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Although microbial genome data are accumulating at an unprecedented pace, it remains a major challenge to interpret, predict, and ultimately design microbial phenotypes and functions from these data. In this workshop, we will discuss genome-scale metabolic models, or GEMs, as a practical framework for addressing this challenge. Metabolic networks reconstructed from genome information provide a foundation for predicting microbial behaviors, including growth, survival strategies, resource utilization, and metabolite production. At the same time, GEMs can be used to guide the design of culture conditions, metabolic pathway engineering, and the production of useful compounds. This workshop will first introduce the fundamentals of model reconstruction and analysis, and then present a broad range of applications, from understanding pathogenic microorganisms in infectious disease research to designing microbial functions for bio-based manufacturing. Overall, this workshop aims to highlight how GEMs can serve as a bridge between genome information and predictive, design-oriented microbial research.

In recent years, lectures and practical training in bioinformatics have been widely implemented across numerous technical colleges, universities, and graduate schools. Many students are expected to acquire skills such as performing diverse data analyses tailored to their institution’s needs, or independently analyzing data generated from their own wet-lab experiments. This objective is closely aligned with the Bioinformatics Certification Exam, which our society has administered for many years. Against a broader backdrop, this trend may also reflect the recent paradigm shift in scientific research toward data science.

However, the rapid advancement of AI technology over the past few years has dramatically shifted the landscape. Remarkably, it is now predicted that in the near future, scientists who specialize in writing simple code or utilizing existing tools for data analysis and visualization may be among the most vulnerable to being replaced by AI.

There must be many educators across the country who are deeply concerned about this issue. While resolving this challenge will not be easy, I propose this session as an opportunity for us to collectively reflect on and discuss what we should be teaching in bioinformatics education moving forward.

Foundational technologies may appear modest at first glance, yet they have always been at the heart of scientific progress. Today, however, the rapid rise of generative AI has pushed many of these technologies behind the veil of large language models, making them increasingly invisible even to researchers themselves. Indeed, many bioinformatics analyses can now be carried out simply by describing a high-level objective in natural language. Yet the value of innovative algorithms born from original ideas, databases that inspire discovery, software refined through years of craftsmanship, and groundbreaking measurement technologies that open entirely new windows onto biological systems remains undiminished, regardless of how far AI advances. In this workshop, we will invite leading researchers who have pioneered the development of foundational technologies over many years. Through their talks, we hope to explore not only the technologies themselves, but also the ideas, philosophies, and research journeys behind them. By learning about these foundational technologies, we aim to create an opportunity to reflect on the broader nature of science and on what it truly means to create new knowledge.

The International Society for Computational Biology (ISCB) is the largest international academic society in the field of bioinformatics. Its student and early-career researcher community, the ISCB Student Council (ISCB SC), supports networking and career development through Regional Student Groups (RSGs) around the world. This workshop aims to raise awareness of ISCB-SC RSG-Japan, the Japanese regional group, and will feature an English research presentation session for early-career researchers who aspire to present at leading international conferences in bioinformatics, such as ISMB 2027 and BIOINFO/GIW ISCB-Asia 2026.

Up to four speakers will be selected through an open call based on the abstracts submitted at the time of application. After each presentation, judges consisting of researchers and organizing committee members will provide feedback and evaluate the presentations based on the clarity of the research, presentation structure, English presentation skills, and responses to questions. Outstanding presenters will receive awards, including ISCB membership registration support, partial support for conference participation fees within the available budget, and prize money.

Through this workshop, we aim to provide early-career researchers with practical experience in preparing for international conference presentations, while creating an opportunity for participants to learn from one another’s research and presentation styles. We also hope to increase the visibility of ISCB-SC RSG-Japan in Japan and encourage young researchers in Japan to take their first steps toward the global bioinformatics research community.

This workshop will explore why collaborations between wet-lab and dry-lab researchers often encounter difficulties, using both successful and unsuccessful examples as a basis for discussion. Although similar discussions have been repeated within the bioinformatics community, they have largely focused on success stories. In this workshop, we will intentionally address failures as well.

In the first half, we will introduce the sea urchin cell atlas project, in which the organizers have been actively involved, and discuss how wet–dry collaborations were established and led to scientific outcomes. The project has resulted in three published papers and serves as a practical example of applying single-cell technologies to non-model organisms.

In the second half, we will examine collaborative projects that failed to generate meaningful outcomes despite having sufficient time, resources, and organizational support. By contrasting successful and unsuccessful cases, we will discuss which challenges can be addressed through technology and analytical methods, and which arise from fundamentally human factors such as communication gaps, mismatched expectations, and interpersonal relationships.

Importantly, this workshop does not treat all failures equally. We distinguish between avoidable failures, such as those caused by insufficient communication or unclear roles and responsibilities, and failures that arise as a natural consequence of pursuing ambitious and high-risk research questions. By reducing the former, we aim to create research environments in which investigators can engage more boldly in the latter. We will also openly discuss the frustrations, motivations, and realities experienced by researchers involved in collaborative projects. Through this perspective of learning not only from success but also from failure, we hope to examine aspects of wet–dry collaboration that are often obscured by survivorship bias. Participants will be encouraged to share their own experiences, successes, failures, and practical strategies, enabling an open discussion across disciplines and career stages and fostering actionable insights for future collaborations.