Links within this page: Fritz Sedlazeck | Steven Brenner | Xuegong Zhang | Hyun Uk Kim | Noam Shomron
Fritz Sedlazeck
Baylor College of Medicine
https://fritzsedlazeck.github.io/
Dr. Fritz Sedlazeck is an Associate Professor at the Human Genome Sequencing Center at Baylor College of Medicine and an Adjunct Associate Professor at Rice University. His research focuses on algorithmic developments and high-performance computing for genomic and genetic applications. Specifically, he studies ways to improve the characterization of complex genomic alterations between individuals’ genomes based on large genomic sequencing data and as such improve our understanding of complex phenotypes such as human diseases.
Steven Brenner
UC Berkeley
https://compbio.berkeley.edu/
Steven Brenner’s research is primarily in the area of computational genomics, including genome variation interpretation, genomic privacy, RNA regulation, protein structure evolution, and function prediction. He has a particular interest in the use of genome sequencing in newborns for population screening and new methods for genomic diagnosis.
Brenner’s undergraduate research was in the first genome laboratory, mentored by Walter Gilbert at Harvard. He received his M.Phil. from the Department of Biochemistry at Cambridge University, and earned a Ph.D. from the University of Cambridge and the MRC Laboratory of Molecular Biology where he studied with Cyrus Chothia. Brenner had a fellowship at the Japan National Institute of Bioscience, followed by postdoctoral research supervised by Michael Levitt at Stanford University School of Medicine.
Brenner has a commitment to supporting open science and development of a diverse, inclusive scientific community. He is currently a member of the ClinGen Sequence Variant Interpretation Working Group and Chair of the Computational subgroup, a director of the Human Genome Variation Society, and a chair of the HUGO Pathogenicity Committee. He was founding chair of the Computational Biology graduate program at Berkeley, a founding editor of PLoS Computational Biology, a founding chair of the Global Alliance for Genomics and Health’s Data Working Group Variant Annotation Task Team, and was a founding director of the Open Bioinformatics Foundation, His recognitions including being a Miller Professor, a Sloan Research Fellow, a Searle Scholar, an AAAS Fellow, an ISCB Fellow, and a recipient of ISCB’s Overton Prize.
Xuegong Zhang
Tsinghua University
http://eca.xglab.tech/member/index.html
Xuegong Zhang is Professor of Pattern Recognition and Bioinformatics in the Department of Automation, Tsinghua University, and Adjunct Professor of the School of Life Sciences and Tsinghua Medicine. He received his BS degree in 1989 and his Ph.D. degree in 1994 both from Tsinghua University, after which he joined the faculty of Tsinghua University. He was a visiting scientist at Harvard School of Public Health in 2001-2002 and 2006, and was a visiting scholar at University of Southern California in 2007. His research interests include machine learning, human cell atlas, intelligent precision medicine, AI foundation models and digital life systems. His early work on detecting differential gene expression from very small samples has been widely used in many labs across the globe, and his leading work on AI foundation models for single-cell transcriptomics put him as a pioneer of current AI biology. Dr. Zhang was elected as ISCB Fellow and CAAI Fellow in 2020, and was elected as the Vice President of ISCB in 2024. He is currently the co-Editors-in-Chief of the journal Quantitative Biology, the Vice President of ISCB, Chair of ISCB-China, and Chair of the Committee of Intelligent Health and Bioinformatics of Chinese Association of Automation (CAA).
