HaMut Lam

987 citations
8 papers · 589 · h-index 8

Impact in

  • Urology top 1%
    • Hair Growth and Disorders
    • Skin and Cellular Biology Research
    • melanin and skin pigmentation

Papers in

    • Wnt/β-catenin signaling in development and cancer 3
    • RNA Research and Splicing 2
    • RNA regulation and disease 2
    • Connexins and lens biology 1
    • Hair Growth and Disorders 5

HaMut Lam

8 papers receiving 567 citations

Peers

HaMut Lam
Comparison fields: 5 of 57
  • Urology 363
  • Cell Biology 332
  • Dermatology 79
  • Molecular Biology 375
  • Genetics 89
Replace N. Meier with:
N. Meier Germany
Ka Wai Mok United States
Kaiju Jiang China
Sabine Kissling Germany
Bedia Assy Israel
Jennifer E. Klatte Germany
Sima Serafimovich Israel
Weiming Qiu China
Abdul Wali Pakistan
Margaret M. Humble United States
HaMut Lam relative to N. Meier Germany N. Meier's profile →
Citations per field
00.5×2.9×
N. Meier · 1×
Citations per year

Countries citing papers authored by HaMut Lam

Since Specialization
Citations

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

Fields of papers citing papers by HaMut Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

8 of 8 papers shown
#Work
1 1998287
2 199797
3 199974
4 199858
5 199835
6 200220
7 200510
8
Identification of a novel splice site mutation in the human hairless gene underlying atrichia with papular lesions.
20068

About HaMut Lam

HaMut Lam is a scholar working on Molecular Biology, Urology, Cell Biology, Paleontology and Pediatrics, Perinatology and Child Health, having authored 8 papers that have together received 589 indexed citations. Recurring topics across this work include Hair Growth and Disorders (5 papers), Skin and Cellular Biology Research (4 papers), Wnt/β-catenin signaling in development and cancer (3 papers), melanin and skin pigmentation (2 papers), RNA Research and Splicing (2 papers), RNA regulation and disease (2 papers), Connexins and lens biology (1 paper) and Neonatal Health and Biochemistry (1 paper). The work is most often cited by research in Urology (363 citations), Cell Biology (332 citations), Dermatology (79 citations), Molecular Biology (375 citations) and Genetics (89 citations). HaMut Lam has collaborated with scholars based in United States, United Kingdom and Pakistan. Frequent co-authors include John A. McGrath, Angela M. Christiano, Wasim Ahmad, Muhammad Faiyaz ul Haque, Mahmud Ahmad, Jorge Frank, Andrey A. Panteleyev, Vincent M. Aita, Monica Peacocke and Andrew Leask. Their work appears in journals such as The American Journal of Human Genetics, Journal of Investigative Dermatology, Journal of Dermatological Science, Science and Genomics.

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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