Katya Moniz

3.1k citations
2 papers · 1.2k · 2 hit papers · h-index 2

Impact in

Papers in

    • Clostridium difficile and Clostridium perfringens research 1
    • SARS-CoV-2 detection and testing 1
    • SARS-CoV-2 and COVID-19 Research 1
    • Gut microbiota and health 1

Katya Moniz

2 papers receiving 1.2k citations

Katya Moniz's Hit Papers

An omics-based framework for assessing the health risk of antimicrobial resistance genes 2021 · 569 citations
5690+2+4Years since publication100200300400500

Peers

Katya Moniz
Comparison fields: 5 of 79
  • Molecular Medicine 233
  • Pollution 442
  • Infectious Diseases 607
  • Applied Microbiology and Biotechnology 40
  • General Dentistry 21
Replace Mathilde Poyet with:
Mathilde Poyet United States
Marcos Quintela‐Baluja United Kingdom
Ocean Thakali Japan
Mohan Amarasiri Japan
Goffe Elsinga Netherlands
Bikash Malla Japan
Katerina Papp United States
Bradley W. Schmitz United States
Tatiana Prado Brazil
Inês B. Moura United Kingdom
Katya Moniz relative to Mathilde Poyet United States Mathilde Poyet's profile →
Citations per field
00.5×1.5×
Mathilde Poyet · 1×
Citations per year

Countries citing papers authored by Katya Moniz

Since Specialization
Citations

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

Fields of papers citing papers by Katya Moniz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Katya Moniz, 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 Katya Moniz Line = papers co-authored together Katya Moniz links everyone, so they are left out of the graph.

All Works

2 of 2 papers shown
#Work
1
SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases
Hit paper breakdown →
2020593
2
An omics-based framework for assessing the health risk of antimicrobial resistance genes
Hit paper breakdown →
2021569

About Katya Moniz

Katya Moniz is a scholar working on Infectious Diseases, Molecular Biology, Molecular Medicine, Radiology, Nuclear Medicine and Imaging and Organic Chemistry, having authored 2 papers that have together received 1.2k indexed citations. Recurring topics across this work include Clostridium difficile and Clostridium perfringens research (1 paper), Gut microbiota and health (1 paper), Antibiotic Resistance in Bacteria (1 paper), COVID-19 diagnosis using AI (1 paper), SARS-CoV-2 detection and testing (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Molecular Medicine (233 citations), Pollution (442 citations), Infectious Diseases (607 citations), Applied Microbiology and Biotechnology (40 citations) and General Dentistry (21 citations). Katya Moniz has collaborated with scholars based in United States, Netherlands and Australia. Frequent co-authors include William P. Hanage, Eric J. Alm, Mathilde Poyet, Edward Topp, Tong Zhang, James M. Tiedje, Li-Guan Li, Xiaole Yin, Mathieu Groussin and Michael R. Gillings. Their work appears in journals such as Nature Communications and mSystems.

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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