Enes Makalic

12.2k citations
64 papers · 1.2k indexed · h-index 18
Topics
Epigenetics and DNA Methylation (18 papers)Genetic Associations and Epidemiology (11 papers)Bayesian Methods and Mixture Models (8 papers)

In The Last Decade

Enes Makalic

60 papers receiving 1.1k citations

Peers

Enes Makalic
Comparison fields: 5 of 136
  • Molecular Biology 590
  • Pediatrics, Perinatology and Child Health 154
  • Genetics 149
  • Cancer Research 143
  • Oncology 138
Replace Daniel F. Schmidt with:
Daniel F. Schmidt Australia
Gad Abraham Australia
Jeffery L. Painter United States
Ståle Nygård Norway
Vincenzo Lagani Greece
Yanxun Xu United States
Daniel Becker United States
Fei Chen China
Jessica Minnier United States
Romain Mathiéu France
Enes Makalic relative to Daniel F. Schmidt Australia Daniel F. Schmidt's profile →
Citations per field
00.5×1.6×
Daniel F. Schmidt · 1×
Citations per year

Countries citing papers authored by Enes Makalic

Since Specialization
Citations

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

Fields of papers citing papers by Enes Makalic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Enes Makalic

This figure shows the co-authorship network connecting the top 25 collaborators of Enes Makalic. A scholar is included among the top collaborators of Enes Makalic 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 Enes Makalic. Enes Makalic 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
#WorkIndexed citations
1 1
2 0
3 3
4 2
5 2
6 2
7 7
8 0
9 1
10 2
11 0
12 47
13 55
14 4
15 35
16
Bayesian Sparse Global-Local Shrinkage Regression for Grouped Variables
1
17 3
18 21
19 6
20 12

About Enes Makalic

Enes Makalic is a scholar working on Statistics and Probability, Aging and Genetics, having authored 64 papers that have together received 1.2k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (18 papers), Genetic Associations and Epidemiology (11 papers) and Bayesian Methods and Mixture Models (8 papers). The work is most often cited by research in Statistics and Probability (92 citations), Aging (19 citations) and Cancer Research (143 citations). Enes Makalic has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Daniel F. Schmidt, Melissa C. Southey, Graham G. Giles, John L. Hopper, Dallas R. English, Roger L. Milne, Pierre‐Antoine Dugué, Jihoon E. Joo, Ee Ming Wong and Daniel D. Buchanan. Their work appears in journals such as PLoS ONE, American Journal of Clinical Nutrition and JNCI Journal of the National Cancer Institute.

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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