Pushkala Jayaraman

625 total citations
22 papers, 322 citations indexed

About

Pushkala Jayaraman is a scholar working on Molecular Biology, Epidemiology and Nephrology. According to data from OpenAlex, Pushkala Jayaraman has authored 22 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Epidemiology and 3 papers in Nephrology. Recurrent topics in Pushkala Jayaraman's work include Genomics and Phylogenetic Studies (4 papers), Bioinformatics and Genomic Networks (3 papers) and Chronic Kidney Disease and Diabetes (3 papers). Pushkala Jayaraman is often cited by papers focused on Genomics and Phylogenetic Studies (4 papers), Bioinformatics and Genomic Networks (3 papers) and Chronic Kidney Disease and Diabetes (3 papers). Pushkala Jayaraman collaborates with scholars based in United States, India and China. Pushkala Jayaraman's co-authors include Jon Whittle, Jeff De Pons, Marek Tutaj, Mary Shimoyama, G. Thomas Hayman, Girish N. Nadkarni, Victoria Petri, Melinda R. Dwinell, Elizabeth A. Worthey and Rajni Nigam and has published in prestigious journals such as Nature Medicine, Annals of Internal Medicine and Bioinformatics.

In The Last Decade

Pushkala Jayaraman

20 papers receiving 309 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pushkala Jayaraman United States 10 154 56 47 31 24 22 322
Yasha Hasija India 14 220 1.4× 54 1.0× 75 1.6× 43 1.4× 15 0.6× 84 535
Leslie Derr United States 7 330 2.1× 39 0.7× 71 1.5× 20 0.6× 32 1.3× 7 468
R. A. Leo Elworth United States 10 227 1.5× 41 0.7× 38 0.8× 18 0.6× 35 1.5× 17 347
Paweł P. Łabaj Poland 15 413 2.7× 21 0.4× 71 1.5× 50 1.6× 28 1.2× 38 857
Anna Paola Carrieri United Kingdom 9 230 1.5× 41 0.7× 32 0.7× 24 0.8× 43 1.8× 18 382
Advait Balaji United States 8 188 1.2× 40 0.7× 23 0.5× 9 0.3× 17 0.7× 14 307
Juexiao Zhou Saudi Arabia 13 288 1.9× 131 2.3× 33 0.7× 18 0.6× 6 0.3× 25 588
Zhihan Zhou China 6 486 3.2× 80 1.4× 79 1.7× 9 0.3× 23 1.0× 17 609
J. Harry Caufield United States 13 223 1.4× 74 1.3× 37 0.8× 23 0.7× 38 1.6× 31 360
Prashanti Manda United States 9 145 0.9× 79 1.4× 18 0.4× 12 0.4× 8 0.3× 31 276

Countries citing papers authored by Pushkala Jayaraman

Since Specialization
Citations

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

Fields of papers citing papers by Pushkala Jayaraman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pushkala Jayaraman

