William J. Blake
- Molecular Biology top 1%
- Genetics top 1%
- Biophysics top 0.5%
- Biomedical Engineering top 10%
- Statistical and Nonlinear Physics top 2%
- Co-authors
- James J. CollinsMads KærnTimothy C. ElstonCharles R. CantorFarren J. IsaacsGábor BalázsiMichael A. KohanskiKevin Murphy
- Topics
- Gene Regulatory Network Analysis (6 papers)Bioinformatics and Genomic Networks (6 papers)CRISPR and Genetic Engineering (4 papers)
- Cited by
- BiophysicsMolecular BiologyGenetics
- Journals
- NatureScienceNucleic Acids Research
- Partner nations
- United StatesCanadaBangladesh
In The Last Decade
William J. Blake
17 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Molecular Biology 4.0k
- Genetics 1.4k
- Biophysics 352
- Biomedical Engineering 349
- Statistical and Nonlinear Physics 261
Countries citing papers authored by William J. Blake
This map shows the geographic impact of William J. Blake'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 William J. Blake with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William J. Blake more than expected).
Fields of papers citing papers by William J. Blake
This network shows the impact of papers produced by William J. Blake. 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 William J. Blake. The network helps show where William J. Blake may publish in the future.
Co-authorship network of co-authors of William J. Blake
This figure shows the co-authorship network connecting the top 25 collaborators of William J. Blake. A scholar is included among the top collaborators of William J. Blake based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with William J. Blake. William J. Blake is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 24 | |
| 2 | 12 | |
| 3 | 18 | |
| 4 | 327 | |
| 5 | 34 | |
| 6 | 26 | |
| 7 | 465 | |
| 8 | Origins of extrinsic variability in eukaryotic gene expression | 77 |
| 9 | 219 | |
| 10 | Stochasticity in gene expression: from theories to phenotypesbreakdown → | 1720 |
| 11 | 18 | |
| 12 | 150 | |
| 13 | Noise in eukaryotic gene expressionbreakdown → | 1214 |
| 14 | Report of the 1989 Asilomar meeting on education in genetic counseling. | 36 |
| 15 | 5 | |
| 16 | 3 | |
| 17 | 2 |
About William J. Blake
William J. Blake is a scholar working on Molecular Biology, Genetics and Paleontology, having authored 17 papers that have together received 4.3k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (6 papers), Bioinformatics and Genomic Networks (6 papers) and CRISPR and Genetic Engineering (4 papers). The work is most often cited by research in Biophysics (352 citations), Molecular Biology (4.0k citations) and Genetics (1.4k citations). William J. Blake has collaborated with scholars based in United States, Canada and Bangladesh. Frequent co-authors include James J. Collins, Mads Kærn, Timothy C. Elston, Charles R. Cantor, Farren J. Isaacs, Gábor Balázsi, Michael A. Kohanski, Kevin Murphy, David R. Walt and Yina Kuang. Their work appears in journals such as Nature, Science and Nucleic Acids Research.
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.