Mahmoud Ghandi

28.5k total citations · 2 hit papers
27 papers, 8.9k citations indexed

About

Mahmoud Ghandi is a scholar working on Molecular Biology, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Mahmoud Ghandi has authored 27 papers receiving a total of 8.9k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Oncology and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Mahmoud Ghandi's work include Genomics and Phylogenetic Studies (5 papers), Cancer Mechanisms and Therapy (4 papers) and CAR-T cell therapy research (4 papers). Mahmoud Ghandi is often cited by papers focused on Genomics and Phylogenetic Studies (5 papers), Cancer Mechanisms and Therapy (4 papers) and CAR-T cell therapy research (4 papers). Mahmoud Ghandi collaborates with scholars based in United States, Iran and France. Mahmoud Ghandi's co-authors include Jill P. Mesirov, Arthur Liberzon, Helga Thorvaldsdóttir, Chet Birger, Pablo Tamayo, M Beer, Morteza Mohammad-Noori, Dongwon Lee, Levi A. Garraway and Gregory V. Kryukov and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Mahmoud Ghandi

26 papers receiving 8.9k citations

Hit Papers

The Molecular Signatures Database Hallmark Gene Set Colle... 2015 2026 2018 2022 2015 2020 2.0k 4.0k 6.0k
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.

  1. The Molecular Signatures Database Hallmark Gene Set Collection
    2015 7.1k citations Arthur Liberzon, Chet Birger et al. Cell Systems profile →
  2. Quantitative Proteomics of the Cancer Cell Line Encyclopedia
    2020 574 citations David P. Nusinow, John Szpyt et al. Cell profile →

Peers

Mahmoud Ghandi
Chet Birger United States
Leslie Cope United States
Luis M. Montuenga Spain
Aly Karsan Canada
Dvir Aran Israel
Yataro Daigo Japan
Arthur Liberzon United States
Jen‐Tsan Chi United States
Hui‐Kuan Lin United States
Vladimir Lazar France
Chet Birger United States
Mahmoud Ghandi
Citations per year, relative to Mahmoud Ghandi Mahmoud Ghandi (= 1×) peers Chet Birger

Countries citing papers authored by Mahmoud Ghandi

Since Specialization
Citations

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

Fields of papers citing papers by Mahmoud Ghandi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahmoud Ghandi

This figure shows the co-authorship network connecting the top 25 collaborators of Mahmoud Ghandi. A scholar is included among the top collaborators of Mahmoud Ghandi 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 Mahmoud Ghandi. Mahmoud Ghandi 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.
Weinstein, H, Kevin Hu, Lisa Fish, et al.. (2024). RPL22 is a tumor suppressor in MSI-high cancers and a splicing regulator of MDM4. Cell Reports. 43(8). 114622–114622. 8 indexed citations
2.
Ghandi, Mahmoud, et al.. (2024). Generalized Gapped k-mer Filters for Robust Frequency Estimation. Bulletin of the Iranian Mathematical Society.. 50(5).
3.
Haas, Brian J., Alexander Dobin, Mahmoud Ghandi, et al.. (2023). Targeted in silico characterization of fusion transcripts in tumor and normal tissues via FusionInspector. Cell Reports Methods. 3(5). 100467–100467. 11 indexed citations
4.
Ghandi, Mahmoud, et al.. (2022). A tool for feature extraction from biological sequences. Briefings in Bioinformatics. 23(3). 9 indexed citations
5.
Hu, Kevin, Mahmoud Ghandi, & Franklin W. Huang. (2021). Integrated evaluation of telomerase activation and telomere maintenance across cancer cell lines. eLife. 10. 14 indexed citations
6.
Nusinow, David P., John Szpyt, Mahmoud Ghandi, et al.. (2020). Quantitative Proteomics of the Cancer Cell Line Encyclopedia. Cell. 180(2). 387–402.e16. 574 indexed citations breakdown →
7.
Togami, Katsuhiro, Jason Stephansky, Mahmoud Ghandi, et al.. (2019). DNA methyltransferase inhibition overcomes diphthamide pathway deficiencies underlying CD123-targeted treatment resistance. Journal of Clinical Investigation. 129(11). 5005–5019. 57 indexed citations
8.
Stern, Josh Lewis, Richard D. Paucek, Franklin W. Huang, et al.. (2017). Allele-Specific DNA Methylation and Its Interplay with Repressive Histone Marks at Promoter-Mutant TERT Genes. Cell Reports. 21(13). 3700–3707. 58 indexed citations
9.
Stephansky, Jason, Katsuhiro Togami, Mahmoud Ghandi, et al.. (2017). Resistance to SL-401 in AML and BPDCN Is Associated with Loss of the Diphthamide Synthesis Pathway Enzyme DPH1 and Is Reversible By Azacitidine. Blood. 130(Suppl_1). 797–797. 13 indexed citations
10.
Le, Xiuning, Pedram Razavi, Daniel J. Treacy, et al.. (2016). Systematic Functional Characterization of Resistance to PI3K Inhibition in Breast Cancer. Cancer Discovery. 6(10). 1134–1147. 97 indexed citations
11.
12.
Liberzon, Arthur, Chet Birger, Helga Thorvaldsdóttir, et al.. (2015). The Molecular Signatures Database Hallmark Gene Set Collection. Cell Systems. 1(6). 417–425. 7058 indexed citations breakdown →
13.
Goetz, Eva M., Mahmoud Ghandi, Daniel J. Treacy, Nikhil Wagle, & Levi A. Garraway. (2014). ERK Mutations Confer Resistance to Mitogen-Activated Protein Kinase Pathway Inhibitors. Cancer Research. 74(23). 7079–7089. 80 indexed citations
14.
Ghandi, Mahmoud, Dongwon Lee, Morteza Mohammad-Noori, & M Beer. (2014). Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features. PLoS Computational Biology. 10(7). e1003711–e1003711. 328 indexed citations
15.
Helming, Katherine, Xiaofeng Wang, Boris G. Wilson, et al.. (2014). ARID1B is a specific vulnerability in ARID1A-mutant cancers. Nature Medicine. 20(3). 251–254. 281 indexed citations
16.
Helming, Katherine, Xiaofeng Wang, Boris G. Wilson, et al.. (2014). Abstract LB-126: ARID1B is a specific vulnerability in ARID1A-mutant cancers. Cancer Research. 74(19_Supplement). LB–126. 1 indexed citations
17.
Ghandi, Mahmoud, Morteza Mohammad-Noori, & M Beer. (2013). Robust $$k$$ k -mer frequency estimation using gapped $$k$$ k -mers. Journal of Mathematical Biology. 69(2). 469–500. 34 indexed citations
18.
Ghandi, Mahmoud & M Beer. (2012). Group Normalization for Genomic Data. PLoS ONE. 7(8). e38695–e38695. 4 indexed citations
19.
Jing, Ying, Yueming Qian, Mahmoud Ghandi, et al.. (2011). A mechanistic study on the effect of dexamethasone in moderating cell death in Chinese Hamster Ovary cell cultures. Biotechnology Progress. 28(2). 490–496. 9 indexed citations
20.
Ghandi, Mahmoud, et al.. (2007). Multiple wavelet denoising for embolic signal enhancement. 658–664. 1 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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