Keynote Talk
Keynote Talk 1
23rd Oct. 10:30-11:30 Large Theatre

Prediction of cancer-associated metabolites and theirapplication for drug targeting system

Hyun Uk Kim
Department of Chemical and Biomolecular Engineering andGraduate School of Engineering Biology,
Korea Advanced Institute of Science and Technology (KAIST)The utilization of bio big data through computational models can help predict
biomarkers and drug targets for a range of diseases. In the case of cancer, asubstantial amount of bio big data has been deposited, including patientspecific omics data (e.g., RNA-seq data) and medical data (e.g., survival data).
In this talk, I will elaborate a computational workflow where transcriptome andmutation data from cancer patients, along with genome-scale metabolicmodels (GEMs), have been used to predict potential biomarkers known as
oncometabolites. Oncometabolites exhibit pro-oncogenic functions when they
accumulate abnormally in cancer cells, and they are generated upon mutations
in a metabolic gene. GEM is a computational model that allows predicting
entire metabolic reaction fluxes. I will also showcase the application of thiscomputational workflow to predict drug targets effective for high-risk bladdercancer patients, showing poor prognosis. The predicted drug targets werevalidated using in vitro and in vivo studies. Ongoing efforts in generating andapplying meaningful bio big data, alongside the proper use of computationalmodels, will revolutionize our approaches to addressing medical problems.

Keynote Talk 2
24th Oct. 9:30-10:30 Large Theatre

How far are we from designing an antibody therapeutic
on a computer?

Charlotte Deane MBE
Professor of Structural Bioinformatics, University of Oxford

Antibodies play a key role in the immune system and our response tovaccines, and have shown great promise as biotherapeutics. The developmentof new biotherapeutics typically takes many years and requires over $1bn ininvestment. Computational methods and in particular, machine learning, haveshown great promise for increasing the speed and reducing the cost ofbiotherapeutic development. In this talk I will describe some of the novel
computational tools and databases we are pioneering in biotherapeutics fromaccurate rapid structure prediction to the prediction of their affinity andbinding, looking at both their promise and limitations.

Keynote Talk 3
24th Oct. 13:45-14:45 Large Theatre

Evolution of SARS-CoV-2 and beyond

Kei SatoProfessor, Division of Systems Virology, Institute of Medical Science,
The University of Tokyo, Japan.
Representative Director, G2P-Japan Association

SARS-CoV-2, the causative agent of COVID-19, emerged at the end of 2019.
During its global spread over the past 3 years, SARS-CoV-2 has been highly
diversified, and these SARS-CoV-2 variants have been considered to be thepotential threats to the human society. In order to elucidate the virologicalcharacteristics of newly emerging SARS-CoV-2 variants in real-time, I launched
a consortium called “The Genotype to Phenotype Japan (G2P-Japan)” inJanuary 2021. With the colleagues who joined the G2P-Japan consortium, we
have revealed the virological characteristics of SARS-CoV-2 variants. In May2023, WHO declared the end of the Public Health Emergency of International
Concern (PHEIC) for COVID-19. However, “the next pandemic” will come in thefuture, and we need to gather our wisdom learned from the COVID-19
pandemic for the preparedness of future pandemic. Here, I will talk about ourfindings on SARS-CoV-2 variants and future perspectives to combat theoutbreaks and pandemic that will happen in the future.

Keynote Talk 425th Oct. 9:30-10:30 Large Theatre

Using bioinformatics to identify new regulatory mechanisms
related to RNA m6A modification

Xiujie Wang
Institute of Genetics and Developmental Biology,
Chinese Academy of Sciences

The application of various types of omics studies has produced huge amountof data,which enabled researchers to identify new regulatory mechanisms
using bioinformatics. By integration of bioinformatic analysis withexperimental studies, we focused on deciphering the regulatory mechanisms
and biological functions of N6-methyladenosine (m6A) modification, which is
the most abundance modification on mRNAs. We discovered that theselectivity of m6A modification sites is partially regulated by miRNAs via
sequencing pairing, revealing a novel function of miRNAs in regulating mRNA
epigenetic modification. We also systematically characterized the distribution
feature and dynamic changes of m6A modification sites in mouse brain during
learning process. Intriguingly, we found that the formation of m6A modification
can enhance the efficacy of hippocampus-dependent memory consolidation byfacilitating the translation of early-response genes, yet excessive training cancompensate the function of m6A in regulating long term memory formation. We
also revealed novel functions of a m6A reader protein, YTHDC1, in regulatingembryonic brain development.