Information

Advanced Data Science

Ueda Laboratory
Material

We are researching methods using data science, such as BIGDATA analysis andmachine learning, to analyze biological data and aim to discover new life phenomena.

Project Lecturer

Hiroki UEDA

Life Information Analysis Using Data Science

Research Area

Project Associate Professor

Shingo TSUJI
Research Area

Machine Learning, Bioinformatics

Project Research Associate

Social Science

Dasgupta BHASKAR
ColumnAt the Ueda Laboratory, we are primarily focusedLaboratory forInterdiciplinary Activities

on "RNA modification using nanopore
sequencers," but we are also working on avariety of other themes. We actively engage incollaborative research with other fields within theAdvanced Science Research Center as well as

Cooperative Laboratories

with other research institutions. We aim toadvance research using AI in numerous fields,
including biology.I used to think that computerscience was a field led by theory since Turing,
but deep learning feels more like the steam

Social Cooperation
Research Departments

2Barrier Free

With the accumulation of large amounts of digital data and the evolution of machinelearning algorithms, mathematical methods can now be applied to solve problems invarious fields. In our laboratory, we are also conducting research on drug
repositioning using Graph Neural Networks, and knowledge graph construction andits applications using large-scale language models (LLM) based on Transformermodels. Knowledge about AI and data science grows and changes constantly,
making it a difficult problem to build educational programs with a complete picture. If
we can represent and visualize the spread and dependencies of knowledge in aknowledge graph, it can be applied in various ways. In our laboratory, we areresearching how to construct such knowledge graphs semi-automatically by using
LLM and large-scale data. In addition, we are promoting Project CDDI (CrossDisciplinary Data Initiative), aimed at leading and supporting data-driven research,education, and social implementation by linking seven research areas through datascience.

Chemical Biomedicine

Problem Solving with Mathematical Methods

Bioinformatics, Data ScienceInformation

We are developing informatics methods to analyze high-throughput measurement
data obtained from next-generation sequencers. Recently, it has become difficult toprocess large amounts of biological data using conventional methods. Furthermore,to integrate data of different dimensions (multi-omix, muilti-modal data), it is essential
to incorporate the latest results of big data analysis techniques and machine learning.
The applications of next-generation sequencing and bioinformatics are diverse, but
we are conducting research in the following areas while also developing software:
・Data analysis for nanopore sequencers: We are developing deep learning software
to detect RNA modifications from the wave current signals of nanopore sequencers
and are conducting various RNA modification detections. RNA modifications areinvolved in various life phenomena and are also advancing in mRNA drugdevelopment.
・Drug Repositioning: The development of a new drug may require an investment ofseveral hundred billion yen, and it is especially difficult to develop new drugs for rarediseases. Although various methods have been proposed for drug repositioning
research, we are developing a new method to apply Graph Attention Autoencoder tolarge multimordal graphs with drug, protein, and disease nodes.

1

Environment and Energy

Deciphering Life Phenomena with
Data Science Technology

engine era where the machines were developed
before the theory was fully established. It feels
like we have returned to the 18th century in astrange way, with a lot of chaos andCorporate SponsoredResearch Programs

experimentation. Perhaps such transitions arealways messy.This is unrelated to my research,
but I recently enjoyed reading the original book of
the Oppenheimer movie and a book on polyvagal
theory. In any case, if you are interested, let's

Research Organization

research together. Please feel free to contact me.

3

http://www.biods.rcast.u-tokyo.ac.jp/
ueda@biods.rcast.u-tokyo.ac.jp

1 Detection of different RNA modifications on rRNA

tsuji@genome.rcast.u-tokyo.ac.jp

2 Detection of m6A modification on each Read
3 Knowledge Graph Created Using LLM

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