How do genes, proteins, and other molecules interact within the cell? How can therapeutic pathways be identified to treat complex diseases? A new BELLA II Testbed, which focuses on bioinformatics, provides an advanced research environment that combines data from various sources with Artificial Intelligence (AI) tools, helping to advance studies in biotechnology and personalized medicine.
The Testbed is technically supported by RedCLARA and the Universidad de los Andes, Venezuela.
This platform allows for detailed modeling of how molecules interact, including processes like gene regulation, metabolism, communication between cells, and how the immune system responds. Such understanding is key to developing new therapies and advancing scientific research. To achieve this, the platform gathers scattered information from diverse sources and generates accurate models that simplify study and analysis.
The Bioinformatics Testbed enables researchers to identify molecular interaction networks, model hypothetical scenarios before committing resources to costly experiments, develop preliminary models that reduce risks in early stages, and conduct experimentation using AI-based methodologies adaptable to various research contexts. It also ensures reproducibility through complete traceability of each result, allowing studies to be replicated and hypotheses systematically explored.
Among its standout features are transparent and verifiable reasoning, which validates each molecular relationship with scientific references; automatic integration of sources such as PubMed, PubTator, Protein Data Bank, HGNC, and Gene Ontology; and expert control of the process, allowing researchers to define search parameters, validate results, and refine models. The platform also facilitates the generation of experimental hypotheses, identification of regulatory pathways and candidate subnetworks, and provides access to generative and logic-based AI models for simulating and inferring molecular interactions.
This testbed has multiple applications: analyzing disease mechanisms, modeling therapeutic targets, designing therapeutic strategies, exploring scientific hypotheses through predictive models, and training generative AI models tailored to specific application domains, combined with logic-based AI to optimize the discovery of molecular interaction networks and subnetworks. It is thus consolidated as an innovative and reference tool for advanced research in bioinformatics.
For information on access plans, preferential rates, and more: Request access to the Bioinformatics Testbed here.
