# Xiao Liang

> master of Computer Science & Engineering, University of Washington, 2017

**Wikidata**: [Q113667874](https://www.wikidata.org/wiki/Q113667874)  
**Source**: https://4ort.xyz/entity/xiao-liang

## Summary
Xiao Liang is a computer scientist who earned a master's degree in Computer Science & Engineering from the University of Washington in 2017. Their research focused on integrating biological knowledge with computational approaches to regulatory network construction, completing their thesis under the guidance of Ka Yee Yeung.

## Biography
- Born: 1991
- Nationality: Not specified
- Education: Master's degree in Computer Science & Engineering, University of Washington, 2017
- Known for: Research in computational biology and regulatory networks
- Employer(s): Not specified
- Field(s): Computer science, computational biology

## Contributions
Xiao Liang's primary contribution is their 2017 master's thesis titled "Integrating External Biological Knowledge in the Construction of Regulatory Networks from Lincs Data." This work explored methodologies for incorporating biological domain knowledge into computational approaches for constructing regulatory networks. The thesis specifically examined how to leverage the Lincs (Library of Integrated Network-based Cellular Signatures) database to enhance regulatory network analysis by integrating external biological knowledge, potentially improving the accuracy and biological relevance of network inference methods.

## FAQs
### Q: What is Xiao Liang's educational background?
A: Xiao Liang earned a master's degree in Computer Science & Engineering from the University of Washington in 2017.

### Q: Who was Xiao Liang's academic advisor?
A: Xiao Liang was advised by Ka Yee Yeung during their studies at the University of Washington.

### Q: What was the focus of Xiao Liang's research?
A: Their research focused on integrating external biological knowledge into the construction of regulatory networks, particularly using data from the Lincs database.

### Q: What did Xiao Liang's thesis specifically address?
A: Their thesis explored methodologies for incorporating biological domain knowledge into computational approaches for constructing regulatory networks.

## Why They Matter
Xiao Liang's work contributes to the intersection of computer science and computational biology by addressing challenges in regulatory network construction. Their research on integrating biological knowledge with computational methods represents an important approach to improving the accuracy and biological relevance of network inference. By focusing on the Lincs database, they contributed to methodologies that could enhance our understanding of cellular regulatory mechanisms, potentially advancing research in systems biology, disease modeling, and drug discovery. Their work exemplifies how computational approaches can be strengthened by incorporating domain-specific biological knowledge.

## Notable For
- Master's degree in Computer Science & Engineering from University of Washington, 2017
- Research focusing on integrating biological knowledge with computational approaches to regulatory networks
- Completion of thesis under guidance of Ka Yee Yeung
- Contribution to computational methodologies using Lincs data
- Focus on enhancing regulatory network construction through biological knowledge integration

## Body

### Early Life and Education
Xiao Liang was born in 1991 and pursued higher education in computer science and engineering. They completed their master's degree at the University of Washington in 2017, specializing in the intersection of computational methods and biological data analysis.

### Academic Research
Xiao Liang's academic work focused on computational biology, specifically addressing challenges in regulatory network construction. Their research explored methodologies for integrating external biological knowledge with computational approaches to improve network inference. Their 2017 thesis, "Integrating External Biological Knowledge in the Construction of Regulatory Networks from Lincs Data," examined how to leverage the Library of Integrated Network-based Cellular Signatures (Lincs) database to enhance regulatory network analysis.

### Academic Advisor and Mentorship
During their studies at the University of Washington, Xiao Liang worked under the guidance of Ka Yee Yeung. This mentorship shaped their research approach in computational biology, particularly in the area of integrating biological domain knowledge into computational frameworks for network analysis.

## References

1. WorldCat