Ian G. Macara

28.7k citations
208 papers · 23.2k indexed · 5 hit papers · h-index 83
  • Cell Biology top 0.02%
    • Cellular transport and secretion 37
    • Hippo pathway signaling and YAP/TAZ 25
    • Microtubule and mitosis dynamics 24
  • Aging top 0.2%
    • RNA Research and Splicing 50
    • Nuclear Structure and Function 41
    • Protein Kinase Regulation and GTPase Signaling 28
    • Wnt/β-catenin signaling in development and cancer 15
    • Genomics and Chromatin Dynamics 12

Ian G. Macara

208 papers receiving 22.7k citations

Hit Papers

Organization and execution of the epith...520200020262008201750010001.5k2.0k

Peers

Ian G. Macara
Comparison fields: 5 of 167
  • Cell Biology 7.2k
  • Aging 731
  • Molecular Biology 17.5k
  • Cancer Research 2.7k
  • Immunology and Allergy 601
Replace Brian A. Hemmings with:
Brian A. Hemmings Switzerland
Shuo Lin United States
Yi Zheng United States
Ben Margolis United States
Roberto Zoncu United States
Yukiko Gotoh Japan
Alex Toker United States
Ángel R. Nebreda Spain
Rony Seger Israel
Brendan D. Manning United States
Ian G. Macara relative to Brian A. Hemmings Switzerland Brian A. Hemmings's profile →
Citations per field
00.5×1.5×2.3×
Brian A. Hemmings · 1×
Citations per year

Countries citing papers authored by Ian G. Macara

Since Specialization
Citations

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

Fields of papers citing papers by Ian G. Macara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian G. Macara. 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 Ian G. Macara. The network helps show where Ian G. Macara may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ian G. Macara, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ian G. Macara Line = papers co-authored together Ian G. Macara links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202019
2 20138
3 2010191
4 200977
5 200854
6 200889
7 2008117
8
The PAR Proteins: Fundamental Players in Animal Cell Polarizationbreakdown →
2007596
9 2006174
10 2006215
11 2005212
12 200476
13 2003401
14 200248
15 2002159
16 2001468
17 199922
18 1998124
19 199571
20 19899

About Ian G. Macara

Ian G. Macara is a scholar working on Aging, Cell Biology and Molecular Biology, having authored 208 papers that have together received 23.2k indexed citations. Recurring topics across this work include RNA Research and Splicing (50 papers), Nuclear Structure and Function (41 papers), Cellular transport and secretion (37 papers), Protein Kinase Regulation and GTPase Signaling (28 papers), Hippo pathway signaling and YAP/TAZ (25 papers), Microtubule and mitosis dynamics (24 papers), Wnt/β-catenin signaling in development and cancer (15 papers) and Genomics and Chromatin Dynamics (12 papers). The work is most often cited by research in Cell Biology (7.2k citations), Aging (731 citations) and Molecular Biology (17.5k citations). Ian G. Macara has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Yi Qin, Bryan R. Cullen, Rui Yi, Gérard Joberty, Lin Gao, Quansheng Du, Luke McCaffrey, Bob Goldstein, Alan Wolfman and Amy M. Brownawell. Their work appears in journals such as Nature, Science and Cell.

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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