Publications by authors named "Samuel G Rodriques"

Academia is a vital source of innovation and discovery, but it faces challenges in funding and coordination. These challenges limit the scope and impact of academic research. Now, philanthropists and governments are exploring new institutional structures and funding strategies, with the goal of unleashing scientific discovery.

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  • Large-language models like GPT-4 have sparked interest among scientists, especially in fields like chemistry and materials science.
  • A hackathon was organized to explore their potential applications, resulting in various projects such as predicting molecular properties and developing educational tools.
  • The rapid prototyping of ideas within the hackathon suggests that LLMs could significantly influence multiple scientific disciplines beyond just chemistry and materials science.
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  • HyPR-seq is a new method for quantifying gene expression at the single-cell level, improving sensitivity for individual RNA transcripts compared to existing methods.
  • It works by hybridizing DNA probes to RNA, then amplifying and sequencing these probes, allowing researchers to profile over 100,000 single cells efficiently.
  • This technique not only identifies rare transcripts and measures gene expression changes but also significantly reduces costs, making it a practical choice for targeted RNA analysis in various biological applications.
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Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein.

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Spatial positions of cells in tissues strongly influence function, yet a high-throughput, genome-wide readout of gene expression with cellular resolution is lacking. We developed Slide-seq, a method for transferring RNA from tissue sections onto a surface covered in DNA-barcoded beads with known positions, allowing the locations of the RNA to be inferred by sequencing. Using Slide-seq, we localized cell types identified by single-cell RNA sequencing datasets within the cerebellum and hippocampus, characterized spatial gene expression patterns in the Purkinje layer of mouse cerebellum, and defined the temporal evolution of cell type-specific responses in a mouse model of traumatic brain injury.

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We propose and theoretically study an approach to massively parallel single molecule peptide sequencing, based on single molecule measurement of the kinetics of probe binding (Havranek, et al., 2013) to the N-termini of immobilized peptides. Unlike previous proposals, this method is robust to both weak and non-specific probe-target affinities, which we demonstrate by applying the method to a range of randomized affinity matrices consisting of relatively low-quality binders.

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Lithographic nanofabrication is often limited to successive fabrication of two-dimensional (2D) layers. We present a strategy for the direct assembly of 3D nanomaterials consisting of metals, semiconductors, and biomolecules arranged in virtually any 3D geometry. We used hydrogels as scaffolds for volumetric deposition of materials at defined points in space.

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We introduce the design and theoretical analysis of a fiber-optic architecture for neural recording without contrast agents, which transduces neural electrical signals into a multiplexed optical readout. Our sensor design is inspired by electro-optic modulators, which modulate the refractive index of a waveguide by applying a voltage across an electro-optic core material. We estimate that this design would allow recording of the activities of individual neurons located at points along a 10-cm length of optical fiber with 40-μm axial resolution and sensitivity down to 100  μV using commercially available optical reflectometers as readout devices.

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