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Sato Lab
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The lab is a bioinformatics lab that reads genetic information through information theory.
AboutAbout the lab
Reading genetic information through information theory.
The Sato Lab does research in bioinformatics, using ideas from information theory to study biological phenomena from the information carried in genes and DNA.
Through basic concepts such as information content and codes, the lab considers how biological information is transmitted and processed, and the mathematics that describes the dynamics of biological change.
To detect intractable cancers early and build a foundation for developing molecularly targeted therapy, the lab also studies the relationship between patterns of gene expression and mutation and the course of disease.
Key terms
- Bioinformatics
- A research field that uses information-theoretic methods to elucidate biological phenomena.
- Code
- Information expressed in a fixed arrangement of symbols. A DNA sequence made up of four bases can also be regarded as a kind of code.
- Prognostic factor
- A factor that affects the course or outcome of a disease.
ResearchResearch themes
The lab considers that biological information is stored as nucleotide sequences, treats these sequences as codes, and studies biological phenomena using coding theory and information-theoretic methods. It works on predicting changes in influenza virus sequences and identifying prognostic factors in cancer.
Predicting influenza virus mutations
Using coding theory, the lab examines the sequences of the receptor-binding region of hemagglutinin in influenza A virus to understand the rules stored there. It then changes sequences according to those rules to predict sequences that are likely to appear in the future.
*Illustrative imageIdentifying prognostic factors in breast cancer
To build a foundation for early detection of intractable breast cancer and development of molecularly targeted therapy, the lab considers how to handle clinical information together with expression and mutation data for more than 20,000 genes. Using information-theoretic methods, it is working to identify prognostic factors that affect disease outcome.
MembersFaculty
- ProfessorKeiko Sato
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Influenza virus particle color” Photo Credit: Cynthia Goldsmith Content Providers(s): CDC/ Dr. Erskine. L. Palmer; Dr. M. L. Martin / Public domain (cropped)
- Identifying prognostic factors in breast cancer: “X-ray of ultrasound-guided marking of breast cancer 2” Jmarchn / CC BY-SA 3.0 (cropped)
- Related lab (植松研究室): “Inside a card catalog at the Indiana State Library - ask the librarian” TBurmeister (WMF) / CC BY-SA 4.0 (cropped)
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