Nir Friedman
Impact in
- Molecular Biology top 0.05%
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Genomics and Chromatin Dynamics
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- RNA Research and Splicing
- Artificial Intelligence top 0.05%
- Bayesian Modeling and Causal Inference
Papers in
-
- Genomics and Chromatin Dynamics 31
- Gene Regulatory Network Analysis 27
- Gene expression and cancer classification 22
- Bioinformatics and Genomic Networks 22
- RNA and protein synthesis mechanisms 18
- RNA Research and Splicing 13
-
- Bayesian Modeling and Causal Inference 57
- Logic, Reasoning, and Knowledge 18
- Co-authors
- Daniel L. Koller (1 shared paper)Aviv Regev (25 shared papers)Moisés Goldszmidt (9 shared papers)Daphne Koller (25 shared papers)Dan Geiger (2 shared papers)Dana Pe’er (7 shared papers)Moran Yassour (11 shared papers)Iftach Nachman (9 shared papers)
- Journals
- Bioinformatics (16 papers)Journal of Computational Biology (7 papers)Proceedings of the National Academy of Sciences (6 papers)PLoS Biology (5 papers)Nature (5 papers)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Nir Friedman
214 papers receiving 49.4k citations
Nir Friedman's Hit Papers
Peers
Comparison fields: 5 of 224
- Molecular Biology 25.3k
- Artificial Intelligence 10.2k
- Aging 325
- Genetics 5.0k
- Plant Science 6.3k
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-authors
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
Showing the 20 most-cited of 225 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Full-length transcriptome assembly from RNA-Seq data without a reference genome Hit paper breakdown → | 2011 | 15972 |
| 2 | Probabilistic graphical models : principles and techniques Hit paper breakdown → | 2009 | 4268 |
| 3 | Bayesian Network Classifiers Hit paper breakdown → | 1997 | 3899 |
| 4 | Using Bayesian Networks to Analyze Expression Data Hit paper breakdown → | 2000 | 2411 |
| 5 | Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data Hit paper breakdown → | 2003 | 1260 |
| 6 | Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens Hit paper breakdown → | 2016 | 1103 |
| 7 | Paternally Induced Transgenerational Environmental Reprogramming of Metabolic Gene Expression in Mammals Hit paper breakdown → | 2010 | 920 |
| 8 | Stochastic protein expression in individual cells at the single molecule level Hit paper breakdown → | 2006 | 899 |
| 9 | Inferring Cellular Networks Using Probabilistic Graphical Models Hit paper breakdown → | 2004 | 895 |
| 10 | Learning Probabilistic Relational Models Hit paper breakdown → | 2001 | 713 |
| 11 | Tissue Classification with Gene Expression Profiles Hit paper breakdown → | 2000 | 632 |
| 12 | Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks Hit paper breakdown → | 2003 | 578 |
| 13 | Chromatin state dynamics during blood formation Hit paper breakdown → | 2014 | 574 |
| 14 | Comprehensive comparative analysis of strand-specific RNA sequencing methods Hit paper breakdown → | 2010 | 563 |
| 15 | A module map showing conditional activity of expression modules in cancer Hit paper breakdown → | 2004 | 552 |
| 16 | Mapping Nucleosome Resolution Chromosome Folding in Yeast by Micro-C Hit paper breakdown → | 2015 | 514 |
| 17 | Natural history and evolutionary principles of gene duplication in fungi Hit paper breakdown → | 2007 | 512 |
| 18 | Linking Stochastic Dynamics to Population Distribution: An Analytical Framework of Gene Expression Hit paper breakdown → | 2006 | 507 |
| 19 | 2007 | 443 | |
| 20 | 2011 | 423 |
About Nir Friedman
Nir Friedman is a scholar working on Molecular Biology, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics and Signal Processing, having authored 225 papers that have together received 51.2k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (57 papers), Genomics and Chromatin Dynamics (31 papers), Gene Regulatory Network Analysis (27 papers), Gene expression and cancer classification (22 papers), Bioinformatics and Genomic Networks (22 papers), RNA and protein synthesis mechanisms (18 papers), Logic, Reasoning, and Knowledge (18 papers) and RNA Research and Splicing (13 papers). The work is most often cited by research in Molecular Biology (25.3k citations), Artificial Intelligence (10.2k citations), Aging (325 citations), Genetics (5.0k citations) and Plant Science (6.3k citations). Nir Friedman has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Daniel L. Koller, Aviv Regev, Moisés Goldszmidt, Daphne Koller, Dan Geiger, Dana Pe’er, Moran Yassour, Iftach Nachman, Joshua Z. Levin and Chad Nusbaum. Their work appears in journals such as Bioinformatics, Journal of Computational Biology, Proceedings of the National Academy of Sciences, PLoS Biology and Nature.
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.