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Hsiao-Fang Sunny Sun

dblp:68/4148 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-3661-4448ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › cancer genomics › cancer driver gene identification
oncogene identification
0.212013
In silico identification of oncogenic potential of fyn-related kinase in hepatocellular carcinoma · Bioinform. 2013

Methods — techniques the papers use, named apart from their topics

tumor-associated gene database · 0.2computational prediction · 0.2
YearPublicationVenuePosition
2022 Editorial
abstract
Presents the introductory editorial for this issue of the publication.
Hsiao-Fang Sunny Sun, Yi-Ping Phoebe Chen
IEEE ACM Trans. Comput. Biol. Bioinform.1
2013 In silico identification of oncogenic potential of fyn-related kinase in hepatocellular carcinoma
abstract
MOTIVATION: Cancer development is a complex and heterogeneous process. It is estimated that 5-10% of human genes probably contribute to oncogenesis, whereas current experimentally validated cancer genes only cover 1% of the human genome. Thus hundreds of cancer genes may still remain to be identified. To search for new genes that play roles in carcinogenesis and facilitate cancer research, we developed a systematic workflow to use information saved in a previously established tumor-associated gene (TAG) database. RESULTS: By exploiting the information of conserved protein domains from the TAG, we identified 183 potential new TAGs. As a proof-of-concept, one predicted oncogene, fyn-related kinase (FRK), which shows an aberrant digital expression pattern in liver cancer cells, was selected for further investigation. Using 68 paired hepatocellular carcinoma samples, we found that FRK was up-regulated in 52% of cases (P < 0.001). Tumorigenic assays performed in Hep3B and HepG2 cell lines revealed a significant correlation between the level of FRK expression and invasiveness, suggesting that FRK is a positive regulator of invasiveness in liver cancer cells. CONCLUSION: These findings implied that FRK is a multitalented signal transduction molecule that produces diverse biological responses in different cell types in various microenvironments. In addition, our data demonstrated the accuracy of computational prediction and suggested that other predicted TAGs can be potential targets for future cancer research. AVAILABILITY: The TAG database is available online at the Bioinformatics Center website: http://www.binfo.ncku.edu.tw/TAG/.
Jia-Shing Chen, Wei-Shiang Hung, Hsiang-Han Chan, Shaw-Jenq Tsai, Hsiao-Fang Sunny Sun
Bioinform.5