This figure shows the co-authorship network connecting the top 25 collaborators of Pushkala Jayaraman. A scholar is included among the top collaborators of Pushkala Jayaraman 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 Pushkala Jayaraman. Pushkala Jayaraman 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.
Jiang, Joy, Pushkala Jayaraman, Joshua Lampert, et al.. (2026). ChatGPT Health performance in a structured test of triage recommendations. Nature Medicine.
2.
Jayaraman, Pushkala & Lili Chan. (2025). Differences in Dialysis Survival. Kidney360. 6(7). 1060–1062. 1 indexed citations
3.
Jayaraman, Pushkala, et al.. (2025). Artificial Intelligence in Nephrology: Pioneering Precision with Multimodal Intelligence. Indian Journal of Nephrology. 35(4). 470–479. 1 indexed citations
4.
Jayaraman, Pushkala, Brian Y. Soong, Alexandra S. Reynolds, et al.. (2024). Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension. npj Digital Medicine. 7(1). 233–233. 5 indexed citations
5.
Hu, Taishan, Timothy L. Mosbruger, Pushkala Jayaraman, et al.. (2024). Targeted and complete genomic sequencing of the major histocompatibility complex in haplotypic form of individual heterozygous samples. Genome Research. 34(10). 1500–1513.
6.
Jayaraman, Pushkala, et al.. (2024). A Primer on Reinforcement Learning in Medicine for Clinicians. npj Digital Medicine. 7(1). 337–337. 24 indexed citations
7.
Vaid, Akhil, Mayte Suárez‐Fariñas, Sanjeev Kaul, et al.. (2023). Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings. Annals of Internal Medicine. 176(10). 1358–1369. 23 indexed citations
8.
Oh, Won-Suk, Pushkala Jayaraman, Pranai Tandon, et al.. (2023). A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19. Artificial Intelligence in Medicine. 148. 102750–102750. 1 indexed citations
9.
Jayaraman, Pushkala, Andrew B. Crouse, Girish N. Nadkarni, & Matthew Might. (2023). A Primer in Precision Nephrology: Optimizing Outcomes in Kidney Health and Disease through Data-Driven Medicine. Kidney360. 4(4). e544–e554. 1 indexed citations
10.
Zhang, Zhe, Sunitha Vege, Taishan Hu, et al.. (2021). Accurate long-read sequencing allows assembly of the duplicated RHD and RHCE genes harboring variants relevant to blood transfusion. The American Journal of Human Genetics. 109(1). 180–191. 20 indexed citations
11.
Oh, Won-Suk, Pushkala Jayaraman, Lili Chan, et al.. (2021). OUP accepted manuscript. Journal of the American Medical Informatics Association. 29(3). 489–499. 5 indexed citations
12.
Jayaraman, Pushkala, Timothy L. Mosbruger, Taishan Hu, et al.. (2020). AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies. Bioinformatics. 36(15). 4353–4356. 7 indexed citations
13.
Wu, Chao, Batsal Devkota, Perry Evans, et al.. (2019). Rapid and accurate interpretation of clinical exomes using Phenoxome: a computational phenotype-driven approach. European Journal of Human Genetics. 27(4). 612–620. 10 indexed citations
14.
Guan, Qiaoning, Jorune Balciuniene, Kajia Cao, et al.. (2018). AUDIOME: a tiered exome sequencing–based comprehensive gene panel for the diagnosis of heterogeneous nonsyndromic sensorineural hearing loss. Genetics in Medicine. 20(12). 1600–1608. 27 indexed citations
15.
Petri, Victoria, Pushkala Jayaraman, Marek Tutaj, et al.. (2014). The pathway ontology – updates and applications. Journal of Biomedical Semantics. 5(1). 7–7. 65 indexed citations
16.
Li, Liping, Enguo Chen, Chun Yang, et al.. (2014). Improved rat genome gene prediction by integration of ESTs with RNA-Seq information. Bioinformatics. 31(1). 25–32. 4 indexed citations
17.
Hayman, G. Thomas, Pushkala Jayaraman, Victoria Petri, et al.. (2013). The updated RGD Pathway Portal utilizes increased curation efficiency and provides expanded pathway information. Human Genomics. 7(1). 4–4. 9 indexed citations
18.
Katz, Lee S., Jay C. Humphrey, Andrew B. Conley, et al.. (2011). Neisseria Base: a comparative genomics database for Neisseria meningitidis. Database. 2011. bar035–bar035. 8 indexed citations
19.
Whittle, Jon & Pushkala Jayaraman. (2006). Generating Hierarchical State Machines from Use Case Charts. 19–28. 29 indexed citations
20.
Jayaraman, Pushkala, et al.. (1980). Inhibition of the incorporation of [3H]DOPA in Mycobacterium leprae by desoxyfructo-serotonin. Biochemical Pharmacology. 29(18). 2526–2528. 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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