Manu Shivakumar

1.6k total citations
49 papers, 478 citations indexed

About

Manu Shivakumar is a scholar working on Molecular Biology, Genetics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Manu Shivakumar has authored 49 papers receiving a total of 478 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 13 papers in Genetics and 8 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Manu Shivakumar's work include Genetic Associations and Epidemiology (11 papers), Bioinformatics and Genomic Networks (8 papers) and RNA modifications and cancer (6 papers). Manu Shivakumar is often cited by papers focused on Genetic Associations and Epidemiology (11 papers), Bioinformatics and Genomic Networks (8 papers) and RNA modifications and cancer (6 papers). Manu Shivakumar collaborates with scholars based in United States, South Korea and India. Manu Shivakumar's co-authors include Dokyoon Kim, Younghee Lee, Sang‐Hyuk Jung, Tullika Garg, Eun Kyung Choe, Kyung-Ah Sohn, Jae‐Seung Yun, Yasser EL‐Manzalawy, Jason E. Miller and Vasant Honavar and has published in prestigious journals such as Nature Communications, Bioinformatics and PLoS ONE.

In The Last Decade

Manu Shivakumar

45 papers receiving 469 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manu Shivakumar United States 12 206 93 74 71 51 49 478
Naijia Liu China 13 146 0.7× 58 0.6× 47 0.6× 34 0.5× 31 0.6× 33 299
Verónica Luzzi United States 12 318 1.5× 50 0.5× 51 0.7× 40 0.6× 50 1.0× 20 621
Kruti P. Maniar United States 15 155 0.8× 47 0.5× 49 0.7× 27 0.4× 116 2.3× 37 686
Giuseppe Miscio Italy 11 201 1.0× 23 0.2× 48 0.6× 34 0.5× 42 0.8× 24 481
Brandon Jew United States 7 221 1.1× 81 0.9× 58 0.8× 31 0.4× 41 0.8× 11 447
Francesca Migheli Italy 13 372 1.8× 121 1.3× 69 0.9× 29 0.4× 39 0.8× 16 664
Matthew Hoffman United States 12 254 1.2× 31 0.3× 140 1.9× 32 0.5× 41 0.8× 22 524
Snježana Kaštelan Croatia 17 148 0.7× 40 0.4× 30 0.4× 26 0.4× 36 0.7× 67 990
Snehal Patil United States 10 310 1.5× 51 0.5× 104 1.4× 14 0.2× 20 0.4× 23 518
Katherine Tian United States 10 218 1.1× 79 0.8× 20 0.3× 60 0.8× 19 0.4× 14 478

Countries citing papers authored by Manu Shivakumar

Since Specialization
Citations

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

Fields of papers citing papers by Manu Shivakumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manu Shivakumar

This figure shows the co-authorship network connecting the top 25 collaborators of Manu Shivakumar. A scholar is included among the top collaborators of Manu Shivakumar 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 Manu Shivakumar. Manu Shivakumar 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.
Jung, Sang‐Hyuk, Manu Shivakumar, Jaeyoung Kim, et al.. (2025). Healthy lifestyle reduces cardiovascular risk in women with genetic predisposition to hypertensive disorders of pregnancy. Nature Communications. 16(1). 1463–1463. 2 indexed citations
2.
Kim, Jaesik, Sang‐Hyuk Jung, Erica Suh, et al.. (2024). Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine. PubMed. 7(1). 225–250. 29 indexed citations
3.
Jung, Sang‐Hyuk, Young Chan Lee, Manu Shivakumar, et al.. (2024). Association between genetic risk and adherence to healthy lifestyle for developing age-related hearing loss. BMC Medicine. 22(1). 141–141. 6 indexed citations
4.
Leiby, Jacob S., et al.. (2024). Deep learning imaging phenotype can classify metabolic syndrome and is predictive of cardiometabolic disorders. Journal of Translational Medicine. 22(1). 434–434. 3 indexed citations
5.
Bae, Jun Ho, Young Mi Jung, Manu Shivakumar, et al.. (2023). EP20.05: Future risk of metabolic syndrome after recurrent spontaneous abortion: a cohort study using UK Biobank. Ultrasound in Obstetrics and Gynecology. 62(S1). 230–230.
6.
Jung, Young Mi, Manu Shivakumar, Chan‐Wook Park, et al.. (2023). Future risk of metabolic syndrome after recurrent pregnancy loss: a cohort study using UK Biobank. Fertility and Sterility. 120(6). 1227–1233. 3 indexed citations
7.
Lee, Seung Mi, Manu Shivakumar, Sang‐Hyuk Jung, et al.. (2023). Genome-wide polygenic risk scores for hypertensive disease during pregnancy can also predict the risk for long-term cardiovascular disease. American Journal of Obstetrics and Gynecology. 229(3). 298.e1–298.e19. 6 indexed citations
8.
Choe, Eun Kyung, Manu Shivakumar, Anurag Verma, et al.. (2022). Leveraging deep phenotyping from health check-up cohort with 10,000 Korean individuals for phenome-wide association study of 136 traits. Scientific Reports. 12(1). 1930–1930. 1 indexed citations
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Shivakumar, Manu, Seonggyun Han, Younghee Lee, & Dokyoon Kim. (2021). Epigenetic interplay between methylation and miRNA in bladder cancer: focus on isoform expression. BMC Genomics. 22(S3). 754–754. 6 indexed citations
12.
Abedi, Vida, Jiang Li, Manu Shivakumar, et al.. (2020). Increasing the Density of Laboratory Measures for Machine Learning Applications. Journal of Clinical Medicine. 10(1). 103–103. 10 indexed citations
13.
Oh, Jong Jin, Manu Shivakumar, Jason E. Miller, et al.. (2019). An exome-wide rare variant analysis of Korean men identifies three novel genes predisposing to prostate cancer. Scientific Reports. 9(1). 17173–17173. 11 indexed citations
14.
Miller, Jason E., Raghu Metpally, Thomas N. Person, et al.. (2019). Systematic characterization of germline variants from the DiscovEHR study endometrial carcinoma population. BMC Medical Genomics. 12(1). 59–59. 1 indexed citations
15.
Kim, Dongwook, Manu Shivakumar, Seonggyun Han, et al.. (2018). Population-dependent Intron Retention and DNA Methylation in Breast Cancer. Molecular Cancer Research. 16(3). 461–469. 25 indexed citations
16.
Miller, Jason E., Manu Shivakumar, Shannon L. Risacher, et al.. (2018). Codon bias among synonymous rare variants is associated with Alzheimer's disease imaging biomarker. IUScholarWorks (Indiana University). 1 indexed citations
17.
Han, Seonggyun, Dongwook Kim, Manu Shivakumar, et al.. (2018). The effects of alternative splicing on miRNA binding sites in bladder cancer. PLoS ONE. 13(1). e0190708–e0190708. 17 indexed citations
18.
EL‐Manzalawy, Yasser, et al.. (2018). Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data. BMC Medical Genomics. 11(S3). 71–71. 46 indexed citations
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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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