Lee A. Newberg

576 total citations
23 papers, 325 citations indexed

About

Lee A. Newberg is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Lee A. Newberg has authored 23 papers receiving a total of 325 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 5 papers in Artificial Intelligence and 5 papers in Genetics. Recurrent topics in Lee A. Newberg's work include RNA and protein synthesis mechanisms (9 papers), Genomics and Phylogenetic Studies (8 papers) and Genomics and Chromatin Dynamics (6 papers). Lee A. Newberg is often cited by papers focused on RNA and protein synthesis mechanisms (9 papers), Genomics and Phylogenetic Studies (8 papers) and Genomics and Chromatin Dynamics (6 papers). Lee A. Newberg collaborates with scholars based in United States, Philippines and Spain. Lee A. Newberg's co-authors include Charles E. Lawrence, Richard M. Karp, Lee Ann McCue, Farid Alizadeh, Sean Conlan, William A. Thompson, David Naor, C. Steven Carmack, Chinnappa D. Kodira and Thomas M. Smith and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Lee A. Newberg

23 papers receiving 305 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lee A. Newberg United States 10 225 69 66 39 24 23 325
Marta Kasprzak Poland 14 386 1.7× 190 2.8× 63 1.0× 68 1.7× 30 1.3× 50 469
Nicolas Wicker France 9 156 0.7× 76 1.1× 43 0.7× 16 0.4× 16 0.7× 24 295
Chaoyang Zhang United States 14 496 2.2× 68 1.0× 73 1.1× 38 1.0× 46 1.9× 43 651
M Waterman United States 10 324 1.4× 175 2.5× 73 1.1× 63 1.6× 24 1.0× 12 468
Alexandru I. Tomescu Finland 11 236 1.0× 147 2.1× 44 0.7× 121 3.1× 33 1.4× 68 437
Peter Friedland United States 10 131 0.6× 144 2.1× 24 0.4× 16 0.4× 13 0.5× 24 319
Andrzej Mizera Luxembourg 10 283 1.3× 52 0.8× 25 0.4× 63 1.6× 9 0.4× 28 373
H. K. Dai United States 6 251 1.1× 81 1.2× 35 0.5× 11 0.3× 31 1.3× 18 347
Michal Ziv-Ukelson Israel 13 662 2.9× 168 2.4× 71 1.1× 73 1.9× 19 0.8× 44 793
Olaf Weiss Germany 7 376 1.7× 34 0.5× 66 1.0× 18 0.5× 24 1.0× 8 435

Countries citing papers authored by Lee A. Newberg

Since Specialization
Citations

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

Fields of papers citing papers by Lee A. Newberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee A. Newberg. 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 Lee A. Newberg. The network helps show where Lee A. Newberg may publish in the future.

Co-authorship network of co-authors of Lee A. Newberg

This figure shows the co-authorship network connecting the top 25 collaborators of Lee A. Newberg. A scholar is included among the top collaborators of Lee A. Newberg 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 Lee A. Newberg. Lee A. Newberg 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.
Morales-Álvarez, Pablo, Lee Cooper, Lee A. Newberg, et al.. (2024). Focused active learning for histopathological image classification. Medical Image Analysis. 95. 103162–103162. 5 indexed citations
2.
Newberg, Lee A., Xiaowei Chen, Chinnappa D. Kodira, & Maria I. Zavodszky. (2018). Computational de novo discovery of distinguishing genes for biological processes and cell types in complex tissues. PLoS ONE. 13(3). e0193067–e0193067. 6 indexed citations
3.
Aggour, Kareem S., et al.. (2015). A highly parallel next-generation DNA sequencing data analysis pipeline in Hadoop. 20. 756–763. 5 indexed citations
4.
Palumbo, Michael J. & Lee A. Newberg. (2010). Phyloscan: locating transcription-regulating binding sites in mixed aligned and unaligned sequence data. Nucleic Acids Research. 38(Web Server). W268–W274. 6 indexed citations
5.
Newberg, Lee A.. (2009). Error statistics of hidden Markov model and hidden Boltzmann model results. BMC Bioinformatics. 10(1). 212–212. 13 indexed citations
6.
Newberg, Lee A. & Charles E. Lawrence. (2009). Exact Calculation of Distributions on Integers, with Application to Sequence Alignment. Journal of Computational Biology. 16(1). 1–18. 32 indexed citations
7.
Newberg, Lee A.. (2008). Significance of Gapped Sequence Alignments. Journal of Computational Biology. 15(9). 1187–1194. 17 indexed citations
8.
Newberg, Heidi Jo, et al.. (2008). Effect of Night Laboratories on Learning Objectives for a Nonmajor Astronomy Class. Astronomy Education Review. 7(2). 66–73. 7 indexed citations
9.
Carmack, C. Steven, Lee Ann McCue, Lee A. Newberg, & Charles E. Lawrence. (2007). PhyloScan: identification of transcription factor binding sites using cross-species evidence. Algorithms for Molecular Biology. 2(1). 1–1. 22 indexed citations
10.
Thompson, William A., Lee A. Newberg, Sean Conlan, Lee Ann McCue, & Charles E. Lawrence. (2007). The Gibbs Centroid Sampler. Nucleic Acids Research. 35(Web Server). W232–W237. 49 indexed citations
11.
Newberg, Lee A., William A. Thompson, Sean Conlan, et al.. (2007). A phylogenetic Gibbs sampler that yields centroid solutions forcis-regulatory site prediction. Bioinformatics. 23(14). 1718–1727. 26 indexed citations
12.
Newberg, Lee A., Lee Ann McCue, & Charles E. Lawrence. (2005). The Relative Inefficiency of Sequence Weights Approaches in Determining a Nucleotide Position Weight Matrix. Statistical Applications in Genetics and Molecular Biology. 4(1). Article13–Article13. 5 indexed citations
13.
Newberg, Lee A. & Charles E. Lawrence. (2004). Mammalian Genomes Ease Location of Human DNA Functional Segments but Not Their Description. Statistical Applications in Genetics and Molecular Biology. 3(1). 1–12. 7 indexed citations
14.
Newberg, Lee A.. (1996). The number of clone orderings. Discrete Applied Mathematics. 69(3). 233–245. 2 indexed citations
15.
Karp, Richard M. & Lee A. Newberg. (1995). An algorithm for analysing probed partial digestion experiments. Computer applications in the biosciences. 11(3). 229–235. 5 indexed citations
16.
Newberg, Lee A.. (1994). Finding a Most Likely Clone Ordering from Oligonucleotide Hybridization Data. Genomics. 21(3). 602–611. 2 indexed citations
17.
Newberg, Lee A. & David Wolfe. (1994). String layouts for a redundant array of inexpensive disks. Algorithmica. 12(2-3). 209–224. 6 indexed citations
18.
Alizadeh, Farid, et al.. (1993). Physical mapping of chromosomes: a combinatorial problem in molecular biology. Symposium on Discrete Algorithms. 371–381. 27 indexed citations
19.
Newberg, Lee A. & David Naor. (1993). A Lower Bound on the Number of Solutions to the Probed Partial Digest Problem. Advances in Applied Mathematics. 14(2). 172–183. 18 indexed citations
20.
Newberg, Lee A. & David Wolfe. (1991). String Layout in Redundant Disk Arrays. UC Berkeley. 1 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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