Michael L. Raymer

2.5k total citations · 1 hit paper
67 papers, 1.7k citations indexed

About

Michael L. Raymer is a scholar working on Molecular Biology, Artificial Intelligence and Media Technology. According to data from OpenAlex, Michael L. Raymer has authored 67 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 15 papers in Artificial Intelligence and 8 papers in Media Technology. Recurrent topics in Michael L. Raymer's work include Metabolomics and Mass Spectrometry Studies (13 papers), RNA and protein synthesis mechanisms (12 papers) and Genomics and Phylogenetic Studies (11 papers). Michael L. Raymer is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (13 papers), RNA and protein synthesis mechanisms (12 papers) and Genomics and Phylogenetic Studies (11 papers). Michael L. Raymer collaborates with scholars based in United States, Sweden and India. Michael L. Raymer's co-authors include William F. Punch, Leslie A. Kuhn, Erik D. Goodman, Anil K. Jain, Travis E. Doom, Dan E. Krane, Nicholas V. Reo, Paul E. Anderson, Nicholas J. DelRaso and Esley M. Heizer and has published in prestigious journals such as Bioinformatics, Journal of Molecular Biology and Scientific Reports.

In The Last Decade

Michael L. Raymer

63 papers receiving 1.6k citations

Hit Papers

Dimensionality reduction using genetic algorithms 2000 2026 2008 2017 2000 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Dimensionality reduction using genetic algorithms
    2000 618 citations Michael L. Raymer, William F. Punch et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael L. Raymer United States 18 660 530 256 154 135 67 1.7k
Halima Bensmail Qatar 26 702 1.1× 468 0.9× 347 1.4× 103 0.7× 73 0.5× 85 2.0k
Balázs Kégl Canada 17 259 0.4× 511 1.0× 731 2.9× 92 0.6× 245 1.8× 43 2.0k
Sören Sonnenburg Germany 17 818 1.2× 900 1.7× 831 3.2× 160 1.0× 78 0.6× 20 2.4k
Rajat K. De India 18 590 0.9× 343 0.6× 182 0.7× 116 0.8× 39 0.3× 90 1.3k
Julia Handl United Kingdom 20 800 1.2× 1.2k 2.2× 313 1.2× 436 2.8× 89 0.7× 53 2.5k
Yves Chauvin United States 16 1.5k 2.3× 801 1.5× 264 1.0× 304 2.0× 164 1.2× 26 3.1k
Chen Li China 23 645 1.0× 683 1.3× 429 1.7× 94 0.6× 36 0.3× 124 2.1k
Raghvendra Mall India 28 1.0k 1.5× 432 0.8× 163 0.6× 177 1.1× 63 0.5× 120 2.7k
Ping Liu China 23 320 0.5× 98 0.2× 247 1.0× 201 1.3× 90 0.7× 85 1.6k
Carlo Vittorio Cannistraci Italy 31 937 1.4× 340 0.6× 94 0.4× 208 1.4× 88 0.7× 96 2.7k

Countries citing papers authored by Michael L. Raymer

Since Specialization
Citations

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

Fields of papers citing papers by Michael L. Raymer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael L. Raymer. 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 Michael L. Raymer. The network helps show where Michael L. Raymer may publish in the future.

Co-authorship network of co-authors of Michael L. Raymer

This figure shows the co-authorship network connecting the top 25 collaborators of Michael L. Raymer. A scholar is included among the top collaborators of Michael L. Raymer 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 Michael L. Raymer. Michael L. Raymer 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.
Raymer, Michael L., et al.. (2024). Multi -Semantic-Stage Neural Networks. 2. 364–369.
2.
3.
Raymer, Michael L., Nicholas V. Reo, J. Philip Karl, et al.. (2021). Urinary Metabolites as Predictors of Acute Mountain Sickness Severity. Frontiers in Physiology. 12. 709804–709804. 12 indexed citations
4.
Raymer, Michael L., et al.. (2021). Toxicity prediction using locality-sensitive deep learner. Computational Toxicology. 21. 100210–100210. 1 indexed citations
5.
Raymer, Michael L., et al.. (2021). Multi-label classification and label dependence in in silico toxicity prediction. Toxicology in Vitro. 74. 105157–105157. 8 indexed citations
6.
Yoo, Seungyeul, Zhiao Shi, Bo Wen, et al.. (2021). A community effort to identify and correct mislabeled samples in proteogenomic studies. Patterns. 2(5). 100245–100245. 5 indexed citations
7.
Yalamanchili, Hima Bindu, et al.. (2017). A Novel Approach for Classifying Gene Expression Data using Topic Modeling. 128. 388–393. 5 indexed citations
8.
Heizer, Esley M., et al.. (2012). Metabolic and Translational Efficiency in Microbial Organisms. Journal of Molecular Evolution. 74(3-4). 206–216. 14 indexed citations
9.
Heizer, Esley M., Michael L. Raymer, & Dan E. Krane. (2011). Amino Acid Biosynthetic Cost and Protein Conservation. Journal of Molecular Evolution. 72(5-6). 466–473. 15 indexed citations
10.
Krane, Dan E., et al.. (2011). Inferring the Number of Contributors to Mixed DNA Profiles. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 9(1). 113–122. 20 indexed citations
11.
Krane, Dan E., et al.. (2009). Automated Isolation of Translational Efficiency Bias That Resists the Confounding Effect of GC(AT)-Content. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 7(2). 238–250. 8 indexed citations
12.
Heizer, Esley M., et al.. (2008). Do Amino Acid Biosynthetic Costs Constrain Protein Evolution in Saccharomyces cerevisiae?. Journal of Molecular Evolution. 67(6). 621–630. 46 indexed citations
13.
Klingbeil, Nathan, et al.. (2007). Engineering Mathematics Education at Wright State University: Uncorking the First Year Bottleneck. CORE Scholar (Wright State University). 6 indexed citations
14.
Heizer, Esley M., et al.. (2006). Amino Acid Cost and Codon-Usage Biases in 6 Prokaryotic Genomes: A Whole-Genome Analysis. Molecular Biology and Evolution. 23(9). 1670–1680. 61 indexed citations
15.
Doom, Travis E., et al.. (2006). Assessing the Implications for Close Relatives in the Event of Similar but Nonmatching DNA Profiles. Journal of Bioresource Management. 46(2). 161–175. 5 indexed citations
16.
Raymer, Michael L., Travis E. Doom, Leslie A. Kuhn, & William F. Punch. (2003). Knowledge discovery in medical and biological datasets using a hybrid bayes classifier/evolutionary algorithm. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 33(5). 802–813. 79 indexed citations
17.
Sweeney, Deacon, Michael L. Raymer, & Thomas D. Lockwood. (2003). Antidiabetic and antimalarial biguanide drugs are metal-interactive antiproteolytic agents. Biochemical Pharmacology. 66(4). 663–677. 56 indexed citations
18.
Gilder, Jason R., Michael L. Raymer, & Travis E. Doom. (2001). PocketMol: A Molecular Visualization Tool for the PocketPC (short paper).. 11–14. 1 indexed citations
19.
Gilder, Jason R., Michael L. Raymer, & Travis E. Doom. (2001). PocketMol: a molecular visualization tool for the Pocket PC. Journal of Bioresource Management. 11–14. 3 indexed citations
20.
Raymer, Michael L., et al.. (1997). Predicting conserved water-mediated and polar ligand interactions in proteins using a K-nearest-neighbors genetic algorithm. Journal of Molecular Biology. 265(4). 445–464. 121 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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