Swami Narala

552 total citations
9 papers, 434 citations indexed

About

Swami Narala is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Swami Narala has authored 9 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Swami Narala's work include Sarcoma Diagnosis and Treatment (2 papers), Wnt/β-catenin signaling in development and cancer (2 papers) and Cytokine Signaling Pathways and Interactions (2 papers). Swami Narala is often cited by papers focused on Sarcoma Diagnosis and Treatment (2 papers), Wnt/β-catenin signaling in development and cancer (2 papers) and Cytokine Signaling Pathways and Interactions (2 papers). Swami Narala collaborates with scholars based in Canada, United States and Austria. Swami Narala's co-authors include Rama Khokha, Marco A. Di Grappa, Sam D. Molyneux, Yang Shao, Alexander G. Beristain, Aditya Murthy, Juan Carlos Zúñiga‐Pflücker, Richard Allsopp, Irving L. Weissman and Derrick J. Rossi and has published in prestigious journals such as Journal of Clinical Investigation, Immunity and Oncogene.

In The Last Decade

Swami Narala

9 papers receiving 431 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Swami Narala Canada	7	230	162	79	77	55	9	434
Andrea Resovi Italy	10	252 1.1×	86 0.5×	35 0.4×	105 1.4×	12 0.2×	15	462
Ángela Pollán Spain	7	209 0.9×	87 0.5×	42 0.5×	134 1.7×	7 0.1×	8	393
Angela Young United States	8	326 1.4×	203 1.3×	60 0.8×	206 2.7×	8 0.1×	9	613
Rebeca Dieguez‐Gonzalez Spain	11	153 0.7×	99 0.6×	11 0.1×	67 0.9×	35 0.6×	15	509
Aubri Charboneau United States	9	505 2.2×	64 0.4×	34 0.4×	160 2.1×	11 0.2×	11	643
Rute Moura Belgium	5	157 0.7×	57 0.4×	29 0.4×	76 1.0×	9 0.2×	8	352
Yuanheng Ning China	12	727 3.2×	137 0.8×	73 0.9×	76 1.0×	7 0.1×	12	953
Bingyin Shi China	14	389 1.7×	211 1.3×	66 0.8×	171 2.2×	5 0.1×	28	661
Zhao Zhi-quan United States	5	307 1.3×	102 0.6×	226 2.9×	81 1.1×	15 0.3×	7	534
Andrea Roberts United States	4	340 1.5×	132 0.8×	39 0.5×	73 0.9×	5 0.1×	4	504

Countries citing papers authored by Swami Narala

Since Specialization

Citations

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

Fields of papers citing papers by Swami Narala

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swami Narala

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

All Works

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9 of 9 papers shown

Defamie, Virginie, Kazeera Aliar, Foram Vyas, et al.. (2024). Metalloproteinase inhibitors regulate biliary progenitor cells through sDLK1 in organoid models of liver injury. Journal of Clinical Investigation. 135(3). 1 indexed citations

Weiss, Ashley, Kazeera Aliar, Yang Shao, et al.. (2021). Abnormal B-cell development in TIMP-deficient bone marrow. Blood Advances. 5(20). 3960–3974. 4 indexed citations

Tang, Qinglian, Jinchang Lu, Changye Zou, et al.. (2018). CDH4 is a novel determinant of osteosarcoma tumorigenesis and metastasis. Oncogene. 37(27). 3617–3630. 26 indexed citations

Voura, Evelyn B., et al.. (2017). Planarians as models of cadmium-induced neoplasia provide measurable benchmarks for mechanistic studies. Ecotoxicology and Environmental Safety. 142. 544–554. 14 indexed citations

Joshi, Purna A., Paul Waterhouse, Nagarajan Kannan, et al.. (2015). RANK Signaling Amplifies WNT-Responsive Mammary Progenitors through R-SPONDIN1. Stem Cell Reports. 5(1). 31–44. 55 indexed citations

Murthy, Aditya, Yang Shao, Swami Narala, et al.. (2012). Notch Activation by the Metalloproteinase ADAM17 Regulates Myeloproliferation and Atopic Barrier Immunity by Suppressing Epithelial Cytokine Synthesis. Immunity. 36(1). 105–119. 107 indexed citations

Beristain, Alexander G., Swami Narala, Marco A. Di Grappa, & Rama Khokha. (2012). Homotypic RANK signaling differentially regulates proliferation, motility and cell survival in osteosarcoma and mammary epithelial cells. Journal of Cell Science. 125(4). 943–955. 61 indexed citations

Molyneux, Sam D., Marco A. Di Grappa, Alexander G. Beristain, et al.. (2010). Prkar1a is an osteosarcoma tumor suppressor that defines a molecular subclass in mice. Journal of Clinical Investigation. 120(9). 3310–3325. 80 indexed citations

Narala, Swami, Richard Allsopp, Guanglei Zhang, et al.. (2008). SIRT1 Acts as a Nutrient-sensitive Growth Suppressor and Its Loss Is Associated with Increased AMPK and Telomerase Activity. Molecular Biology of the Cell. 19(3). 1210–1219. 86 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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