Pardeep Heir

922 citations
12 papers · 624 · h-index 11

Impact in

    • Cancer, Hypoxia, and Metabolism
    • Protein Tyrosine Phosphatases
    • Ubiquitin and proteasome pathways
    • Protein Kinase Regulation and GTPase Signaling
    • PI3K/AKT/mTOR signaling in cancer
    • RNA modifications and cancer

Papers in

    • Ubiquitin and proteasome pathways 2
    • Protein Kinase Regulation and GTPase Signaling 2
    • Cancer, Hypoxia, and Metabolism 5
    • Cancer-related molecular mechanisms research 1

Pardeep Heir

12 papers receiving 620 citations

Peers

Pardeep Heir
Comparison fields: 5 of 67
  • Cancer Research 135
  • Molecular Biology 437
  • Cell Biology 98
  • Genetics 58
  • Immunology 104
Replace Elsie White with:
Elsie White United States
Kimberly A. Scata United States
Víctor J. Sánchez‐Arévalo Lobo Spain
Shiro Kataoka Japan
Nicole E. Carlson United States
Marjon A. Smit Netherlands
Nakho Chang South Korea
Roderick P. Regala United States
Jessica Vieusseux Australia
Jason A. Sager United States
Pardeep Heir relative to Elsie White United States Elsie White's profile →
Citations per field
00.5×
Elsie White · 1×
Citations per year

Countries citing papers authored by Pardeep Heir

Since Specialization
Citations

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

Fields of papers citing papers by Pardeep Heir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pardeep Heir, 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 Pardeep Heir Line = papers co-authored together Pardeep Heir links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2015184
2 2012104
3 201485
4 201159
5 201958
6 201136
7 201625
8 201319
9 201318
10 201415
11 202014
12 20167

About Pardeep Heir

Pardeep Heir is a scholar working on Molecular Biology, Cancer Research, Cell Biology, Oncology and Hematology, having authored 12 papers that have together received 624 indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (5 papers), Cytokine Signaling Pathways and Interactions (3 papers), Acute Myeloid Leukemia Research (2 papers), Ubiquitin and proteasome pathways (2 papers), Microtubule and mitosis dynamics (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers) and Cancer-related molecular mechanisms research (1 paper). The work is most often cited by research in Cancer Research (135 citations), Molecular Biology (437 citations), Cell Biology (98 citations), Genetics (58 citations) and Immunology (104 citations). Pardeep Heir has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include Michael Ohh, Severa Bunda, Gelareh Zadeh, Kelly Burrell, Brian Raught, Yoshihito Kano, Amir Alamsahebpour, Zhong‐Yin Zhang, Li‐Fan Zeng and Jeffrey E. Lee. Their work appears in journals such as Nature Communications, Proceedings of the National Academy of Sciences, Nature Medicine, Journal of Biological Chemistry and American Journal Of Pathology.

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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