Mercy Pawar

412 total citations
25 papers, 288 citations indexed

About

Mercy Pawar is a scholar working on Ophthalmology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mercy Pawar has authored 25 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ophthalmology, 13 papers in Molecular Biology and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mercy Pawar's work include Retinal Diseases and Treatments (8 papers), Retinal Development and Disorders (7 papers) and Ocular Infections and Treatments (6 papers). Mercy Pawar is often cited by papers focused on Retinal Diseases and Treatments (8 papers), Retinal Development and Disorders (7 papers) and Ocular Infections and Treatments (6 papers). Mercy Pawar collaborates with scholars based in United States, India and Germany. Mercy Pawar's co-authors include Cagri G. Besirli, Suresh B. Patil, Khalil N. Bitar, Thomas J. Wubben, Heather Hager, Eric Weh, Andrew J. H. Smith, Andrew D. Smith, Hakan Demirci and P. P. Vaishnava and has published in prestigious journals such as Scientific Reports, Biochemical and Biophysical Research Communications and Ophthalmology.

In The Last Decade

Mercy Pawar

24 papers receiving 287 citations

Peers

Mercy Pawar
Siyan Zhu United States
Pei Zhuang United States
Ritika Gupta United States
Yogita Kanan United States
Junjing Guo United States
Seden Grippon United States
Joshua W. Goldman United States
Ruth Jacobson United States
Siyan Zhu United States
Mercy Pawar
Citations per year, relative to Mercy Pawar Mercy Pawar (= 1×) peers Siyan Zhu

Countries citing papers authored by Mercy Pawar

Since Specialization
Citations

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

Fields of papers citing papers by Mercy Pawar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mercy Pawar

This figure shows the co-authorship network connecting the top 25 collaborators of Mercy Pawar. A scholar is included among the top collaborators of Mercy Pawar 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 Mercy Pawar. Mercy Pawar 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.
Niziol, Leslie M., Ziyun Yang, Yiqing Wang, et al.. (2025). Association of Deep Learning Imaging Algorithm Measures of Microbial Keratitis With Vision Outcomes. Cornea.
2.
Woodward, Maria A., Leslie M. Niziol, Shahzad I. Mian, et al.. (2025). Factors Associated with Vision Outcomes in Microbial Keratitis. Ophthalmology. 132(7). 830–841. 1 indexed citations
3.
Woodward, Maria A., et al.. (2025). Self-knowledge distillation-empowered directional connectivity transformer for microbial keratitis biomarkers segmentation on slit-lamp photography. Medical Image Analysis. 102. 103533–103533. 1 indexed citations
4.
Besirli, Cagri G., et al.. (2024). HSPB4/CRYAA Protect Photoreceptors during Retinal Detachment in Part through FAIM2 Regulation. Neurology International. 16(5). 905–917. 4 indexed citations
5.
Indrayan, Abhaya, et al.. (2024). Use of ROC curve analysis for prediction gives fallacious results: Use predictivity-based indices. Journal of Postgraduate Medicine. 70(2). 91–96. 6 indexed citations
6.
Pawar, Mercy, et al.. (2023). The effect of social determinants of health on severity of microbial keratitis presentation at a tertiary eye care hospital in Southern India. Indian Journal of Ophthalmology. 71(6). 2448–2454. 2 indexed citations
7.
Wubben, Thomas J., Sraboni Chaudhury, Jeanne A. Stuckey, et al.. (2023). Development of Novel Small-Molecule Activators of Pyruvate Kinase Muscle Isozyme 2, PKM2, to Reduce Photoreceptor Apoptosis. Pharmaceuticals. 16(5). 705–705. 6 indexed citations
8.
Mei, Ling, Minzhi Yu, Yayuan Liu, et al.. (2022). Synthetic high-density lipoprotein nanoparticles delivering rapamycin for the treatment of age-related macular degeneration. Nanomedicine Nanotechnology Biology and Medicine. 44. 102571–102571. 15 indexed citations
9.
Pawar, Mercy, et al.. (2022). Quantitative analysis of tear angiogenic factors in retinopathy of prematurity: a pilot biomarker study. Journal of American Association for Pediatric Ophthalmology and Strabismus. 27(1). 14.e1–14.e6. 5 indexed citations
10.
Woodward, Maria A., N. Venkatesh Prajna, Matthias F. Kriegel, et al.. (2021). Open-Source Automatic Biomarker Measurement on Slit-Lamp Photography to Estimate Visual Acuity in Microbial Keratitis. Translational Vision Science & Technology. 10(12). 2–2. 5 indexed citations
11.
Wubben, Thomas J., et al.. (2020). Development of novel pyruvate kinase muscle isoform 2 (PKM2) activators for photoreceptor neuroprotection. Investigative Ophthalmology & Visual Science. 61(7). 4938–4938. 1 indexed citations
12.
Wubben, Thomas J., Mercy Pawar, Eric Weh, et al.. (2020). Small molecule activation of metabolic enzyme pyruvate kinase muscle isozyme 2, PKM2, circumvents photoreceptor apoptosis. Scientific Reports. 10(1). 2990–2990. 30 indexed citations
13.
Weh, Eric, Andrew D. Smith, Heather Hager, et al.. (2020). Hexokinase 2 is dispensable for photoreceptor development but is required for survival during aging and outer retinal stress. Cell Death and Disease. 11(6). 422–422. 29 indexed citations
14.
Smith, Andrew J. H., Mercy Pawar, Marcian E. Van Dort, et al.. (2018). Ocular Toxicity Profile of ST-162 and ST-168 as Novel Bifunctional MEK/PI3K Inhibitors. Journal of Ocular Pharmacology and Therapeutics. 34(6). 477–485. 1 indexed citations
15.
Wubben, Thomas J., et al.. (2018). Photoreceptor metabolic reprogramming provides survival advantage in acute stress while causing chronic degeneration. Investigative Ophthalmology & Visual Science. 59(9). 4448–4448. 16 indexed citations
16.
Wubben, Thomas J., et al.. (2017). Photoreceptor metabolic reprogramming provides survival advantage in acute stress while causing chronic degeneration. Scientific Reports. 7(1). 17863–17863. 39 indexed citations
17.
Pawar, Mercy, et al.. (2017). FAS apoptotic inhibitory molecule 2 is a stress-induced intrinsic neuroprotective factor in the retina. Cell Death and Differentiation. 24(10). 1799–1810. 15 indexed citations
18.
Patil, Suresh B., Yasuhiro Tsunoda, Mercy Pawar, & Khalil N. Bitar. (2004). Translocation and association of ROCK-II with RhoA and HSP27 during contraction of rabbit colon smooth muscle cells. Biochemical and Biophysical Research Communications. 319(1). 95–102. 20 indexed citations
19.
Patil, Suresh B., Mercy Pawar, & Khalil N. Bitar. (2004). Direct association and translocation of PKC-α with calponin. American Journal of Physiology-Gastrointestinal and Liver Physiology. 286(6). G954–G963. 21 indexed citations
20.
Patil, Suresh B., Mercy Pawar, & Khalil N. Bitar. (2004). Phosphorylated HSP27 essential for acetylcholine-induced association of RhoA with PKCα. American Journal of Physiology-Gastrointestinal and Liver Physiology. 286(4). G635–G644. 32 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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