Ibrahim Emam
Impact in
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- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Biomedical Text Mining and Ontologies
- Genomics and Phylogenetic Studies
- RNA modifications and cancer
- Gene Regulatory Network Analysis
- RNA Research and Splicing
- Molecular Biology Techniques and Applications
Papers in
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- Bioinformatics and Genomic Networks 5
- Gene expression and cancer classification 5
- Biomedical Text Mining and Ontologies 3
- Genetics, Bioinformatics, and Biomedical Research 1
- Molecular Biology Techniques and Applications 1
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- Cloud Computing and Resource Management 1
- Co-authors
- Gabriella Rustici (1 shared paper)Alvis Brāzma (1 shared paper)Ele Holloway (1 shared paper)Misha Kapushesky (1 shared paper)Helen Parkinson (1 shared paper)Eleanor Williams (1 shared paper)James Malone (1 shared paper)Shicai Wang (2 shared papers)
- Journals
- Scientific Data (1 paper)BMC Genomics (1 paper)Nucleic Acids Research (1 paper)PLoS ONE (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United KingdomItalyGermany
In The Last Decade
Ibrahim Emam
7 papers receiving 242 citations
Peers
Comparison fields: 5 of 73
- Molecular Biology 195
- Aging 3
- Information Systems and Management 10
- Health Information Management 6
- Genetics 36
Countries citing papers authored by Ibrahim Emam
This map shows the geographic impact of Ibrahim Emam'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 Ibrahim Emam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ibrahim Emam more than expected).
Fields of papers citing papers by Ibrahim Emam
This network shows the impact of papers produced by Ibrahim Emam. 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 Ibrahim Emam. The network helps show where Ibrahim Emam may publish in the future.
Co-authors
The 25 scholars most cited alongside Ibrahim Emam, 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 | 2009 | 176 | |
| 2 | 2014 | 47 | |
| 3 | 2014 | 16 | |
| 4 | Feature Selection for Cancer Classification: An SVM based Approach | 2012 | 6 |
| 5 | 2019 | 3 | |
| 6 | 2012 | 2 | |
| 7 | 2006 | 2 | |
| 8 | 2018 | 0 |
About Ibrahim Emam
Ibrahim Emam is a scholar working on Molecular Biology, Information Systems, Information Systems and Management, Health Information Management and Artificial Intelligence, having authored 8 papers that have together received 252 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Gene expression and cancer classification (5 papers), Biomedical Text Mining and Ontologies (3 papers), Scientific Computing and Data Management (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Cloud Computing and Resource Management (1 paper), Molecular Biology Techniques and Applications (1 paper) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Molecular Biology (195 citations), Aging (3 citations), Information Systems and Management (10 citations), Health Information Management (6 citations) and Genetics (36 citations). Ibrahim Emam has collaborated with scholars based in United Kingdom, Italy and Germany. Frequent co-authors include Gabriella Rustici, Alvis Brāzma, Ele Holloway, Misha Kapushesky, Helen Parkinson, Eleanor Williams, James Malone, Shicai Wang, Ioannis Pandis and Florian Guitton. Their work appears in journals such as Scientific Data, BMC Genomics, Nucleic Acids Research, PLoS ONE and BMC Bioinformatics.
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.