Srijayaprakash Uppada

797 total citations · 1 hit paper
15 papers, 619 citations indexed

About

Srijayaprakash Uppada is a scholar working on Molecular Biology, Neurology and Virology. According to data from OpenAlex, Srijayaprakash Uppada has authored 15 papers receiving a total of 619 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Neurology and 2 papers in Virology. Recurrent topics in Srijayaprakash Uppada's work include RNA Interference and Gene Delivery (4 papers), Barrier Structure and Function Studies (3 papers) and Wnt/β-catenin signaling in development and cancer (3 papers). Srijayaprakash Uppada is often cited by papers focused on RNA Interference and Gene Delivery (4 papers), Barrier Structure and Function Studies (3 papers) and Wnt/β-catenin signaling in development and cancer (3 papers). Srijayaprakash Uppada collaborates with scholars based in United States, Qatar and India. Srijayaprakash Uppada's co-authors include Hamda A. Al‐Naemi, Iman W. Achkar, Mohammad Haris, Shahab Uddin, Ajaz A. Bhat, Sheema Hashem, Muralitharan Shanmugakonar, Punita Dhawan, Amar B. Singh and Neelu Puri and has published in prestigious journals such as PLoS ONE, Oncogene and Biochemical and Biophysical Research Communications.

In The Last Decade

Srijayaprakash Uppada

15 papers receiving 608 citations

Hit Papers

1 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Tight Junction Proteins and Signaling Pathways in Cancer and Inflammation: A Functional Crosstalk

2019 297 citations Ajaz A. Bhat, Srijayaprakash Uppada et al. Frontiers in Physiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Srijayaprakash Uppada United States	11	376	139	123	96	85	15	619
Shyam Babu Prasad India	10	409 1.1×	214 1.5×	139 1.1×	77 0.8×	46 0.5×	22	714
Keun Jae Ahn South Korea	12	225 0.6×	53 0.4×	49 0.4×	105 1.1×	34 0.4×	29	587
Reza Mirzaei Iran	15	259 0.7×	76 0.5×	251 2.0×	121 1.3×	72 0.8×	37	774
T.W. Liang United States	4	282 0.8×	238 1.7×	81 0.7×	39 0.4×	33 0.4×	5	654
Ulrich Kloz Germany	8	359 1.0×	144 1.0×	105 0.9×	38 0.4×	12 0.1×	13	626
Neal Beeman United States	10	245 0.7×	136 1.0×	102 0.8×	50 0.5×	20 0.2×	10	605
Hao Fang China	11	271 0.7×	32 0.2×	98 0.8×	65 0.7×	38 0.4×	30	616
Guobin Song China	14	318 0.8×	42 0.3×	154 1.3×	172 1.8×	136 1.6×	26	710
Shariq Madha United States	12	559 1.5×	48 0.3×	334 2.7×	104 1.1×	55 0.6×	17	1.0k
Jiahui Ye China	16	403 1.1×	21 0.2×	77 0.6×	241 2.5×	59 0.7×	36	770

Countries citing papers authored by Srijayaprakash Uppada

Since Specialization

Citations

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

Fields of papers citing papers by Srijayaprakash Uppada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Srijayaprakash Uppada

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

All Works

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15 of 15 papers shown

Uppada, Srijayaprakash, et al.. (2023). The expanding role of IAP antagonists for the treatment of head and neck cancer. Cancer Medicine. 12(13). 13958–13965. 12 indexed citations

Uppada, Srijayaprakash, Erin M. Scott, Gladys Y.‐P. Ko, et al.. (2022). Paclitaxel and Urolithin A Prevent Histamine-Induced Neurovascular Breakdown Alike, in an Ex Vivo Rat Eye Model. ACS Chemical Neuroscience. 13(14). 2092–2098. 1 indexed citations

Thakur, Vandana, Kabita Pandey, Arpan Acharya, et al.. (2022). Systems biology analyses reveal enhanced chronic morphine distortion of gut-brain interrelationships in simian human immunodeficiency virus infected rhesus macaques. Frontiers in Neuroscience. 16. 1001544–1001544. 3 indexed citations

Pino, María, Srijayaprakash Uppada, Kabita Pandey, et al.. (2020). Safety and Immunological Evaluation of Interleukin-21 Plus Anti-α4β7 mAb Combination Therapy in Rhesus Macaques. Frontiers in Immunology. 11. 1275–1275. 3 indexed citations

Uppada, Srijayaprakash, et al.. (2020). Modified Papanicolaou staining for oral swab samples stored long term. Biotechnic & Histochemistry. 96(5). 359–363. 1 indexed citations

Bhat, Ajaz A., Srijayaprakash Uppada, Iman W. Achkar, et al.. (2019). Tight Junction Proteins and Signaling Pathways in Cancer and Inflammation: A Functional Crosstalk. Frontiers in Physiology. 9. 1942–1942. 297 indexed citations breakdown →

Gowrikumar, Saiprasad, Rizwan Ahmad, Srijayaprakash Uppada, et al.. (2019). Upregulated claudin-1 expression promotes colitis-associated cancer by promoting β-catenin phosphorylation and activation in Notch/p-AKT-dependent manner. Oncogene. 38(26). 5321–5337. 37 indexed citations

Uppada, Srijayaprakash, Saiprasad Gowrikumar, Rizwan Ahmad, et al.. (2018). MASTL induces Colon Cancer progression and Chemoresistance by promoting Wnt/β-catenin signaling. Molecular Cancer. 17(1). 111–111. 66 indexed citations

Singh, Amar B., Srijayaprakash Uppada, & Punita Dhawan. (2016). Claudin proteins, outside-in signaling, and carcinogenesis. Pflügers Archiv - European Journal of Physiology. 469(1). 69–75. 44 indexed citations

10.

Stone, Amanda, et al.. (2014). T-oligo as an anticancer agent in colorectal cancer. Biochemical and Biophysical Research Communications. 446(2). 596–601. 17 indexed citations

11.

Crees, Zachary, et al.. (2014). Oligonucleotides and G-quadruplex Stabilizers: Targeting Telomeres and Telomerase in Cancer Therapy. Current Pharmaceutical Design. 20(41). 6422–6437. 32 indexed citations

12.

Stone, Amanda, et al.. (2014). Targeting c-Met in melanoma. Cancer Biology & Therapy. 15(9). 1129–1141. 35 indexed citations

13.

Puri, Neelu, et al.. (2013). Novel delivery system for T-oligo using a nanocomplex formed with an alpha helical peptide for melanoma therapy. International Journal of Nanomedicine. 9. 43–43. 19 indexed citations

14.

Puri, Neelu, et al.. (2013). hnRNP C1/C2 and Pur-beta proteins mediate induction of senescence by oligonucleotides homologous to the telomere overhang. OncoTargets and Therapy. 7. 23–23. 11 indexed citations

15.

Jacobs, Ryan J., et al.. (2013). Alternative Signaling Pathways as Potential Therapeutic Targets for Overcoming EGFR and c-Met Inhibitor Resistance in Non-Small Cell Lung Cancer. PLoS ONE. 8(11). e78398–e78398. 41 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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