William J. Blake

6.1k total citations · 2 hit papers
17 papers, 4.3k citations indexed

About

William J. Blake is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, William J. Blake has authored 17 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Genetics and 1 paper in Infectious Diseases. Recurrent topics in William J. Blake's work include Gene Regulatory Network Analysis (6 papers), Bioinformatics and Genomic Networks (6 papers) and CRISPR and Genetic Engineering (4 papers). William J. Blake is often cited by papers focused on Gene Regulatory Network Analysis (6 papers), Bioinformatics and Genomic Networks (6 papers) and CRISPR and Genetic Engineering (4 papers). William J. Blake collaborates with scholars based in United States, Canada and Bangladesh. William J. Blake's 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 and has published in prestigious journals such as Nature, Science and Nucleic Acids Research.

In The Last Decade

William J. Blake

17 papers receiving 4.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Stochasticity in gene expression: from theories to phenotypes

2005 1.7k citations Mads Kærn, Timothy C. Elston et al. Nature Reviews Genetics profile →
Noise in eukaryotic gene expression

2003 1.2k citations William J. Blake, Mads Kærn et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
William J. Blake United States	13	4.0k	1.4k	352	349	261	17	4.3k
Mads Kærn Canada	22	4.0k 1.0×	1.4k 1.0×	362 1.0×	424 1.2×	425 1.6×	46	4.7k
Gábor Balázsi United States	32	3.3k 0.8×	1.1k 0.8×	253 0.7×	234 0.7×	213 0.8×	84	4.1k
Attila Becskei Switzerland	19	2.8k 0.7×	852 0.6×	254 0.7×	178 0.5×	260 1.0×	42	3.1k
Mukund Thattai India	16	3.7k 0.9×	1.5k 1.1×	354 1.0×	292 0.8×	387 1.5×	40	4.1k
Jonathan M. Raser United States	7	2.3k 0.6×	671 0.5×	246 0.7×	158 0.5×	134 0.5×	10	2.7k
Abhyudai Singh United States	32	3.8k 1.0×	1.1k 0.8×	351 1.0×	245 0.7×	299 1.1×	221	4.8k
Ertuğrul M. Özbudak United States	19	2.9k 0.7×	919 0.7×	248 0.7×	176 0.5×	212 0.8×	32	3.3k
Hernán G. García United States	31	3.2k 0.8×	920 0.7×	255 0.7×	164 0.5×	62 0.2×	71	3.7k
Timothy Galitski United States	21	3.2k 0.8×	603 0.4×	111 0.3×	257 0.7×	99 0.4×	33	3.9k
Gürol M. Süel United States	25	3.1k 0.8×	1.1k 0.8×	213 0.6×	513 1.5×	189 0.7×	48	4.2k

Countries citing papers authored by William J. Blake

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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17 of 17 papers shown

Phillips, Elizabeth A., Adam D. Silverman, Michael Liu, et al.. (2023). Detection of viral RNAs at ambient temperature via reporter proteins produced through the target-splinted ligation of DNA probes. Nature Biomedical Engineering. 7(12). 1571–1582. 24 indexed citations

Li, Xiang, et al.. (2023). Real-Time, Multiplexed SHERLOCK for in Vitro Diagnostics. Journal of Molecular Diagnostics. 25(7). 428–437. 12 indexed citations

Khan, Wahab, et al.. (2021). High-Throughput CRISPR–Cas13 SARS-CoV-2 Test. Clinical Chemistry. 68(1). 172–180. 18 indexed citations

Dymond, Jessica S., Sarah M. Richardson, Candice Coombes, et al.. (2011). Synthetic chromosome arms function in yeast and generate phenotypic diversity by design. Nature. 477(7365). 471–476. 327 indexed citations

Blake, William J., et al.. (2010). Pairwise selection assembly for sequence-independent construction of long-length DNA. Nucleic Acids Research. 38(8). 2594–2602. 34 indexed citations

Lippow, Shaun M., et al.. (2009). Creation of a type IIS restriction endonuclease with a long recognition sequence. Nucleic Acids Research. 37(9). 3061–3073. 26 indexed citations

Blake, William J., Gábor Balázsi, Michael A. Kohanski, et al.. (2006). Phenotypic Consequences of Promoter-Mediated Transcriptional Noise. Molecular Cell. 24(6). 853–865. 465 indexed citations

Volfson, Dmitri, et al.. (2006). Origins of extrinsic variability in eukaryotic gene expression. Bulletin of the American Physical Society. 77 indexed citations

Volfson, Dmitri, et al.. (2005). Origins of extrinsic variability in eukaryotic gene expression. Nature. 439(7078). 861–864. 219 indexed citations

10.

Kærn, Mads, Timothy C. Elston, William J. Blake, & James J. Collins. (2005). Stochasticity in gene expression: from theories to phenotypes. Nature Reviews Genetics. 6(6). 451–464. 1720 indexed citations breakdown →

11.

Blake, William J. & Farren J. Isaacs. (2004). Synthetic biology evolves. Trends in biotechnology. 22(7). 321–324. 18 indexed citations

12.

Kærn, Mads, William J. Blake, & James J. Collins. (2003). The Engineering of Gene Regulatory Networks. Annual Review of Biomedical Engineering. 5(1). 179–206. 150 indexed citations

13.

Blake, William J., Mads Kærn, Charles R. Cantor, & James J. Collins. (2003). Noise in eukaryotic gene expression. Nature. 422(6932). 633–637. 1214 indexed citations breakdown →

14.

Walker, Ann P., et al.. (1990). Report of the 1989 Asilomar meeting on education in genetic counseling.. PubMed. 46(6). 1223–30. 36 indexed citations

15.

Copeland, Bradley E., et al.. (1967). A Report of the Standards Committee of the College of American Pathologists: National Comprehensive Laboratory Survey 1965, Chemistry Section. American Journal of Clinical Pathology. 48(1). 104–126. 5 indexed citations

16.

Blake, William J.. (1955). Note on the Dating of Terraces in the Lake Melville District, Labrador. Science. 121(3134). 112–112. 3 indexed citations

17.

Blake, William J., et al.. (1954). Multiple Benign Cavernous Angiomas of Spleen, Lungs, and Liver. PubMed. 114(4). 269–276. 2 indexed citations

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.

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