Ali Faisal

533 citations
14 papers · 417 · h-index 11

Impact in

Papers in

    • Gene expression and cancer classification 4
    • Circular RNAs in diseases 2
    • Bioinformatics and Genomic Networks 2
    • Topic Modeling 2
    • Bayesian Methods and Mixture Models 2

Ali Faisal

13 papers receiving 411 citations

Peers

Ali Faisal
Comparison fields: 5 of 116
  • Cancer Research 74
  • Ecological Modeling 19
  • Computational Mathematics 2
  • Molecular Biology 142
  • Cognitive Neuroscience 35
Replace James Bown with:
James Bown United Kingdom
Yunchuan Kong United States
Colleen Kelly United States
Ling Lin China
Avichai Tendler Israel
Daniel Lee United States
Dazhong Liu China
Wen-Yun Yang China
Fritz Lekschas United States
Lei M. Li China
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Citations per field
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Citations per year

Countries citing papers authored by Ali Faisal

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Ali Faisal Line = papers co-authored together Ali Faisal links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2011112
2 201998
3 201045
4 200943
5 201524
6 202118
7 201217
8 200916
9 201416
10 201311
11 201110
12
Sparse Nonparametric Topic Model for Transfer Learning
20126
13 20131
14
Systematic Use of Computational Methods Allows Stratifying Treatment Responders in Glioblastoma Multiforme
20110

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 417 indexed citations. Recurring topics across this work include Gene expression and cancer classification (4 papers), Topic Modeling (2 papers), Neurobiology of Language and Bilingualism (2 papers), Circular RNAs in diseases (2 papers), Bioinformatics and Genomic Networks (2 papers), MicroRNA in disease regulation (2 papers), Bayesian Methods and Mixture Models (2 papers) and Action Observation and Synchronization (2 papers). The work is most often cited by research in Cancer Research (74 citations), Ecological Modeling (19 citations), Computational Mathematics (2 citations), Molecular Biology (142 citations) and Cognitive Neuroscience (35 citations). Ali Faisal has collaborated with scholars based in Finland, United Kingdom and United States. Frequent co-authors include Tiina Lindh‐Knuutila, Samuel Kaski, Annika Hultén, Marijn van Vliet, Sasa L. Kivisaari, Riitta Salmelin, Eeva Kettunen, Leo Lahti, Alvis Brāzma and Nils Gehlenborg. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, Nature Communications, Human Brain Mapping 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.

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