Mark D.M. Leiserson

16.9k total citations · 2 hit papers
33 papers, 4.6k citations indexed

About

Mark D.M. Leiserson is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Mark D.M. Leiserson has authored 33 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 19 papers in Cancer Research and 10 papers in Genetics. Recurrent topics in Mark D.M. Leiserson's work include Cancer Genomics and Diagnostics (18 papers), Bioinformatics and Genomic Networks (13 papers) and Gene expression and cancer classification (7 papers). Mark D.M. Leiserson is often cited by papers focused on Cancer Genomics and Diagnostics (18 papers), Bioinformatics and Genomic Networks (13 papers) and Gene expression and cancer classification (7 papers). Mark D.M. Leiserson collaborates with scholars based in United States, Israel and South Korea. Mark D.M. Leiserson's co-authors include Benjamin J. Raphael, Fabio Vandin, Michael D. McLellan, Beifang Niu, Li Ding, Matthew A. Wyczalkowski, Michael C. Wendl, Christopher A. Miller, John S. Welch and Matthew J. Walter and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Mark D.M. Leiserson

30 papers receiving 4.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Mutational landscape and significance across 12 major cancer types

2013 3.1k citations Cyriac Kandoth, Michael D. McLellan et al. Nature profile →
Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes

2014 588 citations Mark D.M. Leiserson, Fabio Vandin et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark D.M. Leiserson United States	15	3.1k	1.8k	1.2k	630	534	33	4.6k
Fabio Vandin Italy	18	3.5k 1.1×	2.0k 1.1×	1.2k 1.0×	651 1.0×	604 1.1×	62	5.2k
Sari Ward United Kingdom	5	2.7k 0.9×	1.6k 0.9×	888 0.7×	595 0.9×	591 1.1×	9	3.9k
Jon W. Teague United Kingdom	15	3.1k 1.0×	1.7k 0.9×	1.2k 1.0×	698 1.1×	782 1.5×	24	4.5k
Cyriac Kandoth United States	14	3.4k 1.1×	2.3k 1.2×	1.4k 1.2×	784 1.2×	636 1.2×	27	5.3k
Brad Ozenberger United States	2	3.9k 1.3×	2.2k 1.2×	1.1k 0.9×	900 1.4×	605 1.1×	2	5.6k
Fei Yang China	27	3.0k 1.0×	1.6k 0.9×	1.5k 1.2×	431 0.7×	450 0.8×	108	4.8k
Joshua F. McMichael United States	11	3.3k 1.1×	2.0k 1.1×	1.5k 1.2×	789 1.3×	616 1.2×	16	5.8k
Nikhil Wagle United States	27	2.6k 0.8×	1.3k 0.7×	1.9k 1.6×	1.1k 1.7×	496 0.9×	102	4.7k
Matthew A. Wyczalkowski United States	14	2.4k 0.8×	1.4k 0.8×	1.1k 0.9×	548 0.9×	376 0.7×	23	3.7k
Giovanni Ciriello Switzerland	28	2.9k 0.9×	1.4k 0.8×	1.2k 1.0×	631 1.0×	480 0.9×	54	4.4k

Countries citing papers authored by Mark D.M. Leiserson

Since Specialization

Citations

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

Fields of papers citing papers by Mark D.M. Leiserson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark D.M. Leiserson. 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 Mark D.M. Leiserson. The network helps show where Mark D.M. Leiserson may publish in the future.

Co-authorship network of co-authors of Mark D.M. Leiserson

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

All Works

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20 of 20 papers shown

Robinson, Welles, Joshua K. Stone, Fiorella Schischlik, et al.. (2024). Identification of intracellular bacteria from multiple single-cell RNA-seq platforms using CSI-Microbes. Science Advances. 10(27). eadj7402–eadj7402. 10 indexed citations

Leiserson, Mark D.M., et al.. (2023). A mutation-level covariate model for mutational signatures. PLoS Computational Biology. 19(6). e1011195–e1011195.

