Swarooparani Vadlamudi

2.2k total citations
15 papers, 714 citations indexed

About

Swarooparani Vadlamudi is a scholar working on Molecular Biology, Genetics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Swarooparani Vadlamudi has authored 15 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Genetics and 3 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Swarooparani Vadlamudi's work include RNA modifications and cancer (6 papers), Genomics and Chromatin Dynamics (6 papers) and RNA Research and Splicing (4 papers). Swarooparani Vadlamudi is often cited by papers focused on RNA modifications and cancer (6 papers), Genomics and Chromatin Dynamics (6 papers) and RNA Research and Splicing (4 papers). Swarooparani Vadlamudi collaborates with scholars based in United States, Finland and Germany. Swarooparani Vadlamudi's co-authors include John H. Gilmore, L. Fredrik Jarskog, Jean M. Lauder, Karen L. Mohlke, Marie P. Fogarty, Maile A. Henson, Adam C. Roberts, Robert M. Hamer, Maren E. Cannon and Kayvon Salimi and has published in prestigious journals such as Diabetes, Genome Research and The American Journal of Human Genetics.

In The Last Decade

Swarooparani Vadlamudi

14 papers receiving 702 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Swarooparani Vadlamudi United States 11 214 180 123 121 120 15 714
Yael Piontkewitz Israel 14 212 1.0× 326 1.8× 199 1.6× 106 0.9× 70 0.6× 18 857
Roman Willi Switzerland 12 134 0.6× 222 1.2× 147 1.2× 117 1.0× 47 0.4× 25 772
Eva Martišová Spain 14 192 0.9× 81 0.5× 138 1.1× 188 1.6× 57 0.5× 23 743
Kayla M. Quinnies United States 9 140 0.7× 234 1.3× 137 1.1× 182 1.5× 62 0.5× 11 868
Alexandra F. Trollope Australia 16 281 1.3× 62 0.3× 156 1.3× 53 0.4× 87 0.7× 24 1.1k
Sijie Tan China 19 267 1.2× 222 1.2× 110 0.9× 78 0.6× 173 1.4× 44 987
Sonia Rehal Canada 15 211 1.0× 152 0.8× 77 0.6× 128 1.1× 87 0.7× 19 917
Rachana Haliyur United States 9 176 0.8× 67 0.4× 91 0.7× 127 1.0× 262 2.2× 17 761
Moogeh Baharnoori Canada 11 75 0.4× 117 0.7× 81 0.7× 37 0.3× 35 0.3× 28 490
Ruopeng Sun China 16 177 0.8× 38 0.2× 55 0.4× 76 0.6× 77 0.6× 49 678

Countries citing papers authored by Swarooparani Vadlamudi

Since Specialization
Citations

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

Fields of papers citing papers by Swarooparani Vadlamudi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swarooparani Vadlamudi

This figure shows the co-authorship network connecting the top 25 collaborators of Swarooparani Vadlamudi. A scholar is included among the top collaborators of Swarooparani Vadlamudi 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 Swarooparani Vadlamudi. Swarooparani Vadlamudi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Perrin, Hannah J., Swarooparani Vadlamudi, Amy S. Etheridge, et al.. (2025). Genetic effects on chromatin accessibility uncover mechanisms of liver gene regulation and quantitative traits. Genome Research. 35(7). 1485–1502.
2.
Parsons, Victoria A., Swarooparani Vadlamudi, Maren E. Cannon, et al.. (2025). TBC1D30 regulates proinsulin and insulin secretion and is the target of a genomic association signal for proinsulin. Diabetologia. 68(6). 1169–1183. 1 indexed citations
3.
Vadlamudi, Swarooparani, et al.. (2024). Liver regulatory mechanisms of noncoding variants at lipid and metabolic trait loci. Human Genetics and Genomics Advances. 5(2). 100275–100275. 5 indexed citations
4.
Brotman, Sarah M., Chelsea K. Raulerson, Swarooparani Vadlamudi, et al.. (2022). Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits. The American Journal of Human Genetics. 109(1). 66–80. 12 indexed citations
5.
Orchard, Peter, Nandini Manickam, Swarooparani Vadlamudi, et al.. (2021). Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Research. 31(12). 2258–2275. 35 indexed citations
6.
Perrin, Hannah J., Swarooparani Vadlamudi, Martin Wabitsch, et al.. (2021). Chromatin accessibility and gene expression during adipocyte differentiation identify context-dependent effects at cardiometabolic GWAS loci. PLoS Genetics. 17(10). e1009865–e1009865. 13 indexed citations
7.
Cannon, Maren E., Kristin L. Young, Hannah J. Perrin, et al.. (2019). Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits. G3 Genes Genomes Genetics. 9(8). 2521–2533. 14 indexed citations
8.
Davis, James P., et al.. (2018). Enhancer deletion and allelic effects define a regulatory molecular mechanism at the VLDLR cholesterol GWAS locus. Human Molecular Genetics. 28(6). 888–895. 6 indexed citations
9.
Lo, Ken Sin, Swarooparani Vadlamudi, Marie P. Fogarty, Karen L. Mohlke, & Guillaume Lettre. (2014). Strategies to fine-map genetic associations with lipid levels by combining epigenomic annotations and liver-specific transcription profiles. Genomics. 104(2). 105–112. 11 indexed citations
10.
Fogarty, Marie P., Maren E. Cannon, Swarooparani Vadlamudi, Kyle J. Gaulton, & Karen L. Mohlke. (2014). Identification of a Regulatory Variant That Binds FOXA1 and FOXA2 at the CDC123/CAMK1D Type 2 Diabetes GWAS Locus. PLoS Genetics. 10(9). e1004633–e1004633. 50 indexed citations
11.
Fogarty, Marie P., Tami M. Panhuis, Swarooparani Vadlamudi, Martin L. Buchkovich, & Karen L. Mohlke. (2013). Allele-Specific Transcriptional Activity at Type 2 Diabetes–Associated Single Nucleotide Polymorphisms in Regions of Pancreatic Islet Open Chromatin at the JAZF1 Locus. Diabetes. 62(5). 1756–1762. 36 indexed citations
12.
Henson, Maile A., Adam C. Roberts, Kayvon Salimi, et al.. (2008). Developmental Regulation of the NMDA Receptor Subunits, NR3A and NR1, in Human Prefrontal Cortex. Cerebral Cortex. 18(11). 2560–2573. 86 indexed citations
13.
Gilmore, John H., L. Fredrik Jarskog, & Swarooparani Vadlamudi. (2004). Maternal poly I:C exposure during pregnancy regulates TNFα, BDNF, and NGF expression in neonatal brain and the maternal–fetal unit of the rat. Journal of Neuroimmunology. 159(1-2). 106–112. 148 indexed citations
14.
Gilmore, John H., L. Fredrik Jarskog, Swarooparani Vadlamudi, & Jean M. Lauder. (2004). Prenatal Infection and Risk for Schizophrenia: IL-1β, IL-6, and TNFα Inhibit Cortical Neuron Dendrite Development. Neuropsychopharmacology. 29(7). 1221–1229. 215 indexed citations
15.
Gilmore, John H., L. Fredrik Jarskog, & Swarooparani Vadlamudi. (2003). Maternal infection regulates BDNF and NGF expression in fetal and neonatal brain and maternal–fetal unit of the rat. Journal of Neuroimmunology. 138(1-2). 49–55. 82 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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