Sinotools: a computational framework to analyze cancer genomic sequencing data for precision oncology

Abstract

We have developed a computational framework called Sinotools to analyze cancer genomic sequencing data for precision oncology. First of all, Sinotools can identify very low-frequency variants in ctDNA samples from cancer patients using duplex barcode sequencing technology. Sinotools also includes a novel computational algorithm to identify actionable gene fusion events from targeted sequencing data. Sinotools is available at https://github.com/SinOncology.

Biography

Prof. Bingding Huang received his BSc in Cell Biology from University of Science and Technology of China in 2002. Then he received his Master degree in Computer Science from Saarland University and Max Planck Institute for Informatics under Scholarship from International Max Planck Research School in 2004. Afterwards, he joined the Bioinformatics group in Technical University of Dresden where he received his PhD (Dr.ret.nat) in Computer Science from the Computer Science department in 2007. Then he joined the Molecular and Cellular Modeling group in Heidelberg Institute for Theoretical Studies for one year postdoc training. From 2009 to 2012 he was a Adjunct Associate Professor in Division of Systems Biology, Zhejiang-California International NanoSystems Institute, Zhejiang University China. From 2012 to 2015 Dr. Huang worked as a Bioinformatics Scientist in German Cancer Research Center Heidelberg. Then from 2015 to 2017 he worked as a Senior Computational Biologist in Neo New Oncology AG (Part of Siemens Healthineers). Afterwards, he joined Sinotech Genomics Inc. Shanghai as Vice President of Research and Development and Head of Bioinformatics. Recently Dr. Huang joined the College of Big Data and Internet, Shenzhen University as a full Professor in Bioinformatics and Big data.