Farren J. Isaacs

11.7k citations
63 papers · 8.2k indexed · 3 hit papers · h-index 38

Farren J. Isaacs

61 papers receiving 8.1k citations

Hit Papers

Engineering an allosteric transcription factor to respon...25320092026201420202505007501000

Peers

Farren J. Isaacs
Comparison fields: 5 of 142
  • Molecular Biology 7.2k
  • Genetics 2.2k
  • Biotechnology 305
  • Biophysics 161
  • Ecology 656
Replace Christopher V. Rao with:
Christopher V. Rao United States
Drew Endy United States
Gianni Cesareni Italy
Arne Elofsson Sweden
Tetsuya Yomo Japan
Julio Collado‐Vides Mexico
Howard M. Salis United States
Harley H. McAdams United States
Sergey Ovchinnikov United States
Rita Casadio Italy
Farren J. Isaacs relative to Christopher V. Rao United States Christopher V. Rao's profile →
Citations per field
00.5×1.5×2.4×
Christopher V. Rao · 1×
Citations per year

Countries citing papers authored by Farren J. Isaacs

Since Specialization
Citations

This map shows the geographic impact of Farren J. Isaacs'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 Farren J. Isaacs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Farren J. Isaacs more than expected).

Fields of papers citing papers by Farren J. Isaacs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Farren J. Isaacs. 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 Farren J. Isaacs. The network helps show where Farren J. Isaacs may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Farren J. Isaacs, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Farren J. Isaacs Line = papers co-authored together Farren J. Isaacs links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202512
3 202226
4 202254
5 202229
6 20224
7 202110
8 202141
9 2021178
10 202164
11 20214
12 201645
13 2016211
14 2015112
15 201594
16
Genomically Recoded Organisms Expand Biological Functionsbreakdown →
2013645
17 2006465
18 2006277
19 2004425
20 2001418

About Farren J. Isaacs

Farren J. Isaacs is a scholar working on Genetics, Molecular Biology and Biophysics, having authored 63 papers that have together received 8.2k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (33 papers), CRISPR and Genetic Engineering (28 papers), Bacterial Genetics and Biotechnology (20 papers), Genomics and Phylogenetic Studies (7 papers), Bacteriophages and microbial interactions (6 papers), Gene Regulatory Network Analysis (6 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Glycosylation and Glycoproteins Research (4 papers). The work is most often cited by research in Molecular Biology (7.2k citations), Genetics (2.2k citations) and Biotechnology (305 citations). Farren J. Isaacs has collaborated with scholars based in United States, Japan and Israel. Frequent co-authors include James J. Collins, George M. Church, Peter A. Carr, Harris H. Wang, Charles R. Cantor, Jeff Hasty, Daniel J. Dwyer, George Xu, Craig R. Forest and Zachary Z. Sun. Their work appears in journals such as Nature, Science and Cell.

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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