Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Contrary to expectations, a ...
This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
One of the most immediate impacts of AI in medical genetics lies in diagnosis, particularly for rare and complex genetic ...
Many human traits are influenced by multiple genes. Human genes can also carry slight variations in their gene sequences, which can have a wide range of effects. In some complex traits, those small ...
- CANDID-CNS TM achieves an 83% success rate for predicting small molecule brain penetration and distribution versus a 64% success rate for the industry standard CNS-MPO score - Only ~2% of small ...
A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...
Genes were once thought to be static. But recent research in the field of epigenetics has found that genes can and do change in response to environmental cues. We know that genes are capable of ...
Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...
A research team has developed an AI-based approach to streamline the evaluation of maize haploid fertility restoration, a key bottleneck in double haploid (DH) breeding.
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