Liat Ein‐Dor
Impact in
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
- Breast Cancer Treatment Studies
- Molecular Biology top 10%
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Molecular Biology Techniques and Applications
- Gene Regulatory Network Analysis
Papers in
-
- Natural Language Processing Techniques 9
- Topic Modeling 9
- Neural Networks and Applications 6
- Sentiment Analysis and Opinion Mining 3
- Advanced Text Analysis Techniques 3
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- Statistical Mechanics and Entropy 4
- Co-authors
- Eytan Domany (6 shared papers)Or Zuk (3 shared papers)David Givol (3 shared papers)Itai Kela (2 shared papers)Gad Getz (2 shared papers)Ido Kanter (8 shared papers)Noam Slonim (11 shared papers)Alon Halfon (5 shared papers)
- Journals
- Big Data (1 paper)Bioinformatics (1 paper)Computer applications in the biosciences (1 paper)Breast Cancer Research (1 paper)Europhysics Letters (EPL) (1 paper)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Liat Ein‐Dor
27 papers receiving 1.7k citations
Liat Ein‐Dor's Hit Papers
Peers
Comparison fields: 5 of 129
- Cancer Research 276
- Molecular Biology 1.0k
- Artificial Intelligence 301
- Hematology 71
- Statistics and Probability 50
Countries citing papers authored by Liat Ein‐Dor
This map shows the geographic impact of Liat Ein‐Dor'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 Liat Ein‐Dor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liat Ein‐Dor more than expected).
Fields of papers citing papers by Liat Ein‐Dor
This network shows the impact of papers produced by Liat Ein‐Dor. 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 Liat Ein‐Dor. The network helps show where Liat Ein‐Dor may publish in the future.
Co-authors
The 25 scholars most cited alongside Liat Ein‐Dor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Outcome signature genes in breast cancer: is there a unique set? Hit paper breakdown → | 2004 | 615 |
| 2 | Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer Hit paper breakdown → | 2006 | 533 |
| 3 | 2005 | 116 | |
| 4 | 2006 | 115 | |
| 5 | 2020 | 95 | |
| 6 | 2014 | 64 | |
| 7 | 2022 | 31 | |
| 8 | 2005 | 27 | |
| 9 | 2020 | 26 | |
| 10 | 2001 | 18 | |
| 11 | 2001 | 13 | |
| 12 | 2023 | 13 | |
| 13 | 2019 | 12 | |
| 14 | 2022 | 10 | |
| 15 | 1999 | 10 | |
| 16 | 2007 | 10 | |
| 17 | 2002 | 9 | |
| 18 | 2015 | 8 | |
| 19 | 2001 | 7 | |
| 20 | 2016 | 6 |
About Liat Ein‐Dor
Liat Ein‐Dor is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Networks and Communications, Molecular Biology and Economics and Econometrics, having authored 30 papers that have together received 1.8k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (9 papers), Neural Networks and Applications (6 papers), Statistical Mechanics and Entropy (4 papers), Complex Systems and Time Series Analysis (4 papers), Sentiment Analysis and Opinion Mining (3 papers), Advanced Text Analysis Techniques (3 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Cancer Research (276 citations), Molecular Biology (1.0k citations), Artificial Intelligence (301 citations), Hematology (71 citations) and Statistics and Probability (50 citations). Liat Ein‐Dor has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Eytan Domany, Or Zuk, David Givol, Itai Kela, Gad Getz, Ido Kanter, Noam Slonim, Alon Halfon, Ariel Gera and Dafna Tsafrir. Their work appears in journals such as Big Data, Bioinformatics, Computer applications in the biosciences, Breast Cancer Research and Europhysics Letters (EPL).
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.