Nanopore sensors generate complex ionic current traces that encode rich molecular information, making them well-suited for computational signal analysis. Building on previous work in which DNA-barcoded probes were developed for the multiplexed detect...
We propose strategies for incorporating the information in large language models (LLMs) into statistical hypothesis tests in genomics studies. Using gene embeddings derived from text inputs to OpenAI’s GPT-3.5 model, we show that biological signals i...
Long-term transplant success is limited by allograft rejection, a complex process traditionally studied on an organ-specific basis. To establish a unified framework beyond organ-specific studies, we performed a network-based systems biology analysis ...
Mechanistic understanding of how gene activity is regulated has focussed on the roles of transcription factors at promoters and enhancers, whereas mechanisms capable of globally fine-tuning gene expression through dispersed binding across large genom...
Reinforcement learning enables the adaptation of behaviors to changes in the environment. Models of reinforcement learning based on using previous experience to guide future choices enable balancing exploitation of opportunities and exploring the opt...
Protein solubility is a critical physicochemical property influencing protein stability, therapeutic efficacy, and overall developability in drug discovery. However, traditional experimental methods for assessing solubility are often resource-intensi...
The basal ganglia (BG) are central to action selection and reinforcement learning, yet how the topological organization of the BG circuit with dopamine (DA) D1- and D2-receptors shape learning remains unclear. We present a topologically organized spi...
Deciphering the brain’s structure-function relationship is key to understanding the neuronal mechanisms underlying perception and cognition. The cortical column, a vertical organization of neurons with similar functions, is a classic example of prima...
Malformations of cortical development such as tuberous sclerosis complex arise within a heterogeneous cellular landscape that conventional histopathology only partially resolves. Here, we combined a 19-marker multiplex immunofluorescence panel with a...
This study focused on the development of machine-learning- (ML) based strategies for mitigating nitrous oxide (N2O) emissions from various wastewater treatment systems in the United States measured using a benchmark USEPA-endorsed protocol. Results r...
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