Pan-cancer quantitation of epithelial-mesenchymal transition dynamics using parallel reaction monitoring-based targeted proteomics approach. Journal of Translational Medicine. 20(1). 84–84. 3 indexed citations
4.
Byeon, Seul Kee, Anil K. Madugundu, Ankit Jain, et al.. (2021). Cerebrospinal fluid lipidomics for biomarkers of Alzheimer's disease. Molecular Omics. 17(3). 454–463. 28 indexed citations
5.
Bhogireddy, Sailaja, Satendra K. Mangrauthia, Rakesh Kumar, et al.. (2021). Regulatory non-coding RNAs: a new frontier in regulation of plant biology. Functional & Integrative Genomics. 21(3-4). 313–330. 68 indexed citations
6.
Jain, Ankit, et al.. (2021). A Rare Case of Spontaneous Splenic Rupture as the Index Presentation of Chronic Myeloid Leukemia. Cureus. 13(11). e19647–e19647. 3 indexed citations
7.
Rai, Shalu, et al.. (2021). Impact of Oral Health Factors on Quality of Life of Geriatric Population - A Systematic Review. SHILAP Revista de lepidopterología. 33(4). 453–465. 5 indexed citations
8.
Jain, Ankit, et al.. (2021). Gastric Carcinoma: An Unexpected Complication of Loop Gastro-Jejunostomy Done in Childhood. Cureus. 13(6). e15900–e15900. 1 indexed citations
9.
Akhtar, Mohd Javed, Puja Sakhuja, Anil Agarwal, et al.. (2021). Plasma-derived candidate biomarkers for detection of gallbladder carcinoma. Scientific Reports. 11(1). 23554–23554. 15 indexed citations
10.
Sathe, Gajanan, Kiran K. Mangalaparthi, Ankit Jain, et al.. (2020). Multiplexed Phosphoproteomic Study of Brain in Patients with Alzheimer's Disease and Age-Matched Cognitively Healthy Controls. OMICS A Journal of Integrative Biology. 24(4). 216–227. 22 indexed citations
11.
Khanna, Shweta, Prasanta Padhan, Ankit Jain, et al.. (2020). Altered mitochondrial proteome and functional dynamics in patients with rheumatoid arthritis. Mitochondrion. 54. 8–14. 16 indexed citations
12.
Sathe, Gajanan, Ankit Jain, Krishna Patel, et al.. (2020). Urinary glycoproteomic profiling of non-muscle invasive and muscle invasive bladder carcinoma patients reveals distinct N-glycosylation pattern of CD44, MGAM, and GINM1. Oncotarget. 11(34). 3244–3255. 12 indexed citations
13.
Jain, Ankit, et al.. (2019). InDel markers: An extended marker resource for molecular breeding in chickpea. PLoS ONE. 14(3). e0213999–e0213999. 43 indexed citations
14.
Roorkiwal, Manish, Diego Jarquín, Muneendra Kumar Singh, et al.. (2018). Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea. Scientific Reports. 8(1). 11701–11701. 50 indexed citations
15.
Rajagopalan, Pavithra, Ankit Jain, Vishalakshi Nanjappa, et al.. (2018). Proteome-wide changes in primary skin keratinocytes exposed to diesel particulate extract—A role for antioxidants in skin health. Journal of Dermatological Science. 91(3). 239–249. 30 indexed citations
16.
Solanki, Hitendra S., Niraj Babu, Ankit Jain, et al.. (2017). Cigarette smoke induces mitochondrial metabolic reprogramming in lung cells. Mitochondrion. 40. 58–70. 20 indexed citations
17.
Roorkiwal, Manish, Abhishek Rathore, Roma Rani Das, et al.. (2016). Genome-Enabled Prediction Models for Yield Related Traits in Chickpea. Frontiers in Plant Science. 7. 1666–1666. 98 indexed citations
18.
Rajagopalan, Pavithra, Ankit Jain, Aafaque Ahmad Khan, et al.. (2015). LC–MS-based serum metabolomic analysis reveals dysregulation of phosphatidylcholines in esophageal squamous cell carcinoma. Journal of Proteomics. 127(Pt A). 96–102. 42 indexed citations
19.
Jain, Ankit, Saurabh Chaudhary, & Prakash Chand Sharma. (2013). Mining of microsatellites using next generation sequencing of seabuckthorn (Hippophae rhamnoides L.) transcriptome. Physiology and Molecular Biology of Plants. 20(1). 115–123. 14 indexed citations
20.
Jain, Ankit, Rajesh Ghangal, Atul Grover, Saurabh Raghuvanshi, & Prakash Chand Sharma. (2010). Development of EST-based new SSR markers in seabuckthorn. Physiology and Molecular Biology of Plants. 16(4). 375–378. 23 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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