As we enter a new year together as the ASCB community, it is hard not to feel the weight of the moment. These are challenging times for science. Funding is uncertain, priorities are shifting, and pressures on the scientific enterprise are being felt across disciplines and career stages. And yet, even in this environment, our community continues to show remarkable resilience and generosity.
I am deeply grateful to our members, volunteers, staff, and supporters who sustain ASCB through their time, energy, and belief in the enduring value of biological discovery. Because of you, the Society remains a vibrant home for cell biologists around the world.
But today I want to focus on science itself, because that is what ultimately unites us and sustains us. Science is not just our profession; for many of us, it is also our source of curiosity, motivation, and joy. At moments like this, when resources are constrained and expectations are changing, the choices we make as scientists—what problems we work on, what approaches we invest in, and how much risk we are willing to take—matter more than ever.
As scientists, we are keen observers of patterns, not only in nature, but also in our own enterprise. Over the course of a research career, one begins to recognize that biology, like fashion or finance, moves in trends. Certain ideas, tools, and conceptual frameworks suddenly capture the collective imagination. They attract talent, funding, and institutional investment, while conferences and journals reorient around them. For a time, it can feel as though this is where all the important science is happening.
And then, inevitably, the center of gravity shifts.
Having spent several decades in the biological and biomedical sciences, I have had the privilege of witnessing multiple such waves. Each was exciting. Each was, in its own way, transformative. And yet, none represented the final destination. Instead, each trend opened doors, answered some questions, and revealed many more, often in directions that were not initially anticipated. This observation underlies the central message: while it is essential to understand and engage with scientific trends, the long-term vitality of our field depends on our willingness to look beyond them and to create the next frontier.
When I entered science in the late 1980s, the dominant excitement revolved around transcription factors and the control of gene expression. The idea that specific proteins could bind specific regulatory elements on DNA and precisely control genes was electrifying. These discoveries offered a molecular logic to development, differentiation, and disease. Laboratories raced to clone transcription factors, map binding sites, and unravel regulatory hierarchies. It was a period of intellectual clarity and optimism: if we could identify the right regulators, perhaps we could understand and even control cell function.
As the field matured, however, it became clear that gene expression alone could not account for the dynamic behaviors of living cells. Attention shifted in the mid 1990s toward signal transduction, particularly post-translational modifications and tyrosine kinase signaling. Cells came to be viewed not simply as gene expression machines, but as responsive systems capable of rapidly integrating environmental and physiological cues. Nowhere was this shift more impactful than in cancer biology, where signaling pathways provided both mechanistic insight and new therapeutic opportunities.
The completion of the Human Genome Project in the late 1990s marked another turning point. With entire genomes laid bare, biology entered an era in which comprehensive, system-wide measurements became possible. Genomics did more than accelerate discovery; it changed how questions were framed. Hypothesis-driven experiments increasingly coexisted with and sometimes guided by large-scale datasets. The many omics approaches that followed reshaped experimental design and broadened participation in biological research, bringing computation and data science firmly into the mainstream of biology.
In the 2000s, stem cell biology rose to prominence, bringing with it tremendous hope and public attention. The possibility of regenerating tissues, modeling diseases in vitro, and even replacing damaged organs captured the imagination of scientists and society alike. For many young researchers, stem cells represented a direct path from fundamental cell biology to transformative medicine. While the clinical realities have proven more complex than initially envisioned, stem cell research has nonetheless reshaped developmental biology, disease modeling, and regenerative strategies in lasting ways.
More recently, the concept of phase separation has taken center stage. The realization that cells organize themselves not only through membrane-bound organelles but also through dynamic, liquid-like assemblies has offered new ways to think about intracellular organization, signaling, and gene regulation. Phase separation has provided unifying explanations across disparate phenomena, from transcriptional control to neurodegeneration. Its appeal lies partly in its elegance—a physical principle applied broadly across biology, and partly in its ability to connect molecular properties with mesoscale cellular behavior.
And now, we find ourselves in the midst of another powerful trend: artificial intelligence. Advances in machine learning, coupled with unprecedented volumes of biological data, have fueled enormous enthusiasm and investment. From protein structure prediction to image analysis and drug discovery, AI has already delivered remarkable promise. In some narratives, optimism has escalated into the belief that AI and robotics may soon replace humans in solving scientific problems.
There is no question that AI represents a paradigm-shifting development. At the same time, these approaches are fundamentally statistical and data-driven, and while extraordinarily powerful, they remain constrained by the quality, scope, and biases of the data they are trained on, especially in a biological world that is heterogeneous, contextual, and often sparsely sampled. History suggests that while AI will profoundly reshape how we do science, it will not mark an endpoint. Rather, it will become part of the foundation upon which new questions, concepts, and frontiers emerge.
Looking back across these eras, a pattern becomes clear. Each trend reflected a genuine breakthrough and a new way of seeing cells, organisms, or data. Each propelled the field forward, often at unprecedented speed. And yet, none became a permanent plateau. Each eventually blended into the background of standard practice, making room for the next wave of ideas. This is not a failure of trends, but it is their function. Trends are how science reorganizes itself around new insights. The danger lies not in trends themselves, but in mistaking them for destinations rather than transitions.
For individual scientists, especially trainees and early-career investigators, this creates a tension. Trends shape funding priorities, hiring decisions, and perceptions of importance. Ignoring them entirely is neither realistic nor wise. At the same time, simply following the prevailing current can limit creativity and long-term impact. Perhaps the most exciting place to be is just beyond the trend: informed by it but not confined by it. This requires both courage and innovation. It means adopting new technologies without letting them dictate the questions we ask. It means appreciating prevailing theories while remaining attentive to anomalies and inconsistencies. And it means cultivating intellectual independence: the willingness to pursue ideas whose value may not be immediately obvious.
As a Society, ASCB has a special role to play in fostering this mindset. Cell biology has always thrived by integrating concepts from chemistry, physics, engineering, computation, and medicine. Our strength lies not in adherence to any single trend, but in our ability to evolve, to absorb new ideas, and to generate brand new ways of understanding living systems. Supporting diverse approaches, encouraging risk-taking, and valuing deep mechanistic insight alongside technological innovation are essential to this mission.
Trends will continue to come and go. Some will be shorter-lived; others will reshape the field for decades. But the next true frontier—the one we cannot yet name will likely emerge from unexpected connections, from questions that do not fit neatly into current categories, and from scientists who dare to imagine beyond what is fashionable.
Our challenge, and our opportunity, is to ensure that we are not only excellent followers of trends, but also creators of the future ones. That, in my view, is where the enduring excitement of biology truly lies.
About the Author:
Rong Li is a Director and Distinguished Professor at the Mechanobiology Institute, National University of Singapore and ASCB's 2026 President
