Jay T. Goodwin

1.3k total citations
27 papers, 955 citations indexed

About

Jay T. Goodwin is a scholar working on Molecular Biology, Organic Chemistry and Astronomy and Astrophysics. According to data from OpenAlex, Jay T. Goodwin has authored 27 papers receiving a total of 955 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 6 papers in Organic Chemistry and 4 papers in Astronomy and Astrophysics. Recurrent topics in Jay T. Goodwin's work include RNA and protein synthesis mechanisms (8 papers), Protein Structure and Dynamics (5 papers) and DNA and Nucleic Acid Chemistry (5 papers). Jay T. Goodwin is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), Protein Structure and Dynamics (5 papers) and DNA and Nucleic Acid Chemistry (5 papers). Jay T. Goodwin collaborates with scholars based in United States, Germany and Japan. Jay T. Goodwin's co-authors include David G. Lynn, Philip S. Burton, Gary D. Glick, David E. Clark, Robert A. Conradi, Thomas J. Vidmar, Benny Amore, Anil Mehta, Norman F.H. Ho and Richard Cole and has published in prestigious journals such as Journal of the American Chemical Society, Accounts of Chemical Research and Advanced Drug Delivery Reviews.

In The Last Decade

Jay T. Goodwin

27 papers receiving 911 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jay T. Goodwin United States 16 525 215 163 126 120 27 955
Harvey Schwam United States 21 730 1.4× 478 2.2× 68 0.4× 42 0.3× 62 0.5× 31 1.2k
Birgit Claasen Germany 14 390 0.7× 120 0.6× 23 0.1× 86 0.7× 65 0.5× 30 685
Ilona Laczkó Hungary 18 586 1.1× 181 0.8× 19 0.1× 47 0.4× 95 0.8× 42 819
Larry D. Byers United States 20 778 1.5× 552 2.6× 69 0.4× 150 1.2× 140 1.2× 44 1.4k
Yiqin Wu United States 19 1.3k 2.5× 302 1.4× 48 0.3× 222 1.8× 40 0.3× 37 1.6k
Noriyuki Yamaotsu Japan 17 623 1.2× 116 0.5× 252 1.5× 155 1.2× 126 1.1× 51 1.0k
Jacopo Sgrignani Italy 22 611 1.2× 214 1.0× 203 1.2× 228 1.8× 38 0.3× 61 1.2k
Zeno Simon Romania 16 184 0.4× 220 1.0× 246 1.5× 40 0.3× 99 0.8× 66 651
William M. Atkins United States 21 994 1.9× 83 0.4× 216 1.3× 458 3.6× 285 2.4× 43 1.9k
Irene Nobeli United Kingdom 19 1.1k 2.1× 154 0.7× 278 1.7× 77 0.6× 132 1.1× 42 1.5k

Countries citing papers authored by Jay T. Goodwin

Since Specialization
Citations

This map shows the geographic impact of Jay T. Goodwin'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 Jay T. Goodwin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay T. Goodwin more than expected).

Fields of papers citing papers by Jay T. Goodwin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay T. Goodwin. 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 Jay T. Goodwin. The network helps show where Jay T. Goodwin may publish in the future.

