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G protein-coupled receptors (GPCRs) signal through molecular messengers, such as Gβγ, Ca(2+), and phosphatidylinositol 4,5-bisphosphate (PIP2), to modulate N-type voltage-gated Ca(2+) (CaV2.2) channels, playing a crucial role in regulating synaptic transmission. However, the cellular pathways through which GqPCRs inhibit CaV2.2 channel current are not(More)
Polybrominated diphenyl ethers (PBDEs) are brominated flame retardants that act as endocrine disruptors, affecting thyroid hormone homeostasis. As a follow-up to a recent study showing high PBDE levels in household cats and linking PBDE levels with cat hyperthyroidism, we measured PBDEs, polychlorinated biphenyls (PCBs), and organochlorinated pesticides(More)
Handwritten digit classification is a classical problem in field of machine learning or artificial intelligence. Here, we propose a DNA computing method to explore the intersection between biology and computation. We implement of the Molecular Evolutionary Hypernetwork in vitro using DNA sequences as data. The pixels of the images are encoded into DNA(More)
An intersection between biology and computation is explored by classifying handwritten digits using DNA computing. To do this, we propose employing the Molecular Evolutionary Hypernetwork [1] in vitro using specifically encoded DNA as pixels of images. This machine learning algorithm consists of various stages; matching of training or test data with the(More)
Pattern recognition is a major division of machine learning which focuses on learning the patterns and regularities in data. It differs to that of pattern matching where only exact matches are found. However in the field of DNA computing, molecular pattern recognition has not been well established due to the lack of control of molecules in liquid state,(More)
Various benefits of DNA computing such as programmability, immense data storage capacity and massively parallel processing have led to provide fundamental building blocks to motivated goals of building smart in vivo robots with implications in various applications. However, molecular machine learning has not yet been employed to solve more complex tasks(More)
The field of DNA computing offers many advantages for the manipulation of DNA to be applied to the field of machine learning or artificial intelligence. DNA (deoxyribonucleic acid) consists of a sugar-phosphate backbone with a chain of nucleotides and acts as a very compact information storing medium. In 1 μm of DNA 1026 reactions take place, which gives(More)
Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular(More)
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