David G. Bear

5.2k total citations · 1 hit paper
36 papers, 2.3k citations indexed

About

David G. Bear is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, David G. Bear has authored 36 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 13 papers in Genetics and 6 papers in Ecology. Recurrent topics in David G. Bear's work include RNA and protein synthesis mechanisms (17 papers), Bacterial Genetics and Biotechnology (13 papers) and Bacteriophages and microbial interactions (6 papers). David G. Bear is often cited by papers focused on RNA and protein synthesis mechanisms (17 papers), Bacterial Genetics and Biotechnology (13 papers) and Bacteriophages and microbial interactions (6 papers). David G. Bear collaborates with scholars based in United States, Germany and Sweden. David G. Bear's co-authors include Peter H. von Hippel, William D. Morgan, James A. McSwiggen, Joseph P. Menetski, S C Kowalczykowski, Jinting Wang, David J. Chen, Robert B. Cary, Scott Peterson and E. Morton Bradbury and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

David G. Bear

36 papers receiving 2.2k citations

Hit Papers

PROTEIN-NUCLEIC ACID INTERACTIONS IN TRANSCRIPTION: A Mol... 1984 2026 1998 2012 1984 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David G. Bear United States 24 1.9k 866 307 134 96 36 2.3k
Heiner Wolfes Germany 24 1.3k 0.7× 448 0.5× 160 0.5× 59 0.4× 82 0.9× 41 1.6k
Edwin M. Southern United Kingdom 26 2.9k 1.6× 560 0.6× 227 0.7× 75 0.6× 71 0.7× 52 3.7k
Ronald H. Hoess United States 24 2.1k 1.1× 603 0.7× 425 1.4× 33 0.2× 93 1.0× 32 2.4k
Mari Gingery United States 27 2.0k 1.1× 476 0.5× 806 2.6× 157 1.2× 274 2.9× 34 3.1k
Junghae Suh United States 25 1.3k 0.7× 670 0.8× 157 0.5× 111 0.8× 124 1.3× 60 2.1k
Eunyong Park United States 21 1.6k 0.9× 619 0.7× 186 0.6× 106 0.8× 112 1.2× 31 2.0k
Justin C. Deme United Kingdom 21 831 0.4× 453 0.5× 217 0.7× 103 0.8× 59 0.6× 40 1.3k
Kakoli Mitra United States 9 1.2k 0.6× 295 0.3× 132 0.4× 54 0.4× 255 2.7× 10 1.5k
Erwin De Genst United Kingdom 26 1.8k 1.0× 226 0.3× 243 0.8× 174 1.3× 132 1.4× 41 3.0k
Hanspeter Michel United States 16 1.1k 0.6× 161 0.2× 163 0.5× 83 0.6× 68 0.7× 24 2.0k

Countries citing papers authored by David G. Bear

Since Specialization
Citations

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

Fields of papers citing papers by David G. Bear

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David G. Bear

This figure shows the co-authorship network connecting the top 25 collaborators of David G. Bear. A scholar is included among the top collaborators of David G. Bear 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 G. Bear. David G. Bear 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.
Youssof, Sarah, Ronald Schrader, David G. Bear, & Leslie Morrison. (2014). Hip flexion weakness is associated with impaired mobility in oculopharyngeal muscular dystrophy: A retrospective study with implications for trial design. Neuromuscular Disorders. 25(3). 238–246. 11 indexed citations
2.
Eldredge, Jonathan D., et al.. (2013). Student peer assessment in evidence-based medicine (EBM) searching skills training: an experiment. Journal of the Medical Library Association JMLA. 101(4). 244–251. 24 indexed citations
3.
Wallen, E. S., et al.. (2006). Heat shock protein 70 and glycoprotein 96 are differentially expressed on the surface of malignant and nonmalignant breast cells. Cell Stress and Chaperones. 11(4). 334–334. 33 indexed citations
4.
Gupta, Ranjan, et al.. (2005). Shear stress alters the expression of myelin‐associated glycoprotein (MAG) and myelin basic protein (MBP) in Schwann cells. Journal of Orthopaedic Research®. 23(5). 1232–1239. 47 indexed citations
5.
Gupta, Ranjan, et al.. (2005). Schwann cells upregulate vascular endothelial growth factor secondary to chronic nerve compression injury. Muscle & Nerve. 31(4). 452–460. 49 indexed citations
6.
7.
Bear, David G., et al.. (2003). Optimization of Schwann Cell Adhesion in Response to Shear Stress in an in Vitro Model for Peripheral Nerve Tissue Engineering. Tissue Engineering. 9(2). 233–241. 25 indexed citations
8.
Keller, Rebecca W., et al.. (2000). The nuclear poly(A) binding protein, PABP2, forms an oligomeric particle covering the length of the poly(A) tail. Journal of Molecular Biology. 297(3). 569–583. 63 indexed citations
10.
Menetski, Joseph P., David G. Bear, & S C Kowalczykowski. (1990). Stable DNA heteroduplex formation catalyzed by the Escherichia coli RecA protein in the absence of ATP hydrolysis.. Proceedings of the National Academy of Sciences. 87(1). 21–25. 223 indexed citations
12.
Garcı́a, Ricardo, David Keller, J. A. Panitz, David G. Bear, & Carlos Bustamante. (1989). Imaging of metal-coated biological samples by scanning tunneling microscopy. Ultramicroscopy. 27(4). 367–373. 11 indexed citations
13.
Bear, David G., et al.. (1988). Interactions of Escherichia coli transcription termination factor rho with RNA. Journal of Molecular Biology. 199(4). 623–635. 71 indexed citations
14.
McSwiggen, James A., David G. Bear, & Peter H. von Hippel. (1988). Interactions of Escherichia coli transcription termination factor rho with RNA. Journal of Molecular Biology. 199(4). 609–622. 87 indexed citations
15.
Bear, David G., Jeffrey D. Singer, William D. Morgan, et al.. (1985). Escherichia coli transcription termination factor rho has a two-domain structure in its activated form.. Proceedings of the National Academy of Sciences. 82(7). 1911–1915. 40 indexed citations
16.
Morgan, William D., et al.. (1985). RNA sequence and secondary structure requiresments for rho-dependent transcription termination. Nucleic Acids Research. 13(10). 3739–3754. 93 indexed citations
17.
Panitz, J. A. & David G. Bear. (1985). A procedure for increasing the contrast of biological specimens in edge‐projection TEM. Journal of Microscopy. 138(1). 107–110. 3 indexed citations
18.
Platt, Terry & David G. Bear. (1983). Role of RNA Polymerase, ρ Factor, and Ribosomes in Transcription Termination. Cold Spring Harbor Monograph Archive. 15. 123–161. 48 indexed citations
19.
Morgan, William D., David G. Bear, & Peter H. von Hippel. (1983). Rho-dependent termination of transcription. II. Kinetics of mRNA elongation during transcription from the bacteriophage lambda PR promoter.. Journal of Biological Chemistry. 258(15). 9565–9574. 81 indexed citations
20.
Morgan, William D., David G. Bear, & Peter H. von Hippel. (1983). Rho-dependent termination of transcription. I. Identification and characterization of termination sites for transcription from the bacteriophage lambda PR promoter.. Journal of Biological Chemistry. 258(15). 9553–9564. 80 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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