David C. Butler

1.8k total citations
28 papers, 1.3k citations indexed

About

David C. Butler is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Organic Chemistry. According to data from OpenAlex, David C. Butler has authored 28 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 5 papers in Organic Chemistry. Recurrent topics in David C. Butler's work include Muscle Physiology and Disorders (9 papers), Genetic Neurodegenerative Diseases (6 papers) and Algebraic Geometry and Number Theory (4 papers). David C. Butler is often cited by papers focused on Muscle Physiology and Disorders (9 papers), Genetic Neurodegenerative Diseases (6 papers) and Algebraic Geometry and Number Theory (4 papers). David C. Butler collaborates with scholars based in United States, United Kingdom and India. David C. Butler's co-authors include Anne Messer, Stephen E. Alway, Christopher J. Richards, Howard Alper, Parco M. Siu, Emidio E. Pistilli, Shubhada N. Joshi, Huy V. Nguyen, David L. Williamson and Gregory L. Verdine and has published in prestigious journals such as Nature Biotechnology, PLoS ONE and Journal of Molecular Biology.

In The Last Decade

David C. Butler

26 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David C. Butler United States 18 730 314 167 165 162 28 1.3k
Rebecca L. Maglathlin United States 9 802 1.1× 310 1.0× 92 0.6× 173 1.0× 96 0.6× 11 1.4k
Kuiying Xu United States 19 615 0.8× 137 0.4× 93 0.6× 130 0.8× 152 0.9× 47 1.2k
Helmut Mack Germany 16 533 0.7× 280 0.9× 113 0.7× 329 2.0× 19 0.1× 23 1.1k
Kaspar Zimmermann Switzerland 16 663 0.9× 263 0.8× 51 0.3× 139 0.8× 56 0.3× 24 1.0k
R. Scott Struthers United States 25 933 1.3× 368 1.2× 42 0.3× 225 1.4× 82 0.5× 78 2.0k
Wenchao Qü United States 18 419 0.6× 155 0.5× 239 1.4× 52 0.3× 382 2.4× 60 1.2k
Timothy W. Rhoads United States 13 445 0.6× 189 0.6× 182 1.1× 22 0.1× 108 0.7× 17 783
F. García United States 14 932 1.3× 165 0.5× 152 0.9× 118 0.7× 35 0.2× 33 1.4k
Michael A. Pleiss United States 13 481 0.7× 96 0.3× 208 1.2× 161 1.0× 46 0.3× 24 1.2k
Vijay Gokhale United States 30 2.8k 3.9× 304 1.0× 175 1.0× 107 0.6× 40 0.2× 53 3.3k

Countries citing papers authored by David C. Butler

Since Specialization
Citations

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

Fields of papers citing papers by David C. Butler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David C. Butler. 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 David C. Butler. The network helps show where David C. Butler may publish in the future.

