Guillem Rigaill
- Molecular Biology
- Cancer Research top 10%
- Genetics
- Cell Biology top 10%
- Statistics and Probability top 5%
- Co-authors
- Emmanuel BarillotDominique Stoppa‐LyonnetÉlodie ManiéMarc‐Henri SternTatiana PopovaMaryse RomaoGraça RaposoGaëlle Le Dez
- Topics
- Gene expression and cancer classification (8 papers)Statistical Methods and Inference (5 papers)Genomic variations and chromosomal abnormalities (5 papers)
In The Last Decade
Guillem Rigaill
14 papers receiving 616 citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 244
- Cancer Research 175
- Genetics 174
- Cell Biology 122
- Statistics and Probability 75
Countries citing papers authored by Guillem Rigaill
This map shows the geographic impact of Guillem Rigaill'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 Guillem Rigaill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guillem Rigaill more than expected).
Fields of papers citing papers by Guillem Rigaill
This network shows the impact of papers produced by Guillem Rigaill. 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 Guillem Rigaill. The network helps show where Guillem Rigaill may publish in the future.
Co-authorship network of co-authors of Guillem Rigaill
This figure shows the co-authorship network connecting the top 25 collaborators of Guillem Rigaill. A scholar is included among the top collaborators of Guillem Rigaill 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 Guillem Rigaill. Guillem Rigaill is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | Segmentation using Optimal Partitioning and Function Pruning [R package fpop version 2019.08.26] | 1 |
| 4 | 41 | |
| 5 | 52 | |
| 6 | 11 | |
| 7 | 19 | |
| 8 | 14 | |
| 9 | 14 | |
| 10 | 82 | |
| 11 | 35 | |
| 12 | Pruned dynamic programming for optimal multiple change-point detection | 47 |
| 13 | 152 | |
| 14 | 118 | |
| 15 | 44 |
About Guillem Rigaill
Guillem Rigaill is a scholar working on Statistics and Probability, Genetics and Cancer Research, having authored 15 papers that have together received 633 indexed citations. Recurring topics across this work include Gene expression and cancer classification (8 papers), Statistical Methods and Inference (5 papers) and Genomic variations and chromosomal abnormalities (5 papers). The work is most often cited by research in Cancer Research (175 citations), Statistics and Probability (75 citations) and Immunology and Allergy (55 citations). Guillem Rigaill has collaborated with scholars based in France, Mexico and Morocco. Frequent co-authors include Emmanuel Barillot, Dominique Stoppa‐Lyonnet, Élodie Manié, Marc‐Henri Stern, Tatiana Popova, Maryse Romao, Graça Raposo, Gaëlle Le Dez, Guillaume Montagnac and Renaud Poincloux. Their work appears in journals such as PLoS ONE, JNCI Journal of the National Cancer Institute and Cancer 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.