Daniel M. Jordan

10.8k citations
36 papers · 3.3k indexed · 1 hit paper · h-index 14
Topics
Genetic Associations and Epidemiology (22 papers)Genomics and Rare Diseases (18 papers)Genomic variations and chromosomal abnormalities (9 papers)

In The Last Decade

Daniel M. Jordan

34 papers receiving 3.3k citations

Hit Papers

Predicting Functional Effect of Human Missense Mutations ...2013202620172021201350010001.5k2.0k

Peers

Daniel M. Jordan
Comparison fields: 5 of 140
  • Molecular Biology 1.8k
  • Genetics 1.4k
  • Cancer Research 401
  • Oncology 239
  • Surgery 227
Replace Cornelius F. Boerkoel with:
Cornelius F. Boerkoel United States
Michael B. Gorin United States
Yasuaki Shirayoshi Japan
Jeremy Schwartzentruber Canada
Christopher D. Brown United States
Samuel S. Chong Singapore
Sonia Abdelhak Tunisia
Takayuki Morisaki Japan
Ohad S. Birk Israel
Mark J. Cowley Australia
Daniel M. Jordan relative to Cornelius F. Boerkoel United States Cornelius F. Boerkoel's profile →
Citations per field
00.5×1.5×2.4×
Cornelius F. Boerkoel · 1×
Citations per year

Countries citing papers authored by Daniel M. Jordan

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Jordan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Jordan. 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 Daniel M. Jordan. The network helps show where Daniel M. Jordan may publish in the future.

Co-authorship network of co-authors of Daniel M. Jordan

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Jordan. A scholar is included among the top collaborators of Daniel M. Jordan 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 Daniel M. Jordan. Daniel M. Jordan 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 2
3 0
4 3
5 0
6 1
7 9
8 11
9 5
10 2
11 18
12 4
13 1
14 93
15 1
16 79
17 39
18 67
19 58
20 5

About Daniel M. Jordan

Daniel M. Jordan is a scholar working on Genetics, Transplantation and Nephrology, having authored 36 papers that have together received 3.3k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (22 papers), Genomics and Rare Diseases (18 papers) and Genomic variations and chromosomal abnormalities (9 papers). The work is most often cited by research in Genetics (1.4k citations), Cancer Research (401 citations) and Molecular Biology (1.8k citations). Daniel M. Jordan has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Shamil Sunyaev, Ivan Adzhubei, Ron Do, Christopher A. Cassa, Marie Verbanck, Girish N. Nadkarni, Mark Tong, Hong‐Hee Won, Vasily Ramensky and Daniel J. Balick. Their work appears in journals such as Nature, Science and The Lancet.

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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