Hyun Uk Kim
KAIST
https://pure.kaist.ac.kr/en/persons/hyun-uk-kim
Prof. Hyun Uk Kim is an Associate Professor at KAIST, affiliated with the Department of Chemical and Biomolecular Engineering and the Graduate School of Engineering Biology. He obtained his B.Sc. (2005) from Yonsei University and his M.Sc. (2007) and Ph.D. (2011) from KAIST. His research focuses on bio-big data and AI-driven systems biology, with applications in synthetic biology/metabolic engineering and precision medicine. He has published 98 scientific papers. His recent work includes the development of DeepEC, a deep-learning model for enzyme function prediction (PNAS, 2019); DeepMGR, a deep-learning model for predicting gene expression patterns under specific microbial culture conditions (Computational and Structural Biotechnology Journal, 2023); prediction of oncometabolite candidates (Genome Biology, 2024); A machine learning framework for extracting biological pathway information from large-scale literature sources (Metabolic Engineering, 2024); and prediction of multi-drug responses using electronic health records (Computers in Biology and Medicine, 2025). He has received several awards, including the KAIST College of Engineering Technology Innovation Award (2019) and the Impact Research Award (2019, 2021–2024). In 2021, he was appointed as a Kwon Oh-Hyun Associate Professor and received the Young Scientist Award from the Korean Society for Biotechnology and Bioengineering in 2020. He has been an invited/keynote speaker at international conferences, including Metabolic Engineering 15 (Singapore, 2023), The Automated Scientist by the Novo Nordisk Foundation (Denmark, 2024), and the 1st Asia & Pacific Bioinformatics Joint Conference (APBJC2024) (Japan, 2024).
Noam Shomron
Tel Aviv University
https://en-med.tau.ac.il/profile/nshomron
Noam Shomron is passionate about using basic science to advance better healthcare. He is a Professor of Digital Medicine and Functional Genomics at the Faculty of Medical & Health Sciences at Tel Aviv University after training at MIT. He leads a multidisciplinary team of scientists that develops computational methods for parsing big data in the bio-medical field using Artificial Intelligence. Noam published hundreds of peer-reviewed publications on multiple genomic fields; Editor of ‘Deep Sequencing Data Analysis’ book (Springer, Edition I 2013, and II 2021); Director of Djerassi Institute of Oncology; Academic Director of ‘ScienceAbroad’ (NPO); ranked Major in the army forensic lab; Co-founder of several Biotech and Digital Medicine companies: Variantyx, GotSho, IdentifAI, Everly Bio, 4nZOK, among others.
Links within this page: HKU University Museum and Art Gallery | Hiking from the UNK to the Peak
Discover, Connect, and Explore Hong Kong at GIW ISCB-Asia 2025!
Who says networking has to be all PowerPoint, posters and coffee breaks? At GIW ISCB-Asia 2025, we’re reinventing the way connections are made. Picture this: meaningful conversations sparked over dim sum, collaborations born amidst the glow of Victoria Harbour, and friendships forming on the vibrant streets of Hong Kong.
This year, we're blending science with the city's unique energy, offering activities that invite you to explore the culture, cuisine, and iconic sights—all while building your professional network. The following activities will organized at the close of the conference on Saturday, December 13. Registration is required for planning purposes.
Confirmed Activities
HKU University Museum and Art Gallery
The University Museum and Art Gallery (UMAG) of The University of Hong Kong, established in 1953, is Hong Kong's oldest continuously operated museum. Its diverse collection spans over 7,000 years, featuring Neolithic ceramics, Ming and Qing dynasty paintings, and rare bronzes, including ritual vessels and Tang dynasty mirrors. Highlights include one of the earliest known underglaze-blue ceramic pieces and the world's largest collection of Yuan dynasty Nestorian crosses. UMAG also hosts contemporary and historical exhibitions, fostering a vibrant connection between art, education, and the public. As a teaching museum, it continues to support the University and the broader community through programs and activities that celebrate art and history.
Hiking from the UNK to the Peak
https://www.gethigh-hk.com/post/hku-to-the-peak
The Lugard Road Lookout (The Peak), perched along the historic Lugard Road on Victoria Peak, offers one of Hong Kong’s most breathtaking panoramic views. Named after Sir Frederick Lugard, Hong Kong’s 14th Governor, this scenic spot captures the city’s iconic skyline, Victoria Harbour, and distant islands, blending urban energy with natural beauty. Built in the early 20th century, the lookout is a popular stop on the Peak’s circular walking trail, a tranquil escape surrounded by lush greenery. The Lugard Road Lookout is a timeless gem that showcases the harmonious contrast of Hong Kong’s urban and natural landscapes.
More to come….
