Juliana Bernardes

551 citations
18 papers · 309 indexed · h-index 10
Topics
Machine Learning in Bioinformatics (8 papers)Genomics and Phylogenetic Studies (6 papers)Protein Structure and Dynamics (4 papers)
Partner nations
FranceBrazilGermany

In The Last Decade

Juliana Bernardes

18 papers receiving 306 citations

Peers

Juliana Bernardes
Comparison fields: 5 of 67
  • Molecular Biology 228
  • Ecology 53
  • Renewable Energy, Sustainability and the Environment 46
  • Plant Science 42
  • Oceanography 34
Replace Alexandre Maes with:
Alexandre Maes France
Gabriel Gelius‐Dietrich Germany
Minli Xu United States
Mitsuteru Nakao Japan
Matej Vesteg Slovakia
Bruno M.C. Martins United Kingdom
Keisuke Motone Japan
Przemysław Gagat Poland
Sanjay K. Khare India
Fernando D. K. Tria Germany
Juliana Bernardes relative to Alexandre Maes France Alexandre Maes's profile →
Citations per field
00.5×1.5×2.3×
Alexandre Maes · 1×
Citations per year

Countries citing papers authored by Juliana Bernardes

Since Specialization
Citations

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

Fields of papers citing papers by Juliana Bernardes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juliana Bernardes

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 3
2 8
3 1
4 5
5 16
6 8
7 13
8 29
9 1
10 5
11 22
12 88
13 14
14 22
15 38
16 7
17 13
18 16

About Juliana Bernardes

Juliana Bernardes is a scholar working on Molecular Biology, Endocrinology and Immunology, having authored 18 papers that have together received 309 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (8 papers), Genomics and Phylogenetic Studies (6 papers) and Protein Structure and Dynamics (4 papers). The work is most often cited by research in Molecular Biology (228 citations), Renewable Energy, Sustainability and the Environment (46 citations) and Oceanography (34 citations). Juliana Bernardes has collaborated with scholars based in France, Brazil and Germany. Frequent co-authors include Alessandra Carbone, Gerson Zaverucha, Carlos E. Pedreira, Catherine Vaquero, Fabio Rocha Jimenez Vieira, Riccardo Vicedomini, Marie J. J. Huysman, Bernard Gentili, Raffaella Raniello and Maurizio Ribera d’Alcalà. Their work appears in journals such as Bioinformatics, PLoS ONE and The Plant 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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