Park, Tae Yoon, Mark D.M. Leiserson, Gunnar W. Klau, & Benjamin J. Raphael. (2022). SuperDendrix algorithm integrates genetic dependencies and genomic alterations across pathways and cancer types. Cell Genomics. 2(2). 100099–100099. 2 indexed citations

Sinha, Sanju, Karina Barbosa, Kuoyuan Cheng, et al.. (2021). A systematic genome-wide mapping of oncogenic mutation selection during CRISPR-Cas9 genome editing. Nature Communications. 12(1). 6512–6512. 34 indexed citations

Leiserson, Mark D.M., et al.. (2021). A data-driven approach for constructing mutation categories for mutational signature analysis. PLoS Computational Biology. 17(10). e1009542–e1009542.

Chen, Yuexi, et al.. (2021). A mixture model for signature discovery from sparse mutation data. Genome Medicine. 13(1). 173–173. 7 indexed citations

Kim, Yoo-Ah, Damian Wójtowicz, Welles Robinson, et al.. (2020). Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer. Genome Medicine. 12(1). 52–52. 18 indexed citations

Wójtowicz, Damian, et al.. (2020). A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer. iScience. 23(3). 100900–100900. 5 indexed citations

Wójtowicz, Damian, Xiaoqing Huang, Yoo-Ah Kim, et al.. (2019). Hidden Markov models lead to higher resolution maps of mutation signature activity in cancer. Genome Medicine. 11(1). 49–49. 14 indexed citations

10.

Wójtowicz, Damian, Mark D.M. Leiserson, Roded Sharan, & Teresa M. Przytycka. (2019). DNA Repair Footprint Uncovers Contribution of DNA Repair Mechanism to Mutational Signatures. PubMed. 25. 262–273. 4 indexed citations

11.

Persi, Erez, Yuri I. Wolf, Mark D.M. Leiserson, Eugene V. Koonin, & Eytan Ruppin. (2018). Criticality in tumor evolution and clinical outcome. Proceedings of the National Academy of Sciences. 115(47). E11101–E11110. 19 indexed citations

12.

Leiserson, Mark D.M., Vasilis Syrgkanis, Miroslav Dudı́k, et al.. (2018). A multifactorial model of T cell expansion and durable clinical benefit in response to a PD-L1 inhibitor. PLoS ONE. 13(12). e0208422–e0208422. 14 indexed citations

13.

Senft, Daniela, Mark D.M. Leiserson, Eytan Ruppin, & Ze’ev A. Ronai. (2017). Precision Oncology: The Road Ahead. Trends in Molecular Medicine. 23(10). 874–898. 107 indexed citations

14.

Leiserson, Mark D.M., et al.. (2014). Abstract 5324: Pan-cancer identification of mutated pathways and protein complexes. Cancer Research. 74(19_Supplement). 5324–5324. 15 indexed citations

15.

Leiserson, Mark D.M., Fabio Vandin, Hsin-Ta Wu, et al.. (2014). Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nature Genetics. 47(2). 106–114. 588 indexed citations breakdown →

16.

Kandoth, Cyriac, Michael D. McLellan, Fabio Vandin, et al.. (2013). Mutational landscape and significance across 12 major cancer types. Nature. 502(7471). 333–339. 3134 indexed citations breakdown →

17.

Leiserson, Mark D.M., et al.. (2013). Simultaneous Identification of Multiple Driver Pathways in Cancer. PLoS Computational Biology. 9(5). e1003054–e1003054. 168 indexed citations

18.

Leiserson, Mark D.M., et al.. (2013). Network analysis of GWAS data. Current Opinion in Genetics & Development. 23(6). 602–610. 63 indexed citations

19.

Leiserson, Mark D.M., et al.. (2013). Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data. BMC Bioinformatics. 14(1). 23–23. 3 indexed citations

20.

Leiserson, Mark D.M., et al.. (2011). Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut. Journal of Computational Biology. 18(11). 1399–1409. 6 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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