Liu Ka

28 papers receiving 529 citations

Peers

Liu Ka
Comparison fields: 5 of 85
  • Oncology 206
  • Immunology 162
  • Cancer Research 71
  • Genetics 106
  • Neurology 34
Replace Huihui Chen with:
Huihui Chen China
Seok‐Ho Kim South Korea
Sandra Livingston United States
Johannes P. van Netten Canada
Marta Monteiro Portugal
Tomoyasu Hattori Japan
Michela Riba Italy
WE Grizzle United States
Subhash Tripathi Finland
M. K. White United States
Liu Ka relative to Huihui Chen China Huihui Chen's profile →
Citations per field
00.5×4.4×
Huihui Chen · 1×
Citations per year

Countries citing papers authored by Liu Ka

Since Specialization
Citations

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

Fields of papers citing papers by Liu Ka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020211
2 201371
3 201542
4 201739
5 201030
6 201223
7 200622
8 200913
9 201312
10 201610
11 20159
12 20188
13
Comparable Responses in Male and Female Mice to Cerulein-Induced Chronic Pancreatic Injury and Recovery.
20188
14 20097
15 20127
16
Named Entity Extraction of Traditional Chinese Medicine Medical Records Based on Conditional Random Field
20143
17
Regime Shift of Winter North Pacific Sea Surface Temperature after 1990 and Its Possible Causes
20153
18 20083
19
A design of high sensitivity induction magnetometer for TEM
20143
20
A Weibo Bot-users Indentification Model Based on Random Forest
20152

About Liu Ka

Liu Ka is a scholar working on Molecular Biology, Surgery, Genetics, Immunology and Cancer Research, having authored 28 papers that have together received 535 indexed citations. Recurring topics across this work include Pancreatitis Pathology and Treatment (4 papers), Immune Cell Function and Interaction (3 papers), Protein Degradation and Inhibitors (2 papers), Cancer, Lipids, and Metabolism (2 papers), Genetic and phenotypic traits in livestock (2 papers), Estrogen and related hormone effects (2 papers), Cancer-related molecular mechanisms research (2 papers) and Cardiac electrophysiology and arrhythmias (1 paper). The work is most often cited by research in Oncology (206 citations), Immunology (162 citations), Cancer Research (71 citations), Genetics (106 citations) and Neurology (34 citations). Liu Ka has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Z. Runlin, Barbara Savoldo, Amy N. Courtney, Erica J. Di Pierro, Tali Raveh-Sadka, Gianpietro Dotti, Leonid S. Metelitsa, Simon N. Robinson, Cynthia Chauvin and Olga Dakhova. Their work appears in journals such as Cancer Research, BMC Genomics, Journal of genetics and genomics, American Journal of Physiology-Gastrointestinal and Liver Physiology and Biochemical and Biophysical Research Communications.

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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