Cátia Vaz

2.4k citations
11 papers · 1.5k indexed · 1 hit paper · h-index 6

Impact in

Papers in

Cátia Vaz

11 papers receiving 1.5k citations

Hit Papers

GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens 2018 · 636 citations
6362018202620202023200400600

Peers

Cátia Vaz
Comparison fields: 5 of 84
  • Molecular Medicine 394
  • Endocrinology 365
  • Microbiology 186
  • Infectious Diseases 407
  • Food Science 393
Replace Kanako Ishihara with:
Kanako Ishihara Japan
Jorge Rodrigues Portugal
Lourdes Migura‐García Spain
Suk-Chan Jung South Korea
Manal AbuOun United Kingdom
Chiara Francesca Magistrali Italy
M. Concepción Porrero Spain
Mikeljon P. Nikolich United States
Lea Valinsky Israel
Vivian Fussing Denmark
Cátia Vaz relative to Kanako Ishihara Japan Kanako Ishihara's profile →
Citations per field
00.5×3.7×
Kanako Ishihara · 1×
Citations per year

Countries citing papers authored by Cátia Vaz

Since Specialization
Citations

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

Fields of papers citing papers by Cátia Vaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Cátia Vaz, 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 Cátia Vaz Line = papers co-authored together Cátia Vaz links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 20261
2 20241
3
GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens
Hit paper breakdown →
2018636
4 201810
5 20172
6 20171
7 2016126
8 2016317
9 20146
10 20122
11 2012426

About Cátia Vaz

Cátia Vaz is a scholar working on Clinical Biochemistry, Ecological Modeling, Periodontics, Molecular Medicine and Information Systems and Management, having authored 11 papers that have together received 1.5k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), Bacterial Identification and Susceptibility Testing (2 papers), Plant Pathogenic Bacteria Studies (2 papers), Machine Learning in Bioinformatics (2 papers), RNA and protein synthesis mechanisms (2 papers), Oral microbiology and periodontitis research (1 paper), Service-Oriented Architecture and Web Services (1 paper) and Species Distribution and Climate Change (1 paper). The work is most often cited by research in Molecular Medicine (394 citations), Endocrinology (365 citations), Microbiology (186 citations), Infectious Diseases (407 citations) and Food Science (393 citations). Cátia Vaz has collaborated with scholars based in Portugal, Paraguay and United Kingdom. Frequent co-authors include Alexandre P. Francisco, João André Carriço, Mário Ramirez, Mark Achtman, Martin J. Sergeant, Zhemin Zhou, Nabil-Fareed Alikhan, Nina Luhmann, José Melo‐Cristino and Pedro T. Monteiro. Their work appears in journals such as The Journal of Logic and Algebraic Programming, BMC Bioinformatics, Bioinformatics, Genome Research and Algorithms for Molecular Biology.

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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