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Researchers have enabled the effective selection of phages based on the genome of the bacteria they want to target, helping to recommend the best treatment for a patient.

Tree-D Fusion uses AI to create 3D models of urban trees, predicting growth under climate scenarios. These models aid city planning by anticipating challenges like branch interference and improving urban cooling.

Researchers developed an AI-powered protein design method using Alphafold2 and gradient descent optimization. The approach allows precise tailoring of large proteins with desired properties, such as binding to pathogens.

A thymus atlas reveals that immune foundations are set as early as 12 weeks post-conception. Researchers uncovered key T cell development processes, offering insights for engineering immune cells to treat cancer and autoimmune diseases.

Kaunas University of Technology developed a multimodal AI system integrating EEG and speech data to diagnose depression with 97.53% accuracy. Using deep learning, the model processes spectrograms to detect mental health patterns.

Researchers from CRG and Harvard Medical School show that single cells can “learn” by adapting to repeated stimuli using molecular circuits. This behavior mimics habituation in complex organisms and provides insights into cellular memory.

A collaboration among neurosurgeons and computer scientists has defined three sub-types of Chiari type-1 with distinct characteristics that physicians can use to plan treatment options for their patients.

Researchers at Karolinska Institutet tested 10 AI models for predicting triple-negative breast cancer outcomes by analyzing tumor-infiltrating lymphocytes. Eight models demonstrated good prognostic ability.

Machine learning and supercomputer simulations have been used to investigate how tiny gold nanoparticles bind to blood proteins.

A new study has described personality traits that are common among people in certain jobs, leading to the creation of over 250 personality profiles.