Pek Yee Lum

11.9k citations
45 papers · 3.5k indexed · 1 hit paper · h-index 27

Pek Yee Lum

45 papers receiving 3.5k citations

Hit Papers

Extracting insights from the shape of complex data using ...3122013202620172021100200300

Peers

Pek Yee Lum
Comparison fields: 5 of 171
  • Computational Theory and Mathematics 429
  • Molecular Biology 1.8k
  • Aging 44
  • Biophysics 142
  • Pharmacology 207
Replace Jing Huang with:
Jing Huang United States
Chris T. Evelo Netherlands
Ralf Herwig Germany
Philippe Sanséau United Kingdom
Irene F. Kim United States
Diego di Bernardo Italy
Alexander R. Pico United States
Chi‐Ying F. Huang Taiwan
Tamás Korcsmáros United Kingdom
Carlos Evangelista United States
Pek Yee Lum relative to Jing Huang United States Jing Huang's profile →
Citations per field
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Jing Huang · 1×
Citations per year

Countries citing papers authored by Pek Yee Lum

Since Specialization
Citations

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

Fields of papers citing papers by Pek Yee Lum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pek Yee Lum. 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 Pek Yee Lum. The network helps show where Pek Yee Lum may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201766
2 201627
3
Extracting insights from the shape of complex data using topologybreakdown →
2013312
4
The topology of politics : voting connectivity in the US House of Representatives
20121
5 201257
6 201215
7 201199
8 2010207
9 200920
10 200985
11 2007140
12 2006228
13 200666
14 200517
15 2005168
16 2005114
17 2004374
18 200322
19 1993158
20 199016

About Pek Yee Lum

Pek Yee Lum is a scholar working on Anatomy, Physiology and Computational Theory and Mathematics, having authored 45 papers that have together received 3.5k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (11 papers), Gene expression and cancer classification (7 papers), Adipose Tissue and Metabolism (5 papers), Computational Drug Discovery Methods (4 papers), Microbial Metabolic Engineering and Bioproduction (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers) and Topological and Geometric Data Analysis (3 papers). The work is most often cited by research in Computational Theory and Mathematics (429 citations), Molecular Biology (1.8k citations) and Aging (44 citations). Pek Yee Lum has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Eric E. Schadt, Jun Zhu, Robin Wright, Douglas C. Rees, Heather W. Pinkett, Kaspar P. Locher, Christopher D. Armour, Muthuraman Alagappan, Roger G. Ulrich and John R. Lamb. Their work appears in journals such as Science, Cell 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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