Qingbin Song, MD
- ASSISTANT PROFESSOR | Medicine, Nephrology
Dr. Song is a scientist in computational biology. He has double degrees: medicine and computer science, and was well trained on Molecular Biology, Genetics and Computer Science. He has extensive experience in experimental biology and database management. His current goal is to develop a robust information management system on clinical specimen repository for personalized medicine.
He serves as a Director of IT Core Lab in the institute, develops and manages the Laboratory Information Management System (LIMS), integrates biomedical instruments into LIMS and automates the sample extraction and tracking pipeline.
Dr. Song is a Co-Investigator of the NIDDK-funded U01 grant ‘New York CKD Biomarker Program’.
MD, Harbin Medical University
Heilongjiang Health Institute
MS, City University of New York
Albert Einstein College of Medicine
Integration of the custom database with the GeneTraffic (Microarray) database
Digital data from biological instruments will be automated and transformed into a central database system using the BioExper system, and QTL MATCHMAKER database, a tool that enables high throughput mappings of genes and large scale comparative genomic analysis between Homo sapiens, Mus musculus, and Rattus norvegicus. Applications carried out to date include the development of Animal Inventory and Reagent Management modules.
Development of a Computer Managed Comprehensive Platform (BioExper)
Cutting-edge technology will be employed to develop a web-based platform, including JAVA programming language, XML, Oracle database etc. The system will store research data in a central database system, and captures experimental data at single experimental steps. The system will enable easier and more efficient communication of data between medical researchers and provide a data analysis tool.
- Sample tracking and specimen repository management
- Next-generation sequencing data analysis
- Biomedical instruments integration into LIMS