Maya Kansara

63 total papers · 2.8k total citations
30 papers, 2.1k citations indexed

About

Maya Kansara is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Maya Kansara has authored 30 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 14 papers in Oncology and 14 papers in Cancer Research. Recurrent topics in Maya Kansara's work include Cancer Genomics and Diagnostics (9 papers), Cancer-related Molecular Pathways (7 papers) and Epigenetics and DNA Methylation (4 papers). Maya Kansara is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Cancer-related Molecular Pathways (7 papers) and Epigenetics and DNA Methylation (4 papers). Maya Kansara collaborates with scholars based in Australia, United States and New Zealand. Maya Kansara's co-authors include David M. Thomas, Mark J. Smyth, Michele W.L. Teng, Michael V. Berridge, Peter Choong, Melanie Trivett, John Slavin, Paul J. Simmons, Nuzhat Ahmed and Carleen Cullinane and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Maya Kansara

28 papers receiving 2.1k citations

Hit Papers

Translational biology of ... 2014 2026 2018 2022 2014 2024 250 500 750

Author Peers

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

Author Last Decade Papers Cites
Maya Kansara 1.3k 627 572 569 227 30 2.1k
Jacson Shen 974 0.7× 521 0.8× 683 1.2× 614 1.1× 205 0.9× 52 2.0k
David J. Shields 1.7k 1.3× 632 1.0× 643 1.1× 351 0.6× 313 1.4× 44 3.2k
Kiyoko Yoshioka 1.6k 1.2× 339 0.5× 692 1.2× 313 0.6× 165 0.7× 38 2.4k
Bo Shen 1.4k 1.0× 716 1.1× 451 0.8× 517 0.9× 484 2.1× 35 2.7k
Truong D. Dang 886 0.7× 381 0.6× 512 0.9× 713 1.3× 187 0.8× 19 1.8k
Pierrick G.J. Fournier 1.1k 0.8× 415 0.7× 1.7k 3.0× 495 0.9× 179 0.8× 36 2.8k
Michela Pasello 861 0.7× 341 0.5× 473 0.8× 433 0.8× 145 0.6× 45 1.7k
Martin Gr 1.1k 0.9× 624 1.0× 713 1.2× 179 0.3× 206 0.9× 21 2.4k
Maarten van Dinther 1.6k 1.2× 288 0.5× 517 0.9× 393 0.7× 108 0.5× 43 2.3k
Michael S. Isakoff 944 0.7× 527 0.8× 580 1.0× 714 1.3× 173 0.8× 35 2.2k

Countries citing papers authored by Maya Kansara

Since Specialization
Citations

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

Fields of papers citing papers by Maya Kansara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Kansara

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

All Works

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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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