Shubha Anand

2.8k total citations · 2 hit papers
19 papers, 2.0k citations indexed

About

Shubha Anand is a scholar working on Molecular Biology, Genetics and Hematology. According to data from OpenAlex, Shubha Anand has authored 19 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 9 papers in Genetics and 9 papers in Hematology. Recurrent topics in Shubha Anand's work include Chronic Myeloid Leukemia Treatments (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers) and Kruppel-like factors research (5 papers). Shubha Anand is often cited by papers focused on Chronic Myeloid Leukemia Treatments (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers) and Kruppel-like factors research (5 papers). Shubha Anand collaborates with scholars based in United Kingdom, Italy and South Sudan. Shubha Anand's co-authors include Ashok R. Venkitaraman, Sue Penrhyn-Lowe, Tom L. Blundell, Mi-Young Lee, David S. Yu, Thomas Lo, Luca Pellegrini, Dimitar G. Efremov, Óscar R. Burrone and Mikhail Lomonosov and has published in prestigious journals such as Nature, The Journal of Experimental Medicine and Genes & Development.

In The Last Decade

Shubha Anand

19 papers receiving 2.0k citations

Hit Papers

Insights into DNA recombi... 2002 2026 2010 2018 2002 2003 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shubha Anand 1.3k 566 469 464 321 19 2.0k
Marito Araki 2.2k 1.6× 287 0.5× 488 1.0× 304 0.7× 389 1.2× 60 2.6k
Maurizio Di Liberto 1.1k 0.8× 494 0.9× 327 0.7× 275 0.6× 225 0.7× 49 1.8k
Luke F. Peterson 1.7k 1.3× 708 1.3× 240 0.5× 160 0.3× 862 2.7× 66 2.4k
Olivier Rosnet 1.4k 1.0× 440 0.8× 729 1.6× 258 0.6× 1.5k 4.7× 52 2.9k
Max Dobles 1.3k 1.0× 580 1.0× 106 0.2× 923 2.0× 123 0.4× 10 2.9k
Evan Pisick 797 0.6× 427 0.8× 385 0.8× 282 0.6× 620 1.9× 35 1.7k
Douglas C. Saffran 890 0.7× 509 0.9× 1.1k 2.4× 121 0.3× 604 1.9× 33 3.2k
Masao Mizuki 1.2k 0.9× 518 0.9× 478 1.0× 81 0.2× 920 2.9× 47 2.3k
Todd Hembrough 942 0.7× 880 1.6× 232 0.5× 191 0.4× 398 1.2× 71 2.3k
Bradley W. Blaser 816 0.6× 630 1.1× 299 0.6× 134 0.3× 613 1.9× 46 2.1k

Countries citing papers authored by Shubha Anand

Since Specialization
Citations

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

Fields of papers citing papers by Shubha Anand

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shubha Anand

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

All Works

19 of 19 papers shown
1.
Dayimu, Alimu, Lorena Di Lisio, Shubha Anand, et al.. (2023). Clinical and biological markers predictive of treatment response associated with metastatic pancreatic adenocarcinoma. British Journal of Cancer. 128(9). 1672–1680. 5 indexed citations
3.
Caeser, Rebecca, Jie Gao, Nimish Shah, et al.. (2021). Acquired CARD11 Mutation Promotes BCR Independence in Diffuse Large B Cell Lymphoma. JCO Precision Oncology. 5(5). 145–152. 4 indexed citations
4.
Katz‐Summercorn, Annalise, Shubha Anand, Yuanxue Huang, et al.. (2017). Application of a multi‐gene next‐generation sequencing panel to a non‐invasive oesophageal cell‐sampling device to diagnose dysplastic Barrett's oesophagus. The Journal of Pathology Clinical Research. 3(4). 258–267. 8 indexed citations
5.
Kollmann, Karoline, Wolfgang Warsch, Francesca Nice, et al.. (2016). A novel signalling screen demonstrates that CALR mutations activate essential MAPK signalling and facilitate megakaryocyte differentiation. Leukemia. 31(4). 934–944. 43 indexed citations
6.
Anand, Shubha & Brian J.P. Huntly. (2012). Disordered Signaling in Myeloproliferative Neoplasms. Hematology/Oncology Clinics of North America. 26(5). 1017–1035. 5 indexed citations
7.
Anand, Shubha, Emma Gudgin, Peter J. Campbell, et al.. (2011). Increased basal intracellular signaling patterns do not correlate with JAK2 genotype in human myeloproliferative neoplasms. Blood. 118(6). 1610–1621. 37 indexed citations
8.
Anand, Shubha, Philip Beer, Emma Gudgin, et al.. (2011). Effects of the JAK2 mutation on the hematopoietic stem and progenitor compartment in human myeloproliferative neoplasms. Blood. 118(1). 177–181. 51 indexed citations
9.
Boyd, Elaine, Anthony J. Bench, Shubha Anand, et al.. (2010). Clinical utility of routine MPL exon 10 analysis in the diagnosis of essential thrombocythaemia and primary myelofibrosis. British Journal of Haematology. 149(2). 250–257. 82 indexed citations
10.
11.
Li, Juan, Dominik Spensberger, Jong Sook Ahn, et al.. (2010). JAK2 V617F impairs hematopoietic stem cell function in a conditional knock-in mouse model of JAK2 V617F–positive essential thrombocythemia. Blood. 116(9). 1528–1538. 159 indexed citations
12.
Lomonosov, Mikhail, Shubha Anand, Mahesh Sangrithi, R. Davies, & Ashok R. Venkitaraman. (2003). Stabilization of stalled DNA replication forks by the BRCA2 breast cancer susceptibility protein. Genes & Development. 17(24). 3017–3022. 196 indexed citations
13.
Anand, Shubha, Sue Penrhyn-Lowe, & Ashok R. Venkitaraman. (2003). AURORA-A amplification overrides the mitotic spindle assembly checkpoint, inducing resistance to Taxol. Cancer Cell. 3(1). 51–62. 504 indexed citations breakdown →
14.
Pellegrini, Luca, David S. Yu, Thomas Lo, et al.. (2002). Insights into DNA recombination from the structure of a RAD51–BRCA2 complex. Nature. 420(6913). 287–293. 540 indexed citations breakdown →
15.
Ivanovski, Martin, Federico Silvestri, Gabriele Pozzato, et al.. (1998). Somatic Hypermutation, Clonal Diversity, and Preferential Expression of the VH 51p1/VL kv325 Immunoglobulin Gene Combination in Hepatitis C Virus–Associated Immunocytomas. Blood. 91(7). 2433–2442. 21 indexed citations
16.
Ivanovski, Martin, Federico Silvestri, Gabriele Pozzato, et al.. (1998). Somatic Hypermutation, Clonal Diversity, and Preferential Expression of the VH 51p1/VL kv325 Immunoglobulin Gene Combination in Hepatitis C Virus–Associated Immunocytomas. Blood. 91(7). 2433–2442. 212 indexed citations
18.
Batista, Facundo D., Shubha Anand, E. Presani, Dimitar G. Efremov, & Óscar R. Burrone. (1996). The Two Membrane Isoforms of Human IgE Assemble into Functionally Distinct B Cell Antigen Receptors. The Journal of Experimental Medicine. 184(6). 2197–2206. 39 indexed citations
19.
Anand, Shubha, Hemant Verma, Lalit Kumar, & Neeta Singh. (1995). Induction of apoptosis in chronic myelogenous leukemia lymphocytes by hydroxyurea and adriamycin. Cancer Letters. 88(1). 101–105. 26 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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