Annalisa Barla
- Molecular Biology
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Cancer Research
- Neurology top 10%
- Co-authors
- Alessandro VerriFrancesca OdoneSofia MosciLorenzo RosascoMargherita SquillarioCesare FurlanelloGiuseppe JurmanStefano Merler
- Topics
- Gene expression and cancer classification (11 papers)Bioinformatics and Genomic Networks (11 papers)Computational Drug Discovery Methods (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsPLoS ONE
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Annalisa Barla
64 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 143
- Molecular Biology 357
- Computer Vision and Pattern Recognition 248
- Artificial Intelligence 151
- Cancer Research 144
- Neurology 94
Countries citing papers authored by Annalisa Barla
This map shows the geographic impact of Annalisa Barla'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 Annalisa Barla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Annalisa Barla more than expected).
Fields of papers citing papers by Annalisa Barla
This network shows the impact of papers produced by Annalisa Barla. 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 Annalisa Barla. The network helps show where Annalisa Barla may publish in the future.
Co-authorship network of co-authors of Annalisa Barla
This figure shows the co-authorship network connecting the top 25 collaborators of Annalisa Barla. A scholar is included among the top collaborators of Annalisa Barla 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 Annalisa Barla. Annalisa Barla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 9 | |
| 6 | 5 | |
| 7 | 8 | |
| 8 | 3 | |
| 9 | 4 | |
| 10 | 45 | |
| 11 | 22 | |
| 12 | 25 | |
| 13 | Temporal prediction of multiple sclerosis evolution from patient-centered outcomes | 5 |
| 14 | 1 | |
| 15 | 8 | |
| 16 | A dictionary learning based method for aCGH segmentation | 2 |
| 17 | 5 | |
| 18 | 1 | |
| 19 | A method for robust variable selection with significance assessment | 14 |
| 20 | 46 |
About Annalisa Barla
Annalisa Barla is a scholar working on Equine, Aging and Geriatrics and Gerontology, having authored 67 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene expression and cancer classification (11 papers), Bioinformatics and Genomic Networks (11 papers) and Computational Drug Discovery Methods (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (248 citations), Cancer Research (144 citations) and Ophthalmology (79 citations). Annalisa Barla has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Alessandro Verri, Francesca Odone, Sofia Mosci, Lorenzo Rosasco, Margherita Squillario, Cesare Furlanello, Giuseppe Jurman, Stefano Merler, Luigi Varesio and Paolo Fardin. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.
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.