Ashwin Unnikrishnan

2.4k total citations
20 papers, 664 citations indexed

About

Ashwin Unnikrishnan is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Ashwin Unnikrishnan has authored 20 papers receiving a total of 664 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Hematology and 3 papers in Genetics. Recurrent topics in Ashwin Unnikrishnan's work include Acute Myeloid Leukemia Research (7 papers), DNA Repair Mechanisms (4 papers) and RNA Research and Splicing (4 papers). Ashwin Unnikrishnan is often cited by papers focused on Acute Myeloid Leukemia Research (7 papers), DNA Repair Mechanisms (4 papers) and RNA Research and Splicing (4 papers). Ashwin Unnikrishnan collaborates with scholars based in Australia, United States and Sweden. Ashwin Unnikrishnan's co-authors include Toshio Tsukiyama, Philip R. Gafken, John E. Pimanda, Julie A.I. Thoms, A. R. Heydari, Arlan Richardson, Jason W.H. Wong, Pramod Koshy, Jia‐Lin Yang and Dominik Beck and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Blood.

In The Last Decade

Ashwin Unnikrishnan

20 papers receiving 660 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashwin Unnikrishnan Australia 14 463 145 67 59 52 20 664
Yvette Y. Yien United States 12 581 1.3× 57 0.4× 38 0.6× 30 0.5× 75 1.4× 18 691
Yi-Hui Lin China 9 867 1.9× 208 1.4× 151 2.3× 39 0.7× 19 0.4× 21 1.0k
Karen Rockwell United States 6 444 1.0× 177 1.2× 41 0.6× 149 2.5× 69 1.3× 7 753
Thomas Kirkegaard‐Sørensen Denmark 4 432 0.9× 62 0.4× 54 0.8× 72 1.2× 129 2.5× 4 650
Pauline J. van der Watt South Africa 14 546 1.2× 32 0.2× 61 0.9× 23 0.4× 24 0.5× 23 682
Melanie Walsh Ireland 6 256 0.6× 61 0.4× 45 0.7× 73 1.2× 53 1.0× 6 421
Yayun Zheng China 8 371 0.8× 121 0.8× 58 0.9× 82 1.4× 18 0.3× 13 486
Valérie Borel United Kingdom 15 1.2k 2.5× 35 0.2× 118 1.8× 71 1.2× 179 3.4× 21 1.3k
Todd D. Westergard United States 7 423 0.9× 76 0.5× 54 0.8× 35 0.6× 9 0.2× 9 478

Countries citing papers authored by Ashwin Unnikrishnan

Since Specialization
Citations

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

Fields of papers citing papers by Ashwin Unnikrishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashwin Unnikrishnan

