In Sock Jang
Impact in
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- Cancer Genomics and Diagnostics
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- Computational Drug Discovery Methods
Papers in
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- Protein Degradation and Inhibitors 6
- Gene expression and cancer classification 3
- Molecular Biology Techniques and Applications 3
- Bioinformatics and Genomic Networks 3
- Ubiquitin and proteasome pathways 2
- Single-cell and spatial transcriptomics 2
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- Multiple Myeloma Research and Treatments 4
- Co-authors
- Stephen Friend (4 shared papers)Adam A. Margolin (3 shared papers)Elias Chaibub Neto (3 shared papers)Justin Guinney (4 shared papers)Rodrigo Dienstmann (2 shared papers)Carla Grandori (3 shared papers)Brian M. Bot (1 shared paper)Silvia Cermelli (1 shared paper)
- Journals
- Blood (3 papers)Clinical Cancer Research (2 papers)Cold Spring Harbor Perspectives in Medicine (2 papers)Blood Advances (1 paper)Computer applications in the biosciences (1 paper)
- Partner nations
- United StatesGermanySouth Africa
In The Last Decade
In Sock Jang
20 papers receiving 645 citations
Peers
Comparison fields: 5 of 73
- Cancer Research 127
- Computational Theory and Mathematics 114
- Molecular Biology 450
- Oncology 137
- Biophysics 20
Countries citing papers authored by In Sock Jang
This map shows the geographic impact of In Sock Jang'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 In Sock Jang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites In Sock Jang more than expected).
Fields of papers citing papers by In Sock Jang
This network shows the impact of papers produced by In Sock Jang. 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 In Sock Jang. The network helps show where In Sock Jang may publish in the future.
Co-authors
The 25 scholars most cited alongside In Sock Jang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Systematic assessment of analytical methods for drug sensitivity prediction from cancer cell line data. | 2014 | 127 |
| 2 | 2015 | 88 | |
| 3 | 2005 | 71 | |
| 4 | 2014 | 66 | |
| 5 | 2018 | 56 | |
| 6 | 2014 | 55 | |
| 7 | 2013 | 40 | |
| 8 | 2006 | 25 | |
| 9 | 2013 | 23 | |
| 10 | 2013 | 20 | |
| 11 | 2018 | 19 | |
| 12 | 2021 | 15 | |
| 13 | 2007 | 15 | |
| 14 | 2014 | 9 | |
| 15 | 2021 | 8 | |
| 16 | 2019 | 7 | |
| 17 | 2021 | 5 | |
| 18 | 2014 | 5 | |
| 19 | 2018 | 2 | |
| 20 | 2022 | 2 |
About In Sock Jang
In Sock Jang is a scholar working on Molecular Biology, Hematology, Pathology and Forensic Medicine, Oncology and Cancer Research, having authored 20 papers that have together received 658 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (6 papers), Multiple Myeloma Research and Treatments (4 papers), Cancer Genomics and Diagnostics (3 papers), Gene expression and cancer classification (3 papers), Molecular Biology Techniques and Applications (3 papers), Bioinformatics and Genomic Networks (3 papers), Ubiquitin and proteasome pathways (2 papers) and Single-cell and spatial transcriptomics (2 papers). The work is most often cited by research in Cancer Research (127 citations), Computational Theory and Mathematics (114 citations), Molecular Biology (450 citations), Oncology (137 citations) and Biophysics (20 citations). In Sock Jang has collaborated with scholars based in United States, Germany and South Africa. Frequent co-authors include Stephen Friend, Adam A. Margolin, Elias Chaibub Neto, Justin Guinney, Rodrigo Dienstmann, Carla Grandori, Brian M. Bot, Silvia Cermelli, Brady Bernard and Jong Bhak. Their work appears in journals such as Blood, Clinical Cancer Research, Cold Spring Harbor Perspectives in Medicine, Blood Advances and Computer applications in the biosciences.
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.