Co-authorship network of co-authors of David C. Butler

This figure shows the co-authorship network connecting the top 25 collaborators of David C. Butler. A scholar is included among the top collaborators of David C. Butler 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 David C. Butler. David C. Butler 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.
2.
Messer, Anne & David C. Butler. (2019). Optimizing intracellular antibodies (intrabodies/nanobodies) to treat neurodegenerative disorders. Neurobiology of Disease. 134. 104619–104619. 63 indexed citations
3.
Mahajan, Sai Pooja, Kevin B. Weyant, David C. Butler, et al.. (2018). Computational affinity maturation of camelid single-domain intrabodies against the nonamyloid component of alpha-synuclein. Scientific Reports. 8(1). 17611–17611. 30 indexed citations
4.
Iwamoto, Naoki, David C. Butler, Nenad Svrzikapa, et al.. (2017). Control of phosphorothioate stereochemistry substantially increases the efficacy of antisense oligonucleotides. Nature Biotechnology. 35(9). 845–851. 263 indexed citations
5.
Haramizu, Satoshi, et al.. (2017). Dietary resveratrol confers apoptotic resistance to oxidative stress in myoblasts. The Journal of Nutritional Biochemistry. 50. 103–115. 45 indexed citations
6.
Butler, David C., Shubhada N. Joshi, Erwin De Genst, et al.. (2016). Bifunctional Anti-Non-Amyloid Component α-Synuclein Nanobodies Are Protective In Situ. PLoS ONE. 11(11). e0165964–e0165964. 56 indexed citations
7.
Genst, Erwin De, Dimitri Y. Chirgadze, Fabrice Klein, et al.. (2015). Structure of a Single-Chain Fv Bound to the 17 N-Terminal Residues of Huntingtin Provides Insights into Pathogenic Amyloid Formation and Suppression. Journal of Molecular Biology. 427(12). 2166–2178. 23 indexed citations
8.
Joshi, Shubhada N., David C. Butler, & Anne Messer. (2012). Fusion to a highly charged proteasomal retargeting sequence increases soluble cytoplasmic expression and efficacy of diverse anti-synuclein intrabodies. mAbs. 4(6). 686–693. 58 indexed citations
9.
Butler, David C., et al.. (2011). Engineered antibody therapies to counteract mutant huntingtin and related toxic intracellular proteins. Progress in Neurobiology. 97(2). 190–204. 50 indexed citations
10.
Butler, David C. & Anne Messer. (2011). Bifunctional Anti-Huntingtin Proteasome-Directed Intrabodies Mediate Efficient Degradation of Mutant Huntingtin Exon 1 Protein Fragments. PLoS ONE. 6(12). e29199–e29199. 69 indexed citations
11.
Messer, Anne, Sandra Lynch, & David C. Butler. (2009). Developing intrabodies for the therapeutic suppression of neurodegenerative pathology. Expert Opinion on Biological Therapy. 9(9). 1189–1197. 25 indexed citations
12.
Butler, David C., Satoshi Haramizu, David L. Williamson, & Stephen E. Alway. (2009). Phospho-Ablated Id2 Is Growth Suppressive and Pro-Apoptotic in Proliferating Myoblasts. PLoS ONE. 4(7). e6302–e6302. 10 indexed citations
13.
Williamson, David L., David C. Butler, & Stephen E. Alway. (2009). AMPK inhibits myoblast differentiation through a PGC-1α-dependent mechanism. American Journal of Physiology-Endocrinology and Metabolism. 297(2). E304–E314. 71 indexed citations
14.
Williamson, David L., David C. Butler, & Stephen E. Alway. (2007). AMPK regulation of proliferation and differentiation in C2C12 culture models. The FASEB Journal. 21(6). 2 indexed citations
15.
Alway, Stephen E., Parco M. Siu, Zsolt Murlasits, & David C. Butler. (2005). Muscle Hypertrophy Models: Applications for Research on Aging. Canadian Journal of Applied Physiology. 30(5). 591–624. 21 indexed citations
16.
Butler, David C. & Indranil Biswas. (2005). ON PRILL'S PROBLEM. Communications in Algebra. 33(1). 323–330.
17.
Siu, Parco M., Emidio E. Pistilli, David C. Butler, & Stephen E. Alway. (2004). Aging influences cellular and molecular responses of apoptosis to skeletal muscle unloading. American Journal of Physiology-Cell Physiology. 288(2). C338–C349. 121 indexed citations
18.
Butler, David C. & Christopher J. Richards. (2002). Synthesis of 1‘-Substituted Derivatives of 1,2,3,4,5-Pentaphenylferrocene. Organometallics. 21(24). 5433–5436. 49 indexed citations
19.
Jones, Geraint, David C. Butler, & Christopher J. Richards. (2000). Planar chiral mimetics. A new approach to ligand design for asymmetric catalysis. Tetrahedron Letters. 41(48). 9351–9354. 17 indexed citations
20.
Butler, David C.. (1999). Global sections and tensor products of line bundles over a curve. Mathematische Zeitschrift. 231(3). 397–407. 5 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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