Join us in Hong Kong, where science meets adventure, and networking takes a bold, exciting twist!
Links within this page: Abstracts: Submission Guidelines | Abstract Preparation Guidance | Conference Topics | Important Dates | Why Submit?
Join us in advancing computational biology and bioinformatics!
GIW/ISCB-Asia 2025 welcomes abstract submissions featuring research at the forefront of bioinformatics and computational biology. We encourage the submission of original work, whether it is in progress or has been previously published within the last 18 months, for consideration for oral and/or poster presentation.
All presentations are categorized based on scientific topics, ensuring a cohesive organization of talks and posters. Please ensure that your abstract communicates a scientific result and refrains from serving as an advertisement for any commercial software package or products.
GIW/ISCB-Asia 2025 embraces a broad interpretation of bioinformatics/computational biology. Topics of particular interest encompass, but are not limited to, the following:
- Single-Cell Analysis
- Spatial Omics and Histology
- Cutting-Edge AI Applications in Biology and Medicine
- Protein/RNA Structure Analysis, Prediction and Design
- Cancer Genomics and Personalized Medicine
- Metagenomics and Microbiome Analysis
- Network Biology and Systems Biology
- Drug Discovery and Repurposing
- Ethical, Legal and Social Issues (ELSI)
- Bioinformatics Education
- Multi-Omic Informatics
- Databases, Ontologies and Biocuration
- Evolutionary, Comparative Genomics and Phylogenetics
- Synthetic Biology and Engineering
- General Computational Biology
See detailed descriptions of these topics below.
Abstracts: Submission Guidelines
The presenter should be identified during the submission process. Presenters of accepted abstracts are required to make the presentation themselves, and must register and pay to attend the conference.
Submitters may choose to have their submission reviewed for: (i) talk only, (ii) talk and poster or (iii) poster only. If you select talk and poster, and are unsuccessful for a talk, your abstract will automatically be considered for a poster presentation. Submissions must be received by September 29, 2025.
Participants who opt for (i) talk only or (ii) talk and poster are required to submit:
- Both a 200-word abstract to be posted on the conference website AND a long abstract of up to two (2) pages in PDF format.
Participants who opt for (iii) poster only are required to submit:
- A 200-word abstract to be posted on the conference website.
All abstracts must be submitted using the conference submission site by the abstract deadline: September 29, 2025.
Abstract Preparation Guidance
The 200-word abstract should be a brief and concise summary of the background/motivation for the study, method and result (s), as well as a conclusion/statement of significance. The abstract is submitted through the EasyChair submission system.
Accepted abstracts (maximum 200 words) will be posted on the conference website.
For authors requesting a talk you should upload a long abstract of up to two (2) pages in PDF format during the submission process, to provide additional details including figures and graphics that support the main points of the abstract. Do not submit more than two pages.
Your abstract must not contain your title/position or any personal information (e.g. affiliation). These details will be collected through the EasyChair submission system.
Conference Topics
Submissions are invited on, but not limited to, the following topics:
SINGLE-CELL ANALYSIS:
Advancements in single-cell technologies have allowed researchers to delve deeper into understanding cellular heterogeneity, cell signaling, and gene expression at the single-cell level. Analyzing large-scale single-cell data poses challenges in computational methods, driving innovation in this area.
SPATIAL OMICS AND HISTOLOGY:
Methods development, computational analysis, and clinical application of spatial transcriptomics, multi-omics, and/or the integration of histology images. The combination of spatial transcriptomics and histology provides detailed, high-resolution maps of gene expression within the context of tissue architecture.
CUTTING-EDGE AI APPLICATIONS IN BIOLOGY AND MEDICINE::
The application of machine learning algorithms and artificial intelligence in biology and medicine has been rapidly expanding. In biology, these techniques aid in predictive modeling, variant calling, drug discovery, functional genomics, and interpreting complex biological data. In medicine, AI and machine learning are revolutionizing diagnostics, personalized treatment plans, patient monitoring, and clinical decision-making.