This figure shows the co-authorship network connecting the top 25 collaborators of Ashwin Unnikrishnan. A scholar is included among the top collaborators of Ashwin Unnikrishnan 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 Ashwin Unnikrishnan. Ashwin Unnikrishnan 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.
2.
Deshpande, Nandan, Shashank Sathe, Govardhan Anande, et al.. (2022). The splicing factor RBM17 drives leukemic stem cell maintenance by evading nonsense-mediated decay of pro-leukemic factors. Nature Communications. 13(1). 3833–3833. 15 indexed citations
3.
Saini, Sunil Kumar, Anne-Mette Bjerregaard, Ashwin Unnikrishnan, et al.. (2022). Neoantigen reactive T cells correlate with the low mutational burden in hematological malignancies. Leukemia. 36(11). 2734–2738. 4 indexed citations
4.
Mehmood, Rashid, Jia‐Lin Yang, Pramod Koshy, et al.. (2022). Anticancer therapeutic effect of cerium-based nanoparticles: known and unknown molecular mechanisms. Biomaterials Science. 10(14). 3671–3694. 36 indexed citations
5.
Yang, Jia‐Lin, et al.. (2022). Inorganic nanoparticle-based advanced cancer therapies: Promising combination strategies. Drug Discovery Today. 27(12). 103386–103386. 47 indexed citations
6.
7.
Khanna, Anchit, Julie A.I. Thoms, Brett W. Stringer, et al.. (2020). Constitutive CHK1 Expression Drives a pSTAT3–CIP2A Circuit that Promotes Glioblastoma Cell Survival and Growth. Molecular Cancer Research. 18(5). 709–722. 15 indexed citations
8.
Kumar, Praveen, Dominik Beck, Roman Galeev, et al.. (2019). HMGA2 promotes long-term engraftment and myeloerythroid differentiation of human hematopoietic stem and progenitor cells. Blood Advances. 3(4). 681–691. 22 indexed citations
9.
Massé, Aline, Samuel Quentin, Ashwin Unnikrishnan, et al.. (2018). Granulomonocytic progenitors are key target cells of azacytidine in higher risk myelodysplastic syndromes and acute myeloid leukemia. Leukemia. 32(8). 1856–1860. 6 indexed citations
10.
Smeets, Monique, Govardhan Anande, Ashwin Unnikrishnan, et al.. (2018). Srsf2 P95H initiates myeloid bias and myelodysplastic/myeloproliferative syndrome from hemopoietic stem cells. Blood. 132(6). 608–621. 39 indexed citations
11.
Sonderegger, Stefan, Loretta Cerruti, Cédric S. Tremblay, et al.. (2018). Small-Molecule Inhibition of PRMT5 Induces Translational Stress and p53 in JAK2V617F Mutant Myeloproliferative Neoplasms. Blood. 132(Supplement 1). 53–53. 2 indexed citations
12.
Unnikrishnan, Ashwin, Russell Pickford, Mark J. Raftery, et al.. (2017). AZA-MS: a novel multiparameter mass spectrometry method to determine the intracellular dynamics of azacitidine therapy in vivo. Leukemia. 32(4). 900–910. 20 indexed citations
13.
Poulos, Rebecca C., Julie A.I. Thoms, Yi Fang Guan, et al.. (2016). Functional Mutations Form at CTCF-Cohesin Binding Sites in Melanoma Due to Uneven Nucleotide Excision Repair across the Motif. Cell Reports. 17(11). 2865–2872. 53 indexed citations
14.
Unnikrishnan, Ashwin, Yi Fang Guan, Yizhou Huang, et al.. (2016). A quantitative proteomics approach identifies ETV6 and IKZF1 as new regulators of anERG-driven transcriptional network. Nucleic Acids Research. 44(22). 10644–10661. 16 indexed citations
15.
Tursky, Melinda L., Dominik Beck, Julie A.I. Thoms, et al.. (2014). Overexpression of ERG in cord blood progenitors promotes expansion and recapitulates molecular signatures of high ERG leukemias. Leukemia. 29(4). 819–827. 17 indexed citations
16.
Beck, Dominik, Julie A.I. Thoms, D. S. Perera, et al.. (2013). Genome-wide analysis of transcriptional regulators in human HSPCs reveals a densely interconnected network of coding and noncoding genes. Blood. 122(14). e12–e22. 103 indexed citations
17.
Beck, Dominik, et al.. (2012). Signal analysis for genome-wide maps of histone modifications measured by ChIP-seq. Bioinformatics. 28(8). 1062–1069. 8 indexed citations
18.
Unnikrishnan, Ashwin, Bungo Akiyoshi, Sue Biggins, & Toshio Tsukiyama. (2011). An Efficient Purification System for Native Minichromosome from Saccharomyces cerevisiae. Methods in molecular biology. 833. 115–123. 18 indexed citations
19.
Unnikrishnan, Ashwin, Philip R. Gafken, & Toshio Tsukiyama. (2010). Dynamic changes in histone acetylation regulate origins of DNA replication. Nature Structural & Molecular Biology. 17(4). 430–437. 149 indexed citations
20.
Heydari, A. R., et al.. (2007). Caloric restriction and genomic stability. Nucleic Acids Research. 35(22). 7485–7496. 85 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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