Deepak Kumar Jha

1.3k total citations · 1 hit paper
18 papers, 885 citations indexed

About

Deepak Kumar Jha is a scholar working on Molecular Biology, Genetics and Neurology. According to data from OpenAlex, Deepak Kumar Jha has authored 18 papers receiving a total of 885 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 2 papers in Genetics and 2 papers in Neurology. Recurrent topics in Deepak Kumar Jha's work include Genomics and Chromatin Dynamics (8 papers), Epigenetics and DNA Methylation (7 papers) and Cancer-related gene regulation (5 papers). Deepak Kumar Jha is often cited by papers focused on Genomics and Chromatin Dynamics (8 papers), Epigenetics and DNA Methylation (7 papers) and Cancer-related gene regulation (5 papers). Deepak Kumar Jha collaborates with scholars based in United States, India and Canada. Deepak Kumar Jha's co-authors include Brian D. Strahl, George Q. Daley, R. Grant Rowe, Edroaldo Lummertz da Rocha, Patricia Sousa, Mohan Malleshaiah, Sergei Doulatov, Areum Han, Erik Serrao and Alan Engelman and has published in prestigious journals such as Nature, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Deepak Kumar Jha

17 papers receiving 879 citations

Hit Papers

Haematopoietic stem and progenitor cells from human pluri... 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Deepak Kumar Jha United States 13 706 173 124 111 95 18 885
Kwok Peng Ng United States 14 552 0.8× 91 0.5× 174 1.4× 106 1.0× 112 1.2× 20 741
Weili Wang China 12 449 0.6× 185 1.1× 154 1.2× 144 1.3× 53 0.6× 25 651
Sean F. Landrette United States 12 441 0.6× 71 0.4× 191 1.5× 76 0.7× 108 1.1× 18 663
Monika Lichtinger United Kingdom 13 485 0.7× 212 1.2× 151 1.2× 292 2.6× 65 0.7× 17 750
Mareike Roth Austria 10 637 0.9× 66 0.4× 190 1.5× 146 1.3× 149 1.6× 16 909
Kurt Jacobs Belgium 9 545 0.8× 56 0.3× 93 0.8× 150 1.4× 144 1.5× 10 788
Jackie Sloane‐Stanley United Kingdom 11 544 0.8× 166 1.0× 153 1.2× 83 0.7× 31 0.3× 15 708
Maurizio Fazio United States 11 433 0.6× 95 0.5× 143 1.2× 54 0.5× 124 1.3× 16 703
Karen E. Brown United States 11 736 1.0× 72 0.4× 89 0.7× 210 1.9× 76 0.8× 16 1.1k
Samanta A. Mariani United States 15 324 0.5× 182 1.1× 155 1.3× 198 1.8× 58 0.6× 31 601

Countries citing papers authored by Deepak Kumar Jha

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Kumar Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deepak Kumar Jha. 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 Deepak Kumar Jha. The network helps show where Deepak Kumar Jha may publish in the future.

Co-authorship network of co-authors of Deepak Kumar Jha

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

All Works

18 of 18 papers shown
1.
Dronamraju, Raghuvar, Michael J. Emanuele, Deepak Kumar Jha, et al.. (2024). Set2 methyltransferase facilitates cell cycle progression by maintaining transcriptional fidelity. UNC Libraries.
2.
Stevens, Scott W., et al.. (2020). Histone H3K36 methylation regulates pre-mRNA splicing in Saccharomyces cerevisiae. UNC Libraries. 1 indexed citations
3.
Rowe, R. Grant, Edroaldo Lummertz da Rocha, Patricia Sousa, et al.. (2019). The developmental stage of the hematopoietic niche regulates lineage in MLL-rearranged leukemia. The Journal of Experimental Medicine. 216(3). 527–538. 24 indexed citations
4.
Rocha, Edroaldo Lummertz da, R. Grant Rowe, Vanessa Lundin, et al.. (2018). Reconstruction of complex single-cell trajectories using CellRouter. Nature Communications. 9(1). 892–892. 63 indexed citations
5.
Vo, Linda T., Melissa A. Kinney, Xin Liu, et al.. (2018). Regulation of embryonic haematopoietic multipotency by EZH1. Nature. 553(7689). 506–510. 61 indexed citations
6.
Jha, Deepak Kumar, George Q. Daley, Benoît Laurent, et al.. (2018). Novel Epigenetic Vulnerabilities for Diffuse Large B-Cell Lymphoma. Blood. 132(Supplement 1). 2600–2600. 1 indexed citations
7.
Sugimura, Ryohichi, Deepak Kumar Jha, Areum Han, et al.. (2017). Haematopoietic stem and progenitor cells from human pluripotent stem cells. Nature. 545(7655). 432–438. 337 indexed citations breakdown →
8.
Dronamraju, Raghuvar, Deepak Kumar Jha, Umut Eser, et al.. (2017). Set2 methyltransferase facilitates cell cycle progression by maintaining transcriptional fidelity. Nucleic Acids Research. 46(3). 1331–1344. 20 indexed citations
9.
Dronamraju, Raghuvar, Srinivas Ramachandran, Deepak Kumar Jha, et al.. (2017). Redundant Functions for Nap1 and Chz1 in H2A.Z Deposition. Scientific Reports. 7(1). 14 indexed citations
10.
Sugimura, Ryohichi, Deepak Kumar Jha, Areum Han, et al.. (2017). Hematopoietic stem/progenitor cell conversion from human pluripotent stem cells. Protocol Exchange. 1 indexed citations
11.
Hacker, Kathryn E., Catherine C. Fahey, Stephen A. Shinsky, et al.. (2016). Structure/Function Analysis of Recurrent Mutations in SETD2 Protein Reveals a Critical and Conserved Role for a SET Domain Residue in Maintaining Protein Stability and Histone H3 Lys-36 Trimethylation. Journal of Biological Chemistry. 291(40). 21283–21295. 54 indexed citations
12.
Domínguez, Daniel, Yi‐Hsuan Tsai, Nicholas C. Gomez, et al.. (2016). A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer. Cell Research. 26(8). 946–962. 63 indexed citations
13.
Sorenson, Matthew, et al.. (2016). Histone H3K36 methylation regulates pre-mRNA splicing inSaccharomyces cerevisiae. RNA Biology. 13(4). 412–426. 39 indexed citations
14.
Shanle, Erin K., Forest H. Andrews, Stephen L. McDaniel, et al.. (2015). Association of Taf14 with acetylated histone H3 directs gene transcription and the DNA damage response. Genes & Development. 29(17). 1795–1800. 68 indexed citations
15.
Chaturvedi, Sujata, et al.. (2014). Intravascular lymphoma: an unusual cause of rapid cognitive decline and the role of brain biopsy. BMJ Case Reports. 2014. bcr2014205835–bcr2014205835. 2 indexed citations
16.
Jha, Deepak Kumar & Brian D. Strahl. (2014). An RNA polymerase II-coupled function for histone H3K36 methylation in checkpoint activation and DSB repair. Nature Communications. 5(1). 3965–3965. 94 indexed citations
17.
Jha, Deepak Kumar, Sophia X. Pfister, Timothy C. Humphrey, & Brian D. Strahl. (2014). SET-ting the stage for DNA repair. Nature Structural & Molecular Biology. 21(8). 655–657. 19 indexed citations
18.
Ojha, Bal Krishna, et al.. (2005). Trans-cranial Doppler in severe head injury: Evaluation of pattern of changes in cerebral blood flow velocity and its impact on outcome. Surgical Neurology. 64(2). 174–179. 24 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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