Stephen Lim

850 citations
49 papers · 572 · h-index 12

Impact in

Papers in

    • Multiple Myeloma Research and Treatments 19
    • Chronic Myeloid Leukemia Treatments 7
    • CAR-T cell therapy research 11

Stephen Lim

47 papers receiving 559 citations

Peers

Stephen Lim
Comparison fields: 5 of 55
  • Genetics 141
  • Endocrinology, Diabetes and Metabolism 186
  • Hematology 117
  • Oncology 159
  • Cancer Research 32
Replace Livia Hegerova with:
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Mufaddal Moonim United Kingdom
S Khorana United States
Alexandre Kaliski France
Carlo Alberto Giorgi Italy
Anjum Hassan United States
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Edward R. Scheffer Cliff United States
Jacob Garcia United States
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Citations per field
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Citations per year

Countries citing papers authored by Stephen Lim

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006135
2 201364
3 201259
4 202356
5 200727
6 202025
7 200018
8 202215
9 200213
10
Mutation detection using plasma circulating tumor DNA (ctDNA) in a cohort of asymptomatic adults at increased risk for cancer.
201812
11 201711
12 201411
13 202110
14 20119
15 20209
16 20229
17 20229
18 19987
19 20227
20 19966

About Stephen Lim

Stephen Lim is a scholar working on Hematology, Oncology, Genetics, Molecular Biology and Immunology, having authored 49 papers that have together received 572 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (19 papers), CAR-T cell therapy research (11 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (8 papers), Chronic Myeloid Leukemia Treatments (7 papers), Protein Degradation and Inhibitors (4 papers), Chronic Lymphocytic Leukemia Research (4 papers), Immunotherapy and Immune Responses (3 papers) and Biosimilars and Bioanalytical Methods (3 papers). The work is most often cited by research in Genetics (141 citations), Endocrinology, Diabetes and Metabolism (186 citations), Hematology (117 citations), Oncology (159 citations) and Cancer Research (32 citations). Stephen Lim has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Anthony P. Heaney, Hrayr K. Shahinian, William H. Yong, Rakesh Awasthi, Jie Zhang, Harald J. Maier, Anat Ben-Shlomo, Odelia Cooper, Adam N. Mamelak and Galen Cook‐Wiens. Their work appears in journals such as Blood, Journal of Clinical Oncology, Cancer, Clinical Cancer Research and Experimental Hematology.

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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