Co-authorship network of co-authors of Jay T. Goodwin

This figure shows the co-authorship network connecting the top 25 collaborators of Jay T. Goodwin. A scholar is included among the top collaborators of Jay T. Goodwin 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 Jay T. Goodwin. Jay T. Goodwin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tan, Junjun, Li Zhang, Ming-Chien Hsieh, et al.. (2021). Chemical control of peptide material phase transitions. Chemical Science. 12(8). 3025–3031. 11 indexed citations
2.
Tan, Junjun, Ming-Chien Hsieh, Ting Pan, et al.. (2017). Design of multi-phase dynamic chemical networks. Nature Chemistry. 9(8). 799–804. 64 indexed citations
3.
Taran, Olga, Ming-Chien Hsieh, Jay T. Goodwin, et al.. (2017). Expanding the informational chemistries of life: peptide/RNA networks. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 375(2109). 20160356–20160356. 15 indexed citations
4.
Cleaves, Henderson James, Markus Meringer, & Jay T. Goodwin. (2015). 227 Views of RNA: Is RNA Unique in Its Chemical Isomer Space?. Astrobiology. 15(7). 538–558. 11 indexed citations
5.
Goodwin, Jay T., Anil Mehta, & David G. Lynn. (2012). Digital and Analog Chemical Evolution. Accounts of Chemical Research. 45(12). 2189–2199. 45 indexed citations
6.
Burton, Philip S. & Jay T. Goodwin. (2010). Solubility and Permeability Measurement and Applications in Drug Discovery. Combinatorial Chemistry & High Throughput Screening. 13(2). 101–111. 9 indexed citations
7.
Goodwin, Jay T. & David E. Clark. (2005). In Silico Predictions of Blood-Brain Barrier Penetration: Considerations to “Keep in Mind”. Journal of Pharmacology and Experimental Therapeutics. 315(2). 477–483. 84 indexed citations
8.
Burton, Philip S., Jay T. Goodwin, Thomas J. Vidmar, & Benny Amore. (2002). Predicting Drug Absorption: How Nature Made It a Difficult Problem. Journal of Pharmacology and Experimental Therapeutics. 303(3). 889–895. 67 indexed citations
9.
Goodwin, Jay T., Philip S. Burton, Robert A. Conradi, et al.. (2000). An NMR study of conformations of substituted dipeptides in dodecylphosphocholine micelles: Implications for drug transport. Biopolymers. 53(5). 396–410. 13 indexed citations
10.
Goodwin, Jay T., Robert A. Conradi, Philip S. Burton, B. Mao, & Tom Vidmar. (1999). Strategies toward predicting peptide cellular permeability from computed molecular descriptors. Journal of Peptide Research. 53(4). 355–369. 28 indexed citations
11.
Goodwin, Jay T., et al.. (1999). Probing the Structure of an RNA Tertiary Unfolding Transition State. Journal of the American Chemical Society. 121(32). 7461–7462. 15 indexed citations
12.
Goodwin, Jay T., et al.. (1996). Design, Synthesis, and Analysis of Yeast tRNAPhe Analogs Possessing Intra- and Interhelical Disulfide Cross-Links. Journal of the American Chemical Society. 118(22). 5207–5215. 45 indexed citations
13.
Goodwin, Jay T. & Gary D. Glick. (1994). Synthesis of a disulfide stabilized RNA hairpin. Tetrahedron Letters. 35(11). 1647–1650. 22 indexed citations
14.
Goodwin, Jay T., Scott E. Osborne, Patrick C. Swanson, & Gary D. Glick. (1994). Synthesis of a disulfide cross-linked DNA triple helix. Tetrahedron Letters. 35(26). 4527–4530. 8 indexed citations
15.
Goodwin, Jay T., et al.. (1994). Improved Solid-Phase Synthesis of Long Oligoribonucleotides: Application to tRNAphe and tRNAgly. The Journal of Organic Chemistry. 59(26). 7941–7943. 11 indexed citations
16.
Goodwin, Jay T. & David G. Lynn. (1992). Template-directed synthesis: use of a reversible reaction. Journal of the American Chemical Society. 114(23). 9197–9198. 118 indexed citations
17.
Goodwin, Jay T., et al.. (1989). Characterization of the Fusarium toxin equisetin: the use of phenylboronates in structure assignment. Journal of the American Chemical Society. 111(21). 8223–8231. 77 indexed citations
18.
Goodwin, Jay T., et al.. (1982). The selection of operators of forest harvesting machines in the forestry commission. Ergonomics. 25(1). 73–79. 2 indexed citations
19.
Chappelow, Cecil C., Richard L. Elliott, & Jay T. Goodwin. (1963). Reactions of Chlorodialkoxymethylsilanes with Phenylsodium.. Journal of Chemical & Engineering Data. 8(1). 82–87. 4 indexed citations
20.
Chappelow, Cecil C., Richard L. Elliott, & Jay T. Goodwin. (1962). Synthesis of t-Butylsilicon Compounds by the Wurtz-Fitting Reaction1. The Journal of Organic Chemistry. 27(4). 1409–1414. 8 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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