Michael DeGiorgio

3.1k total citations
57 papers, 1.2k citations indexed

About

Michael DeGiorgio is a scholar working on Genetics, Molecular Biology and Paleontology. According to data from OpenAlex, Michael DeGiorgio has authored 57 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Genetics, 29 papers in Molecular Biology and 8 papers in Paleontology. Recurrent topics in Michael DeGiorgio's work include Genetic diversity and population structure (34 papers), Genomics and Phylogenetic Studies (17 papers) and Genetic and phenotypic traits in livestock (12 papers). Michael DeGiorgio is often cited by papers focused on Genetic diversity and population structure (34 papers), Genomics and Phylogenetic Studies (17 papers) and Genetic and phenotypic traits in livestock (12 papers). Michael DeGiorgio collaborates with scholars based in United States, New Zealand and Italy. Michael DeGiorgio's co-authors include Noah A. Rosenberg, J. H. Degnan, Xiaoheng Cheng, Mattias Jakobsson, Trevor J. Pemberton, Rasmus Nielsen, David Bryant, Christian D. Huber, Ines Hellmann and Mehreen R. Mughal and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Current Biology.

In The Last Decade

Michael DeGiorgio

53 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
Michael DeGiorgio United States 20 865 470 141 124 110 57 1.2k
Jonathan Terhorst United States 11 749 0.9× 325 0.7× 125 0.9× 117 0.9× 127 1.2× 26 1.1k
Jack Kamm United States 10 630 0.7× 269 0.6× 116 0.8× 113 0.9× 92 0.8× 15 951
Andrea Benazzo Italy 19 562 0.6× 227 0.5× 205 1.5× 137 1.1× 57 0.5× 35 965
Joseph Lachance United States 17 882 1.0× 367 0.8× 84 0.6× 134 1.1× 58 0.5× 31 1.2k
Flora Jay France 13 730 0.8× 223 0.5× 166 1.2× 70 0.6× 99 0.9× 23 1.1k
Min‐Sheng Peng China 18 754 0.9× 376 0.8× 76 0.5× 52 0.4× 68 0.6× 58 1.1k
Jerome Kelleher United Kingdom 16 947 1.1× 386 0.8× 89 0.6× 85 0.7× 52 0.5× 31 1.2k
José Alfredo Samaniego Castruita Denmark 18 623 0.7× 527 1.1× 429 3.0× 237 1.9× 202 1.8× 33 1.4k
Saeid Naderi Iran 13 856 1.0× 182 0.4× 220 1.6× 59 0.5× 70 0.6× 36 1.1k
R Kondo Japan 8 591 0.7× 516 1.1× 101 0.7× 58 0.5× 96 0.9× 9 1.1k

Countries citing papers authored by Michael DeGiorgio

Since Specialization
Citations

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

Fields of papers citing papers by Michael DeGiorgio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael DeGiorgio

This figure shows the co-authorship network connecting the top 25 collaborators of Michael DeGiorgio. A scholar is included among the top collaborators of Michael DeGiorgio 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 DeGiorgio. Michael DeGiorgio 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.
Fumagalli, Matteo, et al.. (2025). Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning. Molecular Biology and Evolution. 42(5). 1 indexed citations
2.
DeGiorgio, Michael, et al.. (2025). Genomic Anomaly Detection with Functional Data Analysis. Genes. 16(6). 710–710.
3.
McKenna, Duane D., et al.. (2024). TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution. Bioinformatics Advances. 5(1). vbae196–vbae196.
4.
Murray, J. D., François Lanoë, María Nieves Zedeño, et al.. (2024). Genomic analyses correspond with deep persistence of peoples of Blackfoot Confederacy from glacial times. Science Advances. 10(14). eadl6595–eadl6595. 1 indexed citations
5.
DeGiorgio, Michael, et al.. (2024). Predicting evolutionary targets and parameters of gene deletion from expression data. Bioinformatics Advances. 4(1). vbae002–vbae002.
6.
DeGiorgio, Michael, et al.. (2023). Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data. Molecular Biology and Evolution. 40(10). 3 indexed citations
7.
DeGiorgio, Michael, et al.. (2023). Uncovering Footprints of Natural Selection Through Spectral Analysis of Genomic Summary Statistics. Molecular Biology and Evolution. 40(7). 9 indexed citations
8.
Adams, Richard H., et al.. (2023). Robust Phylogenetic Regression. Systematic Biology. 73(1). 140–157. 6 indexed citations
9.
Lindo, John, et al.. (2022). The genomic prehistory of the Indigenous peoples of Uruguay. PNAS Nexus. 1(2). pgac047–pgac047. 7 indexed citations
10.
Mughal, Mehreen R. & Michael DeGiorgio. (2021). Properties and unbiased estimation of F - and D -statistics in samples containing related and inbred individuals. Genetics. 220(1). 5 indexed citations
11.
DeGiorgio, Michael, et al.. (2020). A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data. Molecular Biology and Evolution. 37(10). 3023–3046. 30 indexed citations
12.
DeGiorgio, Michael & Raquel Assis. (2020). Learning Retention Mechanisms and Evolutionary Parameters of Duplicate Genes from Their Expression Data. Molecular Biology and Evolution. 38(3). 1209–1224. 8 indexed citations
13.
DeGiorgio, Michael, et al.. (2020). Identifying and Classifying Shared Selective Sweeps from Multilocus Data. Genetics. 215(1). 143–171. 14 indexed citations
14.
Cheng, Xiaoheng & Michael DeGiorgio. (2020). Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection. Molecular Biology and Evolution. 37(11). 3267–3291. 21 indexed citations
15.
DeGiorgio, Michael, et al.. (2020). Maximum Likelihood Estimation of Species Trees from Gene Trees in the Presence of Ancestral Population Structure. Genome Biology and Evolution. 12(2). 3977–3995. 4 indexed citations
16.
Mousset, Sylvain, et al.. (2020). VolcanoFinder: Genomic scans for adaptive introgression. PLoS Genetics. 16(6). e1008867–e1008867. 60 indexed citations
17.
Garud, Nandita R., et al.. (2018). Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity. Genetics. 210(4). 1429–1452. 50 indexed citations
18.
Cheng, Xiaoheng & Michael DeGiorgio. (2018). Detection of Shared Balancing Selection in the Absence of Trans-Species Polymorphism. Molecular Biology and Evolution. 36(1). 177–199. 20 indexed citations
19.
Prada, Carlos, Ann F. Budd, Cheryl M. Woodley, et al.. (2016). Empty Niches after Extinctions Increase Population Sizes of Modern Corals. Current Biology. 26(23). 3190–3194. 69 indexed citations
20.
Huber, Christian D., Michael DeGiorgio, Ines Hellmann, & Rasmus Nielsen. (2015). Detecting recent selective sweeps while controlling for mutation rate and background selection. Molecular Ecology. 25(1). 142–156. 92 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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