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Related papers: Dynamic Pooling Improves Nanopore Base Calling Acc…

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We reduce training time in convolutional networks (CNNs) with a method that, for some of the mini-batches: a) scales down the resolution of input images via downsampling, and b) reduces the forward pass operations via pooling on the…

Machine Learning · Computer Science 2019-10-16 Zissis Poulos , Ali Nouri , Andreas Moshovos

The advent of high-throughput sequencing technologies has revolutionized genome analysis by enabling the rapid and cost-effective sequencing of large genomes. Despite these advancements, the increasing complexity and volume of genomic data…

Genomics · Quantitative Biology 2025-03-06 Can Firtina

Expanding genetic codes from natural standard nucleotides to artificial non-standard nucleotides marks a significant advancement in synthetic biology, with profound implications for biotechnology and medicine. Decoding the biological…

Genomics · Quantitative Biology 2024-09-17 Hyunjin Shim

Developing ultra-low-energy superconducting computing and fault-tolerant quantum computing will require scalable superconducting memory. While conventional superconducting logic-based memory cells have facilitated early demonstrations,…

Molecular separation traditionnally relies on sieving processes across passive nanoporous membranes. Here we explore theoretically the concept of non-equilibrium active sieving. We investigate a simple model for an active noisy nanopore,…

Soft Condensed Matter · Physics 2017-10-23 Sophie Marbach , Lydéric Bocquet

Fast, reliable and inexpensive DNA sequencing is an important pursuit in healthcare, especially in personalized medicine with possible deep societal impacts. Despite significant progress of various nanopore-based sequencing configurations,…

The rapidly growing computational demands of deep neural networks require novel hardware designs. Recently, tunable nanoelectronic devices were developed based on hopping electrons through a network of dopant atoms in silicon. These "Dopant…

Plasmonic nanopores combine nanofluidic confinement with electromagnetic field enhancement, enabling optical interrogation of single molecules in sub-wavelength volumes. Yet, direct optical readout within these metallic geometries has…

Dynamic nuclear polarisation (DNP) refers to a class of techniques used to increase the signal in nuclear magnetic resonance measurements by transferring spin polarisation from ensembles of highly polarised electrons to target nuclear…

Quantum Physics · Physics 2020-12-24 L. T. Hall , D. A. Broadway , A. Stacey , D. A. Simpson , J-P. Tetienne , L. C. L. Hollenberg

DNA data storage is rapidly emerging as a promising solution for long-term data archiving, largely due to its exceptional durability. However, the synthesis of DNA strands remains a significant bottleneck in terms of cost and speed. To…

Other Computer Science · Computer Science 2025-07-11 Parv Agarwal , Nimesh Pinnamaneni , Thomas Heinis

Convolutional neural networks (CNNs) with convolutional and pooling operations along the frequency axis have been proposed to attain invariance to frequency shifts of features. However, this is inappropriate with regard to the fact that…

Computation and Language · Computer Science 2016-08-24 Hwaran Lee , Geonmin Kim , Ho-Gyeong Kim , Sang-Hoon Oh , Soo-Young Lee

We investigate the dynamics of DNA translocation through a nanopore using 2D Langevin dynamics simulations, focusing on the dependence of the translocation dynamics on the details of DNA sequences. The DNA molecules studied in this work are…

Soft Condensed Matter · Physics 2008-02-05 Kaifu Luo , Tapio Ala-Nissila , See-Chen Ying , Aniket Bhattacharya

The threading of a polymer chain through a small pore is a classic problem in polymer dynamics and underlies nanopore sensing technology. However important experimental aspects of the polymer motion in a solid-state nanopore, such as an…

Biological Physics · Physics 2016-07-18 Nicholas A. W. Bell , Ulrich F. Keyser

Dynamic nuclear polarization (DNP) has revolutionized the field of NMR spectroscopy, expanding its reach and capabilities to investigate diverse materials, biomolecules, and complex dynamic processes. Bringing high-efficiency DNP to the…

Mesoscale and Nanoscale Physics · Physics 2024-02-27 Sahand Tabatabaei , Pritam Priyadarsi , Namanish Singh , Pardis Sahafi , Daniel Tay , Andrew Jordan , Raffi Budakian

Solid-state nanopores are promising tools for single molecule detection of both DNA and proteins. In this study, we investigate the patterns of ionic current blockades as DNA translocates into or out of the geometric confinement of such…

Biological Physics · Physics 2017-04-05 Kaikai Chen , Nicholas A. W. Bell , Jinglin Kong , Yu Tian , Ulrich F. Keyser

We study theoretically the feasibility of using transverse electronic transport within a nanopore for rapid DNA sequencing. Specifically, we examine the effects of the environment and detection probes on the distinguishability of the DNA…

Soft Condensed Matter · Physics 2009-11-13 Johan Lagerqvist , Michael Zwolak , Massimiliano Di Ventra

In this paper we investigate the effects of graphene nanopore geometry on homopolymer ssDNA pulling process through nanopore using steered molecular dynamic (SMD) simulations. Different graphene nanopores are examined including axially…

Biological Physics · Physics 2015-01-12 Vahid Satarifard , Masumeh Foroutan , Mohammad Reza Ejtehadi

Dynamical nuclear polarisation (DNP) is an important technique that uses polarisation transfer from electron to nuclear spins to achieve nuclear hyperpolarisation. As the electron spin of the nitrogen vacancy (NV) centres in diamond can be…

We report an accurate method to determine DNA barcodes from the dwell time measurement of protein tags (barcodes) along the DNA backbone using Brownian dynamics simulation of a model DNA and use a recursive theoretical scheme which improves…

Soft Condensed Matter · Physics 2021-02-09 Swarnadeep Seth , Aniket Bhattacharya

Pooling layers are essential building blocks of convolutional neural networks (CNNs), to reduce computational overhead and increase the receptive fields of proceeding convolutional operations. Their goal is to produce downsampled volumes…

Computer Vision and Pattern Recognition · Computer Science 2022-12-05 Alexandros Stergiou , Ronald Poppe