PROTEIN/RNA STRUCTURE ANALYSIS, PREDICTION AND DESIGN:
Cutting-edge computational methods are revolutionizing our ability to predict and design the structures of proteins and RNA molecules. These advancements hold immense potential for developing new drugs, understanding fundamental biological functions, and creating innovative therapeutics.
CANCER GENOMICS AND PERSONALIZED MEDICINE:
Computational approaches are instrumental in analyzing large-scale genomic and clinical data to tailor treatments based on an individual's genetic makeup. Precision oncology, in particular, relies on computational biology for tumor profiling, drug sensitivity prediction, and identifying potential therapeutic targets.
METAGENOMICS AND MICROBIOME ANALYSIS:
Computational tools play a crucial role in studying complex microbial communities and their impact on human health, agriculture, and the environment. Analyzing metagenomic data involves developing algorithms for taxonomic classification, functional profiling, and understanding microbial interactions.
NETWORK BIOLOGY AND SYSTEMS BIOLOGY:
Computational modeling of biological networks, such as protein-protein interactions, metabolic pathways, and gene regulatory networks, helps in understanding the underlying mechanisms of complex biological systems. Systems biology integrates computational and experimental approaches to study biological systems holistically.
DRUG DISCOVERY AND REPURPOSING:
Computational methods are extensively used in virtual screening, molecular docking, and drug-target interaction prediction. These approaches accelerate drug discovery and enable the repurposing of existing drugs for new therapeutic applications.
ETHICAL, LEGAL AND SOCIAL ISSUES (ELSI):
With the increasing volume of biological data being generated, there is a growing emphasis on addressing ethical concerns, ensuring data privacy, and developing frameworks for responsible data sharing and usage in computational biology research.
BIOINFORMATICS EDUCATION:
Bioinformatics education is fast advancing by reflecting substantial changes in the expanding research areas and educational tools.
MULTI-OMIC INFORMATICS:
Various informatics resources and technologies have been developed for omics data accumulated via high-throughput technologies.
DATABASES, ONTOLOGIES AND BIOCURATION:
To effectively manage the vast amounts of biological data generated by advanced measurement techniques, it is increasingly crucial to design interoperable and reusable biological databases, construct ontologies for precise data representation in life sciences, and refine biocuration workflows to enhance data quality and accessibility.
EVOLUTIONARY, COMPARATIVE GENOMICS AND PHYLOGENETICS:
New discoveries as well as groundbreaking methods are being made for comparing genomic data and revealing the evolutionary histories and relationships of diverse species.
SYNTHETIC BIOLOGY AND ENGINEERING:
Engineering biology enabling the intentional design, manufacture and deployment of living cells, cell systems, and other biological processes to create materials and products for benefiting humanity.
GENERAL COMPUTATIONAL BIOLOGY:
Other topics related to computational biology not listed above.
Important Dates
Submission Deadline: September 29, 2025
Abstract Decision Date: October 17, 2025
Late-Breaking Posters Deadline: October 20, 2025
Late-Breaking Poster Decision Date: October 29, 2025
Why Submit?
GIW XXXIV | ISCB-Asia VIII provides a leading platform for presenting groundbreaking research, engaging with peers, and advancing computational biology globally. Join us in exploring cutting-edge innovations and impactful discoveries.
Submit your work and be part of this premier conference!
Venue Information
University of Hong Kong
Rayson Huang Lecture Theatre
Pok Fu Lam Rd, Lung Fu Shan, Hong Kong
Link to Map
Hotel Accommodations
Coming soon.
Getting to Hong Kong
Hong Kong is a major international hub, easily accessible by air, land, and sea. Hong Kong International Airport (HKIA) serves numerous direct flights from major cities worldwide.
Upon arrival, efficient transport options like the Airport Express train, buses, and taxis provide seamless connections to the city center. For travelers from Mainland China and Macau, high-speed trains, cross-boundary coaches, and ferry services offer convenient access to Hong Kong.
This extensive network ensures that reaching Hong Kong is straightforward, regardless of your starting point.
The Discover Hong Kong website has detailed up-to-date information about traveling to the city.