Ali Faisal
Impact in
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- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
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- Bioinformatics and Genomic Networks 5
- Gene expression and cancer classification 4
- Gene Regulatory Network Analysis 2
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- Bayesian Methods and Mixture Models 2
- Topic Modeling 2
- Co-authors
- Annika Hultén (2 shared papers)Riitta Salmelin (2 shared papers)Tiina Lindh‐Knuutila (2 shared papers)Marijn van Vliet (2 shared papers)Sasa L. Kivisaari (2 shared papers)Samuel Kaski (8 shared papers)Eeva Kettunen (2 shared papers)Ioana Borze (1 shared paper)
- Journals
- BMC Bioinformatics (2 papers)Bioinformatics (2 papers)Genes Chromosomes and Cancer (1 paper)Neurocomputing (1 paper)Nature Communications (1 paper)
- Partner nations
- FinlandUnited KingdomSwitzerland
In The Last Decade
Ali Faisal
13 papers receiving 382 citations
Peers
Comparison fields: 5 of 120
- Cancer Research 80
- Ecological Modeling 17
- Molecular Biology 157
- Artificial Intelligence 55
- Cognitive Neuroscience 33
Countries citing papers authored by Ali Faisal
This map shows the geographic impact of Ali Faisal'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 Ali Faisal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ali Faisal more than expected).
Fields of papers citing papers by Ali Faisal
This network shows the impact of papers produced by Ali Faisal. 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 Ali Faisal. The network helps show where Ali Faisal may publish in the future.
Co-authors
The 25 scholars most cited alongside Ali Faisal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 105 | |
| 2 | 2019 | 93 | |
| 3 | 2009 | 40 | |
| 4 | 2010 | 38 | |
| 5 | 2015 | 23 | |
| 6 | 2021 | 18 | |
| 7 | 2014 | 16 | |
| 8 | 2009 | 16 | |
| 9 | 2012 | 15 | |
| 10 | 2013 | 9 | |
| 11 | 2011 | 9 | |
| 12 | Sparse Nonparametric Topic Model for Transfer Learning | 2012 | 5 |
| 13 | 2013 | 1 | |
| 14 | Systematic Use of Computational Methods Allows Stratifying Treatment Responders in Glioblastoma Multiforme | 2011 | 0 |
About Ali Faisal
Ali Faisal is a scholar working on Molecular Biology, Artificial Intelligence, Social Psychology, Cognitive Neuroscience and Cancer Research, having authored 14 papers that have together received 388 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Gene expression and cancer classification (4 papers), MicroRNA in disease regulation (2 papers), Action Observation and Synchronization (2 papers), Neurobiology of Language and Bilingualism (2 papers), Bayesian Methods and Mixture Models (2 papers), Topic Modeling (2 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Cancer Research (80 citations), Ecological Modeling (17 citations), Molecular Biology (157 citations), Artificial Intelligence (55 citations) and Cognitive Neuroscience (33 citations). Ali Faisal has collaborated with scholars based in Finland, United Kingdom and Switzerland. Frequent co-authors include Annika Hultén, Riitta Salmelin, Tiina Lindh‐Knuutila, Marijn van Vliet, Sasa L. Kivisaari, Samuel Kaski, Eeva Kettunen, Ioana Borze, Kaisa Salmenkivi and Mirva Peltoniemi. Their work appears in journals such as BMC Bioinformatics, Bioinformatics, Genes Chromosomes and Cancer, Neurocomputing and Nature Communications.
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.