imputation

High-speed compressed-sensing fluorescence lifetime imaging microscopy of live cells

This paper introduces compressed FLIM for high-speed, high-resolution live-cell imaging, achieving 100 Hz imaging with reduced photobleaching and motion artifacts.

Visualization of giant virus particles using BONCAT labeling and STED microscopy

The paper uses BONCAT labeling and STED microscopy to visualize giant virus particles in Cafeteria burkhardae during infection with CroV, demonstrating efficient AHA incorporation into viral proteins.

Exploring neighborhoods in large metagenome assembly graphs reveals hidden sequence diversity

The paper introduces a system to recover missing genomic content from metagenomic data by analyzing subgraphs in assembly graphs.

IMPLICON: an ultra-deep sequencing method to uncover DNA methylation at imprinted regions

IMPLICON is a high-throughput method for measuring DNA methylation at imprinted regions with high coverage and resolution, validated in mice and adapted for human use to detect imprinting errors.

Flexible Experimental Designs for Valid Single-cell RNA-sequencing Experiments Allowing Batch Effects Correction

This paper introduces BUSseq, a Bayesian model that corrects batch effects in scRNA-seq data while clustering cell types and imputing missing values.

Imputing missing RNA-seq data from DNA methylation by using transfer learning based-deep neural network

The paper introduces TDimpute, a transfer learning-based deep neural network for imputing missing RNA-seq data using DNA methylation, showing improved accuracy across 16 cancer datasets.

Wide field-of-view volumetric imaging by a mesoscopic scanning oblique plane microscopy with switchable objective lens

This paper introduces a new variant of oblique plane microscopy (OPM) that achieves a large mesoscopic field-of-view for volumetric imaging, demonstrating its application on zebrafish larvae, mouse cortex, and C. elegans.

Learning a latent representation of human genomics using Avocado

This paper introduces Avocado, a deep learning method that learns latent representations of human genomics data, enabling accurate imputation of unperformed experiments and improved performance on genomics tasks.

scIGANs: single-cell RNA-seq imputation using generative adversarial networks

scIGANs uses GANs to impute dropouts in scRNA-seq data, improving downstream analysis and performance across datasets.

Miniaturized Devices for Bioluminescence Imaging in Freely Behaving Animals

This paper demonstrates a modified fluorescent miniscope capable of detecting bioluminescence in vivo with improved sensitivity and reduced hardware complexity.

Wide-field Fluorescence Lifetime Imaging Microscopy with a High-Speed Mega-pixel SPAD Camera

This paper introduces a high-speed wide-field FLIM system using a SPAD camera and neural network for faster lifetime estimation, demonstrating real-time imaging capabilities.

Protein enhanced NIR-IIb emission of indocyanine green for functional bioimaging

This study demonstrates that indocyanine green (ICG) emits strong NIR-IIb fluorescence when dissolved in protein solutions, enabling high-resolution bioimaging with improved signal-to-background ratio.

A peptide-level multiple imputation strategy accounting for the different natures of missing values in proteomics data

Estimating what fraction of missing proteomics values are missing completely at random lets MCAR- and MNAR-specific imputers be combined; on simulations this beats standard imputation.

A 3D Reconstruction Algorithm for Real-time Simultaneous Multi-Source EIT Imaging for Lung Function Monitoring

This paper presents a 3D EIT algorithm for real-time lung function monitoring using simulated data, phantoms, and human subjects.

Network-enabled efficient image restoration for 3D microscopy of turbid biological specimens

This paper introduces ScatNet, a deep-learning method for restoring 3D fluorescence microscopy images of turbid biological specimens, improving resolution and signal-to-noise ratio.

In vivo corneal and lenticular microscopy with asymmetric fundus retroillumination

This paper introduces a new non-contact in vivo microscopy technique for corneal and lenticular imaging using asymmetric fundus retroillumination, achieving micron-scale resolution.

Biologically excretable AIE dots for visualizing through the marmosets intravitally: horizons in future clinical nanomedicine

This study designs excretable AIE dots for deep-tissue imaging in marmosets, demonstrating their biocompatibility and excretion capabilities.

AlphaFamImpute: high accuracy imputation in full-sib families from genotype-by-sequencing data

AlphaFamImpute improves genotype imputation in full-sib families using low-coverage GBS data by leveraging shared haplotype segments between siblings.

Light-Sheet Fluorescence Microscopy with Scanning Non-diffracting Beams

This paper enhances light-sheet fluorescence microscopy by using scanning non-diffracting beams, improving image quality in complex biological samples.

Self-activated photoblinking of nitrogen vacancy centers in nanodiamonds (sandSTORM): A method for rapid single molecule localization microscopy with unlimited observation time

This paper introduces sandSTORM, a STORM variant using nanodiamonds for faster, less damaging super-resolution imaging with unlimited observation time.

How to quantitatively measure, assess and correct the fluorescence crosstalk in the wide-field microscopy

The paper introduces a quantitative metric and protocol to measure and correct fluorescence crosstalk in wide-field microscopy using common image processing software.

Probabilistic Optically-Selective Single-molecule Imaging Based Localization Encoded (POSSIBLE) Microscopy for Ultra-superresolution Imaging of Dendra2-HA transfected NIH3T3 cells

This paper introduces POSSIBLE microscopy to achieve ultra-superresolution imaging by selecting bright molecules with narrow size-distribution, resulting in better-resolved clusters in NIH3T3 cells.

Adapting genotyping-by-sequencing and variant calling for heterogeneous stock rats

The paper adapts genotype-by-sequencing for HS rats to call and impute over 3.7 million SNPs with 99% concordance compared to a genotyping array.

Fast scanned widefield scheme provides tunable and uniform illumination for optimized SMLM on large fields of view

This paper introduces ASTER, a new illumination technique that enables uniform and tunable illumination for SMLM over large fields of view, improving imaging precision and throughput.

A hybrid open-top light-sheet microscope for multi-scale imaging of cleared tissues

The paper introduces a hybrid light-sheet microscope that enables versatile multi-scale imaging of cleared tissues with varying resolution, geometry, and compatibility requirements.

Application of aptamers improves CRISPR-based live imaging of plant telomeres

This paper improves CRISPR-based live imaging of plant telomeres using aptamers, showing better labeling quality in transiently transformed plants but limitations in stable transformations.

Fluorogenic probe for fast 3D whole-cell DNA-PAINT

This paper introduces a fluorogenic DNA-PAINT probe that reduces background and increases imaging speed for 3D whole-cell DNA-PAINT.

Scedar: a scalable Python package for single-cell RNA-seq exploratory data analysis

Scedar is a Python package for scRNA-seq exploratory analysis, offering visualization, imputation, rare profile detection, and clustering on large datasets efficiently and without distribution assumptions.

Deep learning enables structured illumination microscopy with low light levels and enhanced speed

This paper uses deep learning to improve structured illumination microscopy, reducing image requirements and enabling low-light, high-speed super-resolution imaging.

PRIME: a probabilistic imputation method to reduce dropouteffects in single cell RNA sequencing

PRIME is a probabilistic imputation method that reduces dropout effects in single-cell RNA sequencing data, improving visualization quality and clustering accuracy.