Carousel imageCarousel image

Hi, I am Pei-Chen Peng. I am a postdoctoral scientist at Cedars-Sinai Medical Center, working with Dr. Simon Gayther in the Center for Bioinformatics and Functional Genomics. My research interest lies in computational genomics. I use statistical and machine learning methods, to understand problems in molecular biology and cancer genomics. My work focuses specifically on linking genetic variation in regulatory region to phenotype.

I obtained my Ph.D. in Computer Science from University of Illinois at Urbana-Champaign (UIUC) in 2018, advised by Prof. Saurabh Sinha. I hold a M.S. and a B.S. in Computer Science from National Taiwan University in 2013 and 2011 respectively. I received a Google Anita Borg Award in 2012 and a Grace Hopper Celebration Scholarship in 2016.

Research Interests

Bioinformatics and Computational Biology, developing and applying computational methods to understand problems in biology, genomics, and medicine.


Cedars-Sinai Medical Center, CA, USA | 2019-present
Postdoctoral Scientist in Biomedical Sciences
Mentor: Dr. Simon Gayther

University of Illinois at Urbana-Champaign, IL, USA | 2013-2018
Ph.D. in Computer Science
Advisor: Prof. Saurabh Sinha

National Taiwan University, Taipei, Taiwan
M.S. in Computer Science and Information Engineering | 2011-2013
B.S. in Computer Science and Information Engineering | 2007-2011
GPA 4.0/4, National Taiwan University Presidential Award

Honors and Awards



  • Accomplishing Career Transitions Program | American Society of Cell Biology 2019

  • HHMI International Student Research Fellowship Finalist | HHMI 2016

  • Grace Hopper Celebration Scholarship | Anita Borg Institute, 2015 and 2016

  • Study Abroad Scholarship | Ministry of Education, Taiwan, 2013

  • Google Anita Borg Memorial Scholarship| Google Inc., 2012

  • Presidential Award | National Taiwan University, 2007

Travel Grants/Conference Scholarships:

  • ISMB | 2020

  • ASCB/EMBO | 2019 and 2020

  • CRA-W Early Career Mentoring Workshops | Computing Research Association, 2018 and 2020

  • CRA-W Grad Cohort Workshop | Computing Research Association, 2016


Articles Under Review in Journals (*equal contribution)

1. N. Gull*, M. R. Jones*, P.-C. Peng*, S. G. Coetzee, T. C. Silva, J. T. Plummer, ... & S. Gayther. (2020). DNA methylation landscapes of matched primary and recurrent high grade serous ovarian cancers are preserved throughout disease progression and chemoresistance. bioRxiv (2020): 10.1101/2020.02.21.960468. Under Review in Cell Genomics

Articles in Peer-Reviewed Journals (*equal contribution)

2. M. R. Jones*, P.-C. Peng*, S. G. Coetzee, J. Tyrer, A. L. Reyes, R. I. Corona, B. Davis, S. Chen, F. Dezem, J.-H. Seo, Ovarian Cancer Association Consortium, B. P. Berman, M. Freedman, J. T. Plummer, K. Lawrenson, P. Pharoah, D. J. Hazelett, S. A. Gayther. Ovarian Cancer Risk Variants are Enriched in Histotype-Specific Enhancers that Disrupt Transcription Factor Binding Sites. American Journal of Human Genetics. 2020, 107(4):622-635

3. P.-C. Peng, P. Khoueiry, C. Girardot, J. P. Reddington, D. A. Garfield, E. E. M. Furlong, S. Sinha, The Role of Chromatin Accessibility in cis-Regulatory Evolution. Genome biology and evolution 11.7 (2019): 1813-1828.

4. P. Khoueiry, C. Girardot, L. Ciglar, P.-C. Peng, H. E. Gustafson, S. Sinha, E. E. M. Furlong, Uncoupling Evolutionary Changes in DNA Sequence, Transcription Factor Occupancy and Enhancer Activity. eLife, 2017, 6:e28440

5. P.-C. Peng and S. Sinha, Quantitative Modeling of Gene Expression Using DNA Shape Features of Binding Sites. Nucleic Acids Research, 2016, 44(13): e120 *Nominated for top 10 papers in RECOMB/RSG 2016

6. P.-C. Peng, M.A.H. Samee, S. Sinha, Incorporating Chromatin Accessibility Data into Sequence-to-Expression Modeling. Biophysical Journal, 2015, 108(5):1257-1267

7. H.-C. Liu, P.-C. Peng, T.-C. Hsieh, T.-C. Yeh, C.-J. Lin, C.-Y. Chen, J.-Y. Hou, L.-Y. Shih, and D.-C. Liang, Comparison of Feature Selection Methods for Cross-Laboratory Microarray Analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2013, 10(3):593-604


8. P.-C. Peng, Quantifying the functional and evolutionary relationships among sequences, transcription factor binding and gene expression. Ph.D. Thesis. University of Illinois at Urbana-Champaign, 2018.

9. P.-C. Peng, Gene Regulatory Network Inference and Complex Phenotype Prediction from Genetical Genomics Data. M.S. Thesis. National Taiwan University, 2013.

Teaching and Mentoring Experiences

Cedars-Sinai Medical Center, CA, USA
Guest lecturer, BMS 510 Human Genetics and Genomics | 2019 and 2021

American Society of Cell Biology
Mentor, Innovative Programs to Enhance Research Training (IPERT) initiative | 2019

Mayo Clinic and UIUC Alliance, MN/FL and IL, USA
Leading Teaching Assistant, Computational Genomics Course | 2015-2017

University of Illinois at Urbana-Champaign, IL, USA
Teaching Assistant, CS 466 Introduction to Bioinformatics | 2016
Mentor, Passionate on Parallel Research Experience for Undergraduates (REU) | 2014

National Taiwan University, Taipei, Taiwan
Teaching Assistant, CSIE 1212 Data Structure and Algorithm | 2012
Teaching Assistant, CSIE 2136 Algorithm Design and Analysis | 2011

Selected Conference Presentations

1. Integrating genetic fine-mapping and functional genomics to prioritize credible causal risk variants for epithelial ovarian cancer. (poster) ASHG, virtual, 2020. *Reviewer’s Choice Award.

2. Prioritizing credible causal risk variants for epithelial ovarian cancer by genomic and epigenomic annotation analyses. (poster) ISMB, virtual, 2020.

3. Functional enrichment of ovarian cancer GWAS risk SNPs. (talk) Ovarian Cancer Satellite Meeting, MD Anderson Cancer Center, 2019.

4. Partitioned heritability and functional enrichment reveal ovarian cancer risk variants in histotype-specific enhancers that disrupt transcription factor binding sites. (poster) ASHG, Houston, TX, 2019. *Reviewer’s Choice Award.

5. Quantifying the relationships among evolutionary changes in sequence, accessibility, TF binding and regulatory activity of enhancers of a well characterized developmental system. (talk) CSHL conference on Systems Biology: Global Regulation of Gene Expression, Cold Spring Harbor, NY, 2017

6. Quantitative modeling of gene expression from sequence, using DNA shape-based model of binding sites. (talk & poster) RECOMB/ISCB RSG, Philadelphia, PA, 2015

7. The role of chromatin accessibility in thermodynamics-based model of transcriptional regulation by enhancers. (poster) ISMB Regulatory Genomics SIG, Boston, MA, 2014