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| http://dx.doi.org/10.1093/nar/17.13.5422 | DOI Listing |
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Highly parallel simulation tool for the design of isotachophoresis experiments.
Anal Chim Acta
February 2025
Department of Mechanical Engineering, Stanford University, 488 Escondido Mall, Stanford, CA, 94305, USA. Electronic address:
Background: Isotachophoresis (ITP) is a well-established electrokinetic method for separation and preconcentration of analytes. Several simulation tools for ITP have been published, but their use for experimental design is limited by the computational time for a single run and/or by the number of conditions that can be investigated per simulation run. A large fraction of the existing solvers also do not account for ionic strength effects, which can influence whether an analyte focuses in ITP.
View Article and Find Full Text PDFTime-varying 3D optical torque via a single beam.
Nat Commun
January 2025
Department of Optics and Optical Engineering, University of Science and Technology of China, Hefei, China.
The spin angular momentum (SAM) plays a significant role in light-matter interactions. It is well known that light carrying SAM can exert optical torques on micro-objects and drive rotations, but 3D rotation around an arbitrary axis remains challenging. Here, we demonstrate full control of the 3D optical torque acting on a trapped microparticle by tailoring the vectorial SAM transfer.
View Article and Find Full Text PDFModular DNA origami-based electrochemical detection of DNA and proteins.
Proc Natl Acad Sci U S A
January 2025
Department of Bioengineering, California Institute of Technology, Pasadena, CA 91125.
The diversity and heterogeneity of biomarkers has made the development of general methods for single-step quantification of analytes difficult. For individual biomarkers, electrochemical methods that detect a conformational change in an affinity binder upon analyte binding have shown promise. However, because the conformational change must operate within a nanometer-scale working distance, an entirely new sensor, with a unique conformational change, must be developed for each analyte.
View Article and Find Full Text PDFCSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data.
Cell Genom
January 2025
Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA. Electronic address:
Exploratory analysis of single-cell RNA sequencing (scRNA-seq) typically relies on hard clustering over two-dimensional projections like uniform manifold approximation and projection (UMAP). However, such methods can severely distort the data and have many arbitrary parameter choices. Methods that can model scRNA-seq data as non-discrete "gene expression programs" (GEPs) can better preserve the data's structure, but currently, they are often not scalable, not consistent across repeated runs, and lack an established method for choosing key parameters.
View Article and Find Full Text PDFRandom walks with long-range memory on networks.
Chaos
January 2025
Instituto de Física, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
We study an exactly solvable random walk model with long-range memory on arbitrary networks. The walker performs unbiased random steps to nearest-neighbor nodes and intermittently resets to previously visited nodes in a preferential way such that the most visited nodes have proportionally a higher probability to be chosen for revisit. The occupation probability can be expressed as a sum over the eigenmodes of the standard random walk matrix of the network, where the amplitudes slowly decay as power-laws at large times, instead of exponentially.
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