Matthew T. Maurano

18.6k citations
25 papers · 1.9k indexed · 1 hit paper · h-index 15
    • Genomics and Chromatin Dynamics 17
    • CRISPR and Genetic Engineering 7
    • RNA and protein synthesis mechanisms 6
    • RNA Research and Splicing 5
    • Epigenetics and DNA Methylation 3
    • Cancer-related gene regulation 3
    • RNA Interference and Gene Delivery 2
  • Genetics top 5%
    • Genomic variations and chromosomal abnormalities 2
  • Aging top 10%

Matthew T. Maurano

23 papers receiving 1.9k citations

Hit Papers

BEDOPS: high-performance genomic feature operations6352012202620162021200400600

Peers

Matthew T. Maurano
Comparison fields: 5 of 112
  • Molecular Biology 1.5k
  • Genetics 579
  • Aging 25
  • Cancer Research 186
  • Plant Science 235
Replace Jeff Vierstra with:
Jeff Vierstra United States
Yulia A. Medvedeva Russia
Corinne Grey France
Ho‐Ryun Chung Germany
Petko M. Petkov United States
Egor Prokhortchouk Russia
Brian J. Raney United States
Sean Thomas United States
Yavuz Ariyürek Netherlands
Paul A. Ginno United States
Matthew T. Maurano relative to Jeff Vierstra United States Jeff Vierstra's profile →
Citations per field
00.5×3.5×
Jeff Vierstra · 1×
Citations per year

Countries citing papers authored by Matthew T. Maurano

Since Specialization
Citations

This map shows the geographic impact of Matthew T. Maurano'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 Matthew T. Maurano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew T. Maurano more than expected).

Fields of papers citing papers by Matthew T. Maurano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew T. Maurano. 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 Matthew T. Maurano. The network helps show where Matthew T. Maurano may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Matthew T. Maurano, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew T. Maurano Line = papers co-authored together Matthew T. Maurano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20261
2 202410
3 202433
4 20243
5 202328
6 202226
7 20228
8 20220
9 202228
10 202126
11 202131
12 202118
13 20219
14 20195
15 2015139
16 2015200
17 20152
18 201279
19 201249
20 2012436

About Matthew T. Maurano

Matthew T. Maurano is a scholar working on Molecular Biology, Genetics and Modeling and Simulation, having authored 25 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (17 papers), CRISPR and Genetic Engineering (7 papers), RNA and protein synthesis mechanisms (6 papers), RNA Research and Splicing (5 papers), Epigenetics and DNA Methylation (3 papers), Cancer-related gene regulation (3 papers), RNA Interference and Gene Delivery (2 papers) and Genomic variations and chromosomal abnormalities (2 papers). The work is most often cited by research in Molecular Biology (1.5k citations), Genetics (579 citations) and Aging (25 citations). Matthew T. Maurano has collaborated with scholars based in United States, Belgium and Finland. Frequent co-authors include J Stamatoyannopoulos, Richard Sandstrom, Robert E. Thurman, Jeff Vierstra, Eric Haugen, Kristen Lee, Shane Neph, Rajinder Kaul, Sean Thomas and Richard Humbert. Their work appears in journals such as Nature, Science and Cell.

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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