Hani Neuvirth
Impact in
- Virology top 10%
- HIV Research and Treatment
-
- Computational Drug Discovery Methods
Papers in
-
- Protein Structure and Dynamics 5
- Bioinformatics and Genomic Networks 2
- Gene expression and cancer classification 1
-
- Enzyme Structure and Function 4
- Co-authors
- Gideon Schreiber (5 shared papers)Ran Raz (1 shared paper)Mati Cohen (2 shared papers)Dana Reichmann (2 shared papers)Ofer Rahat (1 shared paper)Michal Rosen‐Zvi (4 shared papers)Ehud Aharoni (5 shared papers)Kay E. Gottschalk (1 shared paper)
- Journals
- Big Data (1 paper)Bioinformatics (1 paper)Genetic Epidemiology (1 paper)Protein Engineering Design and Selection (1 paper)Proteins Structure Function and Bioinformatics (1 paper)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Hani Neuvirth
14 papers receiving 746 citations
Peers
Comparison fields: 5 of 89
- Virology 45
- Computational Theory and Mathematics 158
- Molecular Biology 537
- Health Information Management 19
- Materials Chemistry 161
Countries citing papers authored by Hani Neuvirth
This map shows the geographic impact of Hani Neuvirth'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 Hani Neuvirth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hani Neuvirth more than expected).
Fields of papers citing papers by Hani Neuvirth
This network shows the impact of papers produced by Hani Neuvirth. 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 Hani Neuvirth. The network helps show where Hani Neuvirth may publish in the future.
Co-authors
The 25 scholars most cited alongside Hani Neuvirth, 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 | 2004 | 364 | |
| 2 | 2007 | 164 | |
| 3 | 2008 | 53 | |
| 4 | 2008 | 43 | |
| 5 | 2011 | 39 | |
| 6 | 2008 | 37 | |
| 7 | 2004 | 27 | |
| 8 | 2007 | 18 | |
| 9 | 2016 | 6 | |
| 10 | 2010 | 5 | |
| 11 | 2015 | 5 | |
| 12 | 2011 | 2 | |
| 13 | 2014 | 2 | |
| 14 | The EuResist Approach for Predicting Response to Anti HIV-1 Therapy | 2008 | 1 |
About Hani Neuvirth
Hani Neuvirth is a scholar working on Molecular Biology, Materials Chemistry, Artificial Intelligence, Computational Theory and Mathematics and Statistics and Probability, having authored 14 papers that have together received 766 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Enzyme Structure and Function (4 papers), Statistical Methods in Clinical Trials (3 papers), Computational Drug Discovery Methods (3 papers), Bioinformatics and Genomic Networks (2 papers), Diabetes Management and Research (1 paper), Genomics and Rare Diseases (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Virology (45 citations), Computational Theory and Mathematics (158 citations), Molecular Biology (537 citations), Health Information Management (19 citations) and Materials Chemistry (161 citations). Hani Neuvirth has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Gideon Schreiber, Ran Raz, Mati Cohen, Dana Reichmann, Ofer Rahat, Michal Rosen‐Zvi, Ehud Aharoni, Kay E. Gottschalk, Mattia Prosperi and Francesca Incardona. Their work appears in journals such as Big Data, Bioinformatics, Genetic Epidemiology, Protein Engineering Design and Selection and Proteins Structure Function and 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.