imputation

Threshold illumination for non-invasive imaging of cells and tissues

The paper investigates the effect of light intensity and wavelength on cell contractility, finding that red light below 57 W/m2 maintains force homeostasis, suggesting its use for non-invasive imaging.

Fast Nonnegative Matrix Factorization andApplications to Pattern Extraction, Deconvolutionand Imputation

The paper introduces a fast nonnegative matrix factorization algorithm that handles missing values and integrates prior knowledge, implemented in the R package NNLM.

Deep Learning Enhanced Hyperspectral Fluorescence Lifetime Imaging

This paper introduces a deep learning framework for fast hyperspectral fluorescence lifetime imaging, achieving rapid acquisition and processing without training data.

A Pairwise Distance Distribution Correction (DDC) algorithm to eliminate blinking-caused artifacts in super-resolution microscopy

The paper introduces DDC, a method to correct blinking artifacts in SMLM by using true pairwise distance distributions, improving spatial reconstruction accuracy.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations

This study uses TOPMed whole genome sequences to improve imputation quality and detect rare variant associations in admixed African and Hispanic/Latino populations, identifying two novel associations with hematological traits.

Symmetrically-dispersed spectroscopic single-molecule localization microscopy

This paper introduces SDsSMLM, a spectroscopic single-molecule localization microscopy technique that improves spatial and spectral precision by symmetrically dispersing photons.

Multi-photon attenuation-compensated light-sheet fluorescence microscopy

This paper introduces a method to improve depth penetration in multi-photon light-sheet fluorescence microscopy using a graded neutral density filter, benchmarked against a spatial light modulator system.

SCRIBE: a new approach to dropout imputation and batch effects correction for single-cell RNA-seq data

SCRIBE imputes dropout events and corrects batch effects in scRNA-seq data, improving recovery of cell-specific gene expression and biological variation.

Fast and accurate defocus for improved tunability of cryo-EM experiments

This paper introduces a method to modulate defocus during cryo-EM movie acquisition, enabling per-frame defocus adjustments for improved experimental tunability.

A Multi-Breed Reference Panel and Additional Rare Variation Maximizes Imputation Accuracy in Cattle

The paper improves imputation accuracy in cattle by using a multi-breed reference panel with rare variants from the GGP-F250 assay.

Porous upconversion nanostructures as bimodal biomedical imaging contrast agents

This study designs core-porous shell upconversion nanoparticles to enhance both fluorescent and MRI signals for dual-modal biomedical imaging.

Live Cell Imaging of Single RNA Molecules with Fluorogenic Mango II Arrays

This paper introduces a novel Mango II aptamer array for high-contrast, single-molecule RNA imaging in live and fixed cells, showing improved signal-to-noise ratio and compatibility with super-resolution microscopy.

A Spectral De-mixing Model for Triplex In Vivo Imaging of Optical Coherence Tomography Contrast Agents

This paper introduces a spectral de-mixing model to detect multiple OCT contrast agents in vivo, validated using gold nanobipyramids in a live mouse.

scGAIN: Single Cell RNA-seq Data Imputation using Generative Adversarial Networks

scGAIN imputes missing gene expressions in scRNA-seq data using GANs, improving clustering and matching with bulk RNA-seq.

Improving imputation quality in BEAGLE for crop and livestock data

The paper evaluates BEAGLE versions for imputation quality in crop and livestock data, finding that parameter tuning significantly improves imputation accuracy.

A Recurrent Neural Network Based Method for Genotype Imputation on Phased Genotype Data

This paper introduces a recurrent neural network method for genotype imputation using phased genotype data, showing comparable accuracy to existing methods for common variants and better performance when haplotype data is limited.

deepMc: deep Matrix Completion for imputation of single cell RNA-seq data

deepMc uses deep matrix factorization to impute missing values in single cell RNA-seq data, improving clustering, differential expression analysis, and cell type separability.

Whole-genome reference panel of 1,781 Northeast Asians improves imputation accuracy of rare and low-frequency variants

The paper introduces a whole-genome reference panel of 1,781 Northeast Asians, showing improved imputation accuracy for rare and low-frequency variants compared to existing panels.

DeepImpute: an accurate, fast and scalable deep neural network method to impute single-cell RNA-Seq data

DeepImpute is a deep neural network method for imputing single-cell RNA-seq data, showing better accuracy and scalability than existing methods.

Autonomous bioluminescence imaging of single mammalian cells with the bacterial bioluminescence system

This paper demonstrates autonomous bioluminescence imaging of mammalian cells using the bacterial bioluminescence system, achieving luminescence comparable to firefly luciferase.

Three-dimensional super-resolution fluorescence imaging of DNA

This paper develops a 3D super-resolution imaging method for DNA using BALM and optical astigmatism, demonstrating its application to single DNA molecules and metaphase chromosomes.

bayNorm: Bayesian gene expression recovery, imputation and normalisation for single cell RNA-sequencing data

bayNorm provides a Bayesian method for normalizing, imputing, and recovering gene expression in scRNA-seq data, improving accuracy and reducing batch effects.

High speed multi-plane super-resolution structured illumination microscopy of living cells using an image-splitting prism

This paper introduces a multi-plane SR-SIM technique to enable fast 3D live cell imaging using an image-splitting prism and additional camera.

A framework for testing different imputation methods for tabular datasets

The paper develops a framework to test imputation methods on a clinical stroke dataset and finds that listwise deletion performs poorly, while the best method depends on the missing data mechanism.

Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction

The paper presents artifact-free whole-slide imaging using structured illumination microscopy and Bayesian image reconstruction, showcasing applications in human tissue pathology.

xQTLImp: efficient and accurate xQTL summary statistics imputation

xQTLImp imputes missing xQTL summary statistics using multivariate Gaussian approximation, rediscovering novel significant eQTL associations in a single-cell dataset.

Legacy Data Confounds Genomics Studies

The paper identifies a batch effect in 1000 Genomes Project data causing spurious mutation calls and affecting GWAS results, suggesting legacy data may need to be retired or upgraded.

Accurate and Efficient Cell Lineage Tree Inference from Noisy Single Cell Data: the Maximum Likelihood Perfect Phylogeny Approach

ScisTree infers cell lineage trees from noisy single-cell data using genotype probabilities, achieving high accuracy and efficiency compared to existing methods.

Synergic Combination of Stimulated Emission Depletion Microscopy with Image Scanning Microscopy to Reduce Light Dosage

This paper combines STED microscopy with image scanning microscopy to reduce light dosage while maintaining resolution.

Volumetric Lissajous Confocal Microscopy

This paper introduces volumetric Lissajous confocal microscopy to achieve high-speed 3D imaging with tunable sampling rates and sub-millisecond acquisition times.