Xiaopeng Bian, Ph.D.

Staff Scientist

Biography

Dr. Xiaopeng Bian is a bioinformatics specialist at CBIIT and has spent his twenty-year tenure focusing on caArray, protExpress, CPAS, CTD2, and PID. He has developed and maintained project websites, provided technical and scientific expertise, and served as a liaison to the cancer research community. Currently, Dr. Bian is working on high throughput genomic data analysis under a high-performance parallel computing environment in supporting intramural and extramural research, such as the Department of Cancer Epidemiology and Genetics and the Center for Cancer Research. He performs basic and advanced analysis of data produced from next generation sequencing systems (DNA-seq, RNA-seq, exome, whole genome, and ChIP-seq, etc.). Dr. Bian graduated from Tianjin Medical College in China and earned his doctorate degree from Duke University.

Projects

  • APOLLO

Publications

  • Comparing the performance of selected variant callers using synthetic data and genome segmentation. Bian X, Zhu B, Wang M, Hu Y, Chen Q, Nguyen C, Hicks B, Meerzaman D. BMC Bioinformatics. 2018 Nov 19;19(1):429. doi: 10.1186/s12859-018-2440-7.
  • SomaticCombiner: improving the performance of somatic variant calling based on evaluation tests and a consensus approach. Wang M, Luo W, Jones K, Bian X, Williams R, Higson H, Wu D, Hicks B, Yeager M, Zhu B. Sci Rep. 2020 Jul 30;10(1):12898. doi: 10.1038/s41598-020-69772-8.
  • Landscape of Germline Genetic Variants in AGT, MGMT, and TP53 in Mexican Adult Patients with Astrocytoma. Carlos-Escalante JA, Gómez-Flores-Ramos L, Bian X, Perdomo-Pantoja A, de Andrade KC, Mejía-Pérez SI, Cacho-Díaz B, González-Barrios R, Reynoso-Noverón N, Soto-Reyes E, Sánchez-Correa TE, Guerra-Calderas L, Yan C, Chen Q, Castro-Hernández C, Vidal-Millán S, Taja-Chayeb L, Gutiérrez O, Álvarez-Gómez RM, Gómez-Amador JL, Ostrosky-Wegman P, Mohar-Betancourt A, Herrera-Montalvo LA, Corona T, Meerzaman D, Wegman-Ostrosky T. Cell Mol Neurobiol. 2020 Jun 13. doi: 10.1007/s10571-020-00901-7. Online ahead of print.