P. K. Vinod

2.6k total citations · 1 hit paper
67 papers, 1.6k citations indexed

About

P. K. Vinod is a scholar working on Molecular Biology, Cell Biology and Artificial Intelligence. According to data from OpenAlex, P. K. Vinod has authored 67 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 15 papers in Cell Biology and 11 papers in Artificial Intelligence. Recurrent topics in P. K. Vinod's work include Microtubule and mitosis dynamics (12 papers), Fungal and yeast genetics research (9 papers) and Gene Regulatory Network Analysis (7 papers). P. K. Vinod is often cited by papers focused on Microtubule and mitosis dynamics (12 papers), Fungal and yeast genetics research (9 papers) and Gene Regulatory Network Analysis (7 papers). P. K. Vinod collaborates with scholars based in India, United Kingdom and Italy. P. K. Vinod's co-authors include U. Deva Priyakumar, Rishal Aggarwal, C. V. Jawahar, Béla Novák, Orsolya Kapuy, Gábor Bánhegyi, K. V. Venkatesh, Raju S. Bapi, Mauro Conti and Akka Zemmari and has published in prestigious journals such as Cell, PLoS ONE and Current Biology.

In The Last Decade

P. K. Vinod

63 papers receiving 1.6k citations

Hit 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.

MolGPT: Molecular Generation Using a Transformer-Decoder Model

2021 282 citations P. K. Vinod, U. Deva Priyakumar et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
P. K. Vinod India	22	754	297	248	230	209	67	1.6k
Rohan Gupta India	19	810 1.1×	69 0.2×	121 0.5×	131 0.6×	352 1.7×	63	2.0k
Xinghua Lu United States	28	1.3k 1.7×	181 0.6×	423 1.7×	114 0.5×	132 0.6×	151	2.4k
Wilson Wen Bin Goh Singapore	23	1.2k 1.6×	117 0.4×	181 0.7×	111 0.5×	93 0.4×	102	2.2k
Mary Qu Yang United States	25	1.9k 2.5×	112 0.4×	269 1.1×	56 0.2×	139 0.7×	120	2.7k
Akira Funahashi Japan	19	2.0k 2.7×	169 0.6×	69 0.3×	94 0.4×	265 1.3×	72	2.9k
Ina Koch Germany	26	2.1k 2.8×	87 0.3×	181 0.7×	92 0.4×	325 1.6×	107	3.3k
José A. Seoane Spain	21	839 1.1×	90 0.3×	123 0.5×	82 0.4×	98 0.5×	55	1.6k
Gary R. Mirams United Kingdom	36	1.7k 2.3×	284 1.0×	51 0.2×	70 0.3×	216 1.0×	96	3.3k
Jörg Menche Austria	24	2.3k 3.0×	110 0.4×	162 0.7×	47 0.2×	759 3.6×	53	3.2k

Countries citing papers authored by P. K. Vinod

Since Specialization

Citations

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

Fields of papers citing papers by P. K. Vinod

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. K. Vinod. 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 P. K. Vinod. The network helps show where P. K. Vinod may publish in the future.

Co-authorship network of co-authors of P. K. Vinod

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Paul, George, et al.. (2025). Screening of oral potentially malignant disorders and oral cancer using deep learning models. Scientific Reports. 15(1). 17949–17949. 1 indexed citations

2.

Vinod, P. K., et al.. (2025). DeepGraphMut: a graph-based deep learning method for cancer prognosis using somatic mutation profile. Briefings in Bioinformatics. 26(4).

3.

Vinod, P. K., et al.. (2025). DroidTTP: Mapping android applications with TTP for Cyber Threat Intelligence. Journal of Information Security and Applications. 93. 104162–104162. 1 indexed citations

4.

Vinod, P. K., et al.. (2024). OSTIS: A novel Organization-Specific Threat Intelligence System. Computers & Security. 145. 103990–103990. 4 indexed citations

5.

Uppin, Megha, et al.. (2024). IPD-Brain: An Indian histopathology dataset for glioma subtype classification. Scientific Data. 11(1). 1403–1403. 3 indexed citations

6.

Shetty, Keerthi, et al.. (2023). Network diffusion-based approach for survival prediction and identification of biomarkers using multi-omics data of papillary renal cell carcinoma. Molecular Genetics and Genomics. 298(4). 871–882. 1 indexed citations

7.

Mukhia, Nirza, et al.. (2023). AI-Assisted Screening of Oral Potentially Malignant Disorders Using Smartphone-Based Photographic Images. Cancers. 15(16). 4120–4120. 25 indexed citations

8.

Vinod, P. K., et al.. (2023). Gene expression signatures of stepwise progression of Hepatocellular Carcinoma. PLoS ONE. 18(12). e0296454–e0296454.

9.

Priyakumar, U. Deva, et al.. (2023). PREHOST: Host prediction of coronaviridae family using machine learning. Heliyon. 9(2). e13646–e13646. 1 indexed citations

10.

Vinod, P. K., et al.. (2022). Model scenarios for cell cycle re-entry in Alzheimer's disease. iScience. 25(7). 104543–104543. 6 indexed citations

11.

Vinod, P. K., et al.. (2022). Systems-level analysis of transcriptome reorganization during liver regeneration. Molecular Omics. 18(4). 315–327. 2 indexed citations

12.

Vinod, P. K., et al.. (2020). Integrative analysis of DNA methylation and gene expression in papillary renal cell carcinoma. Molecular Genetics and Genomics. 295(3). 807–824. 26 indexed citations

13.

Vinod, P. K., et al.. (2019). Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning. Scientific Reports. 9(1). 10509–10509. 156 indexed citations

14.

Vinod, P. K., et al.. (2018). Single-cell transcriptomic analysis of pancreatic islets in health and type 2 diabetes. International Journal of Advances in Engineering Sciences and Applied Mathematics. 11(2). 105–118. 1 indexed citations

15.

Kapuy, Orsolya, et al.. (2018). Computational modelling of meiotic entry and commitment. Scientific Reports. 8(1). 180–180. 4 indexed citations

16.

Vinod, P. K., et al.. (2018). Mathematical modelling of reversible transition between quiescence and proliferation. PLoS ONE. 13(6). e0198420–e0198420. 3 indexed citations

17.

Vinay, Laurent, et al.. (2017). Systems-level organization of non-alcoholic fatty liver disease progression network. Molecular BioSystems. 13(9). 1898–1911. 16 indexed citations

18.

Vinod, P. K., et al.. (2012). Interplay of transcriptional and proteolytic regulation in driving robust cell cycle progression. Molecular BioSystems. 8(3). 863–870. 5 indexed citations

19.

Kapuy, Orsolya, P. K. Vinod, József Mandl, & Gábor Bánhegyi. (2012). A cellular stress-directed bistable switch controls the crosstalk between autophagy and apoptosis. Molecular BioSystems. 9(2). 296–306. 45 indexed citations

20.

Vinod, P. K. & K. V. Venkatesh. (2009). Quantification of the effect of amino acids on an integrated mTOR and insulinsignaling pathway. Molecular BioSystems. 5(10). 1163–1173. 25 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.

Explore authors with similar magnitude of impact