Moisès Burset

2.3k citations
15 papers · 1.6k indexed · 1 hit paper · h-index 13

Moisès Burset

15 papers receiving 1.6k citations

Hit Papers

Evaluation of Gene Structure Prediction Programs5171996202620062016100200300400500

Peers

Moisès Burset
Comparison fields: 5 of 96
  • Molecular Biology 1.3k
  • Cancer Research 110
  • Urology 39
  • Immunology and Allergy 32
  • Surgery 230
Replace James Wettenhall with:
James Wettenhall Australia
Hyang‐Sook Yoo South Korea
Miguel Carballo Spain
Jacques Remacle Belgium
A. Gordon Robertson Canada
Simon Knott United States
Chao‐Xing Yuan United States
Simon J. van Heeringen Netherlands
Weimin Liu United States
Shouyuan Zhao China
Moisès Burset relative to James Wettenhall Australia James Wettenhall's profile →
Citations per field
00.5×3.3×
James Wettenhall · 1×
Citations per year

Countries citing papers authored by Moisès Burset

Since Specialization
Citations

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

Fields of papers citing papers by Moisès Burset

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

15 of 15 papers shown
#Work
1 201410
2 201310
3 201326
4 201058
5 200964
6 200829
7 200829
8 200728
9 200721
10 200742
11 200617
12 2001179
13 2000460
14 2000150
15
Evaluation of Gene Structure Prediction Programsbreakdown →
1996517

About Moisès Burset

Moisès Burset is a scholar working on Cancer Research, Immunology and Allergy and Molecular Biology, having authored 15 papers that have together received 1.6k indexed citations. Recurring topics across this work include Bladder and Urothelial Cancer Treatments (7 papers), Molecular Biology Techniques and Applications (5 papers), Urinary and Genital Oncology Studies (4 papers), RNA and protein synthesis mechanisms (3 papers), Machine Learning in Bioinformatics (2 papers), Epigenetics and DNA Methylation (2 papers), Prostate Cancer Treatment and Research (2 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Molecular Biology (1.3k citations), Cancer Research (110 citations) and Urology (39 citations). Moisès Burset has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Roderic Guigó, Lourdes Mengual, Antonio Alcaraz, María J. Ribal, James W. Fickett, Pankaj Agarwal, Josep F. Abril, Elisabet Ars, Humberto Villavicencio and Mercedes Marín‐Aguilera. Their work appears in journals such as European Urology, The Journal of Urology, Nucleic Acids Research, Clinical Cancer Research and Genome Research.

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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