dkNET Showcases AI-Driven Biomedical Data Science Innovations at ISMB 2026

The dkNET team is featured at the International Conference on Intelligent Systems for Molecular Biology (ISMB) 2026 in Washington, DC, on July 13, 2026, highlighting new developments in cloud-based data science, artificial intelligence (AI), and knowledge representation for biomedical research.

Tech Track session

Dr. Chen Li presents:

“dkNET Computational Core — Cloud-native, Collaborative AI/ML and Literature Intelligence for Biomedical Research”
July 13, 2026 | 12:20–1:00 PM ET

Supported by the NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the dkNET team is developing a Computational Core powered by Apache Texera (Incubating) to support collaborative, reproducible, and scalable biomedical data analysis.

Bio-Ontologies and Knowledge Representation Track

Dr. Maryann Martone will deliver an invited keynote lecture in the :

“AI and Ontologies: The Beginning of a Beautiful Friendship”
July 13, 2026 | 4:40–5:40 PM ET

Dr. Martone’s keynote explores the evolving relationship between artificial intelligence and biomedical ontologies. 

Abstract from ISMB 2026 website:

"The field of ontology, like almost every other field of human endeavor, is heavily impacted by the AI revolution. Those of us who spend time constructing them are often asked whether they are necessary now that large language models and other tools are able to reason over unstructured text and extract key concepts and their relationships. If an LLM can apparently "understand" that a hippocampal neuron and a CA1 pyramidal cell are related without consulting the Cell Ontology, why are these painstakingly curated knowledge structures necessary?

The answer is that ontologies and AI are not substitutes — they are increasingly complementary and mutually reinforcing — but the nature of ontologies' value is shifting. In this presentation, I will argue that human-curated ontologies serve an irreplaceable function as stable anchors in a constantly shifting knowledge landscape.

I will illustrate this complementarity and mutual reinforcement through our work over the past few decades to build ontologies and other knowledge structures for biomedicine. I will provide lessons learned in our efforts to construct and maintain effective ontologies for neuroscience, a challenging domain where key entities like brain anatomy and cell types still lack consensus.

I will discuss some of our approaches and infrastructure for building multiscale connectivity and cell type knowledge bases to accommodate rapidly advancing knowledge by using a sociology of science framework to propose when and how a concept deserves stable representation. I will also make the case that AI is the “killer technology” that allows us not only to realize our long-standing goal of building comprehensive and complete knowledge artifacts at scale, but to deliver the tools required to exploit them to domain experts."

Together, these presentations highlight dkNET’s ongoing efforts to advance FAIR, collaborative, and AI-enabled biomedical research infrastructure, empowering scientists with new tools for data analysis, knowledge discovery, and reproducible research.


More information: https://www.iscb.org/ismb2026