Soyeon Kim
Pittsburgh,PA
Summary
Skilled Researcher enthusiastic about researching cancer, especially in precision medicine.
Expert in multi-omics data analyses using statistical and computational methods. Detail-oriented and methodical professional successful in developing in-depth research projects. Reliable team player with excellent communication and problem-solving skills.
Overview
13
13
years of professional experience
Work History
Research Assistant Professor
University Of Pittsburgh
08.2020 - Current
- Obtained NIH K01 grant as a Principal Investigator for 5 years.
- Designed and conducted integrative analyses of multi-omics data (e.g. genotype, DNA methylation, and gene expression) to uncover pathogeneses of a disease
- Developed deep learning methods to 1) better cluster cell types in single-cell RNA seq, 2) infer non-linear causality among clinical and molecular features, and 3) predict phenotypes using DNA methylation.
- Published 12 peer-reviewed papers and presented at ASHG and ATS conferences.
- Mentored 5 Ph.D. or Master students to conduct research and career advice.
- Reviewed 10 articles in peer-reviewed journals as a reviewer
Postdoctoral Research Scholar
University Of Pittsburgh
06.2018 - 06.2020
- Received NIH T32 award for 2 years
- Researched causal relationship among GWAS SNPs, DNA methylation, and gene expression
- Researched interactions between miRNA and mRNA in breast cancer
- Published 5 peer-reviewed papers and invited to a session at an ATS conference.
- Collaborated with 16 multidisciplinary team members to acquire, generate, and analyze multi-omics data.
Postdoctoral Research Fellow
University Of Texas Health Science Center At Houston
12.2016 - 12.2017
- Developed statistical machine learning models to predict gene expression using long-range regulatory elements using epigenetic data in pan-cancer
- Predicted five-year survival of breast cancer patients and other phenotypes using the predicted gene expression
- Liaised with the advisor to review grants and manuscripts to develop potential publications.
- Pursued independent and complementary research interests.
- Mentored a Ph.D. student in implementing statistical models, writing R codes, and writing a manuscript
Graduate Research Assistant
University Of Texas MD Anderson Cancer Center
06.2010 - 12.2015
- Developed a novel statistical learning method, Prediction Oriented Marker Selection (PROMISE), to identify predictive and prognostic biomarkers and predict outcomes of treatments in high dimensional data for personalized medicine.
- Integrated BATTLE (Biomarkers-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination) trial data and patients' gene expression data for data analysis.
- Won the Student Paper Award Competition hosted by the American Statistical Association (ASA) Biopharmaceutical Section
- Conducted research independently given the research topic and wrote manuscripts
Education
Ph.D. - Statistics
Rice University
Houston, TX12.2015
Master of Arts - Statistics
Rice University
Houston, TX05.2013
Bachelor of Arts - Applied Statistics
Yonsei University
Seoul, South Korea02.2008
Skills
- High-throughput Transcriptomic, Genomic, and Epigenetic data analysis
- High-dimensional data analysis
- Machine Learning
- Bioinformatics
- R
- Biostatistics
- Data visualization
- Cancer research
- Manuscript and grant writing
Selected Publications
- Kim S, Xu Z, Forno E, Qin Y, Park HJ, Yue M, Yan Q, Manni ML, Acosta-Pérez E, Canino G, Chen W. Cis-and trans-eQTM analysis reveals novel epigenetic and transcriptomic immune markers of atopic asthma in airway epithelium. Journal of Allergy and Clinical Immunology. 2023 Oct 1;152(4):887-98.
- Fan Z, Kernan KF, Sriram A, Benos PV, Canna SW, Carcillo JA, Kim S*, Park HJ*. Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems. GigaScience. 2023;12:giad044.
- Bai Y, Qin Y, Fan Z, Morrison RM, Nam K, Zarour HM, Koldamova R, Padiath QS, Kim S*, Park HJ*. scMAPA: Identification of cell-type–specific alternative polyadenylation in complex tissues. GigaScience. 2022;11:giac033.
- Kim S, Bai Y, Fan Z, Diergaarde B, Tseng GC, Park HJ. The microRNA target site landscape is a novel molecular feature associating alternative polyadenylation with immune evasion activity in breast cancer. Briefings in Bioinformatics. 2021 May;22(3):bbaa191.
- Kim S, Forno E, Zhang R, Park HJ, Xu Z, Yan Q, Boutaoui N, Acosta-Pérez E, Canino G, Chen W, Celedón JC. Expression quantitative trait methylation analysis reveals methylomic associations with gene expression in childhood asthma. Chest. 2020 Nov 1;158(5):1841-56.
- Kim S, Forno E, Yan Q, Jiang Y, Zhang R, Boutaoui N, Acosta-Pérez E, Canino G, Chen W, Celedón JC. SNPs identified by GWAS affect asthma risk through DNA methylation and expression of cis-genes in airway epithelium. European Respiratory Journal. 2020 Apr 1;55(4).
- Kim S, Park HJ, Cui X, Zhi D. Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer. Scientific reports. 2020 Mar 3;10(1):3920.
- Park HJ, Ji P, Kim S, Xia Z, Rodriguez B, Li L, Su J, Chen K, Masamha CP, Baillat D, Fontes-Garfias CR. 3′ UTR shortening represses tumor-suppressor genes in trans by disrupting ceRNA crosstalk. Nature genetics. 2018 Jun;50(6):783-9.
- Kim S, Baladandayuthapani V, Lee JJ. P rediction-O riented M arker S election (PROMISE): With Application to High-Dimensional Regression. Statistics in biosciences. 2017 Jun;9:217-45.
* co-corresponding author
Timeline
Research Assistant Professor
University Of Pittsburgh
08.2020 - Current
Postdoctoral Research Scholar
University Of Pittsburgh
06.2018 - 06.2020
Postdoctoral Research Fellow
University Of Texas Health Science Center At Houston
12.2016 - 12.2017
Graduate Research Assistant
University Of Texas MD Anderson Cancer Center
06.2010 - 12.2015
Ph.D. - Statistics
Rice University
Master of Arts - Statistics
Rice University
Bachelor of Arts - Applied Statistics
Yonsei University
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