Nir Friedman
- Molecular Biology top 0.1%
- Genomics and Chromatin Dynamics 29
- Gene Regulatory Network Analysis 28
- Bioinformatics and Genomic Networks 23
- Gene expression and cancer classification 22
- RNA and protein synthesis mechanisms 19
- RNA Research and Splicing 14
- Artificial Intelligence top 0.05%
- Bayesian Modeling and Causal Inference 51
- Logic, Reasoning, and Knowledge 15
- Biophysics top 0.2%
- Aging top 1%
- Signal Processing top 0.5%
- Co-authors
- Daniel L. KollerMoisés GoldszmidtDan GeigerDaphne KollerAviv RegevDana Pe’erIftach NachmanMichal Linial
- Journals
- Bioinformatics (16 papers)Journal of Computational Biology (7 papers)Proceedings of the National Academy of Sciences (6 papers)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Nir Friedman
202 papers receiving 29.2k citations
Hit Papers
Peers
Comparison fields: 5 of 220
- Molecular Biology 17.5k
- Artificial Intelligence 7.8k
- Biophysics 837
- Aging 241
- Signal Processing 1.2k
Countries citing papers authored by Nir Friedman
This map shows the geographic impact of Nir Friedman'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 Nir Friedman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nir Friedman more than expected).
Fields of papers citing papers by Nir Friedman
This network shows the impact of papers produced by Nir Friedman. 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 Nir Friedman. The network helps show where Nir Friedman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nir Friedman, 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 | 2023 | 10 | |
| 2 | 2022 | 13 | |
| 3 | 2022 | 21 | |
| 4 | 2021 | 9 | |
| 5 | 2020 | 28 | |
| 6 | 2017 | 18 | |
| 7 | Chromatin state dynamics during blood formationbreakdown → | 2014 | 556 |
| 8 | High-Resolution View of the Yeast Meiotic Program Revealed by Ribosome Profiling | 2011 | 6 |
| 9 | 2010 | 16 | |
| 10 | Comprehensive comparative analysis of strand-specific RNA sequencing methods | 2010 | 1 |
| 11 | 2007 | 435 | |
| 12 | Learning Hidden Variable Networks: The Information Bottleneck Approach | 2005 | 44 |
| 13 | Learning probabilistic models of link structure | 2003 | 142 |
| 14 | 2002 | 47 | |
| 15 | Likelihood computations using value abstraction | 2000 | 12 |
| 16 | Discovering the hidden structure of complex dynamic systems | 1999 | 41 |
| 17 | Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting | 1998 | 52 |
| 18 | Learning Belief Networks in the Presence of Missing Values and Hidden Variables | 1997 | 231 |
| 19 | Challenge: what is the impact of Bayesian networks on learning? | 1997 | 16 |
| 20 | Conditional logics of belief change | 1994 | 11 |
About Nir Friedman
Nir Friedman is a scholar working on Artificial Intelligence, Molecular Biology and Signal Processing, having authored 210 papers that have together received 30.5k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (51 papers), Genomics and Chromatin Dynamics (29 papers), Gene Regulatory Network Analysis (28 papers), Bioinformatics and Genomic Networks (23 papers), Gene expression and cancer classification (22 papers), RNA and protein synthesis mechanisms (19 papers), Logic, Reasoning, and Knowledge (15 papers) and RNA Research and Splicing (14 papers). The work is most often cited by research in Molecular Biology (17.5k citations), Artificial Intelligence (7.8k citations) and Biophysics (837 citations). Nir Friedman has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Daniel L. Koller, Moisés Goldszmidt, Dan Geiger, Daphne Koller, Aviv Regev, Dana Pe’er, Iftach Nachman, Michal Linial, Long Cai and Eran Segal. Their work appears in journals such as Bioinformatics, Journal of Computational Biology, Proceedings of the National Academy of Sciences, Nature and PLoS Biology.
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.