imputation

Missing-value imputation and in silico region detection for spatially resolved transcriptomics

The paper introduces MIST, a tool that detects tissue regions and imputes missing gene-expression values in spatial transcriptomics data, improving accuracy and enabling downstream analysis.

Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs

The paper introduces Japonica Array NEO, a SNP array for the Japanese population with enhanced coverage and disease risk SNPs, showing high imputation quality and utility in genotyping cohorts.

N-Aryl Pyrido Cyanine derivatives: nuclear and organelle DNA markers for two-photon and super-resolution imaging

This paper introduces new DNA-binding fluorescent probes that enable high-selectivity, cell-permeable imaging of nuclear and organelle DNA using advanced microscopy techniques.

Chromatin-accessibility estimation of single-cell ATAC data with scOpen

scOpen improves downstream analysis of sparse scATAC-seq data by imputing open chromatin regions, revealing regulatory changes in kidney fibrosis.

Instant three color multi-plane fluorescence microscopy

This paper introduces a multi-plane multi-color fluorescence microscope capable of rapid volumetric imaging of fixed and living cells.

A Simple Optimization Workflow to Enable Precise and Accurate Imputation of Missing Values in Proteomic Datasets

This study evaluates imputation methods for proteomic datasets, finding that local and global methods perform best in different contexts and that fragment-level imputation improves accuracy.

Factorization-based Imputation of Expression in Single-cell Transcriptomic Analysis (FIESTA) recovers Gene-Cell-State Relationships

FIESTA imputes missing values in scRNA-seq data using non-negative matrix factorization, improving gene-cell-state relationships and marker discovery.

tdLanYFP, a yellow, bright, photostable and pH insensitive fluorescent protein for live cell imaging and FRET-based sensing strategies

Perfecting and extending the near-infrared biological window

The paper defines and extends the near-infrared biological window for improved in vivo fluorescence imaging, proposing new regions and demonstrating enhanced imaging capabilities.

Gene Expression Imputation with Generative Adversarial Imputation Nets

This paper introduces GAIN-GTEx, a gene expression imputation method that outperforms existing approaches on RNA-Seq data from cancer types and diverse tissues.

From partial to whole genome imputation of SARS-CoV-2 for epidemiological surveillance

The paper develops impuSARS, a method to impute missing SARS-CoV-2 genome sequences, improving the utility of incomplete data for epidemiological surveillance.

Missing Value Imputation using XGboost for Label-Free Mass Spectrometry-Based Proteomics Data

This paper introduces XGboost for missing value imputation in label-free proteomics data, showing it outperforms existing methods with empirical parameter settings.

Imputation of Spatially-resolved Transcriptomes by Graph-regularized Tensor Completion

This paper introduces FIST, a graph-regularized tensor completion model for imputing missing mRNA expressions in spatial transcriptomics data, showing improved performance over existing methods.

Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks

This paper introduces GraphSCI, a method that imputes dropout events in scRNA-seq data using graph convolution networks, outperforming existing methods on simulated and real data.

scGNN: a novel graph neural network framework for single-cell RNA-Seq analyses

scGNN introduces a graph neural network framework for scRNA-Seq analyses, improving gene imputation and cell clustering on benchmark datasets and revealing disease-related neural development in Alzheimer's disease.

Information-Efficient, Off-Center Sampling Results in Improved Precision in 3D Single Particle Tracking Microscopy

This paper introduces an optimized 3D single-particle tracking system using off-center sampling to improve localization precision by efficiently utilizing photons.

Fast holographic scattering compensation for deep tissue biologicalimaging

This paper introduces DASH, a fast algorithm for scattering compensation in deep tissue imaging, achieving significant signal enhancement in mouse hippocampal tissue.

A multi-task convolutional deep learning method for HLA allelic imputation and its application to trans-ethnic MHC fine-mapping of type 1 diabetes

DEEP*HLA improves HLA allelic imputation for low-frequency alleles, enabling trans-ethnic MHC fine-mapping of type 1 diabetes with high accuracy.

Structured illumination microscopy with noise-controlled image reconstructions

This paper introduces noise-controlled reconstruction methods for structured illumination microscopy to reduce artefacts and improve image quality.

Spatial frequency-based image reconstruction to improve image contrast in multi-offset adaptive optics ophthalmoscopy

The paper introduces a post-processing method to enhance retinal image contrast by optimally combining multi-offset AO ophthalmoscope images.

Human iPSC-derived renal cells change their immunogenic properties during maturation: Implications for regenerative therapies

This study shows that hiPSC-derived renal cells become less immunogenic as they mature, with implications for improving immune tolerance in regenerative therapies.

Two-pass alignment using machine-learning-filtered splice junctions increases the accuracy of intron detection in long-read RNA sequencing

The paper improves intron detection in long-read RNA sequencing by filtering spurious splice junctions using machine learning and a two-pass alignment approach.

Self-contained and modular structured illumination microscope

The paper introduces a modular structured illumination microscope (SIM) called HIT-SIM that enhances existing fluorescence microscopes with fast super-resolution imaging capabilities.

WEDGE: imputation of gene expression values from single-cell RNA-seq datasets using biased matrix decomposition

WEDGE imputes gene expression values in single-cell RNA-seq datasets using biased matrix decomposition, improving clustering and correlation recovery in sparse data.

A 48-Channel Receive Array Coil for Mesoscopic Diffusion-Weighted MRI of Human ex vivo Brain Imaging on the 3T Connectome Scanner

This paper designs and validates a 48-channel receive array coil for high-resolution, high b-value diffusion-weighted ex vivo brain MRI, showing improved SNR and imaging performance compared to in vivo coils.

Cryo-TEM simulations of amorphous radiation-sensitive samples using multislice wave propagation.

The paper introduces a new method for simulating cryo-EM images of amorphous samples, improving accuracy by modeling spatially variable inelastic scattering and radiation damage.

Synthesizing VERDICT maps from standard DWI data using GANs

This study synthesizes VERDICT maps from standard DWI data using GANs, showing strong correlation between synthetic and real maps for tumor area quantification.

MEMS enabled miniaturized light-sheet microscopy with all optical control

This paper describes a compact, cost-effective light-sheet microscopy system using MEMS scanners and tunable lenses for biomedical imaging.

View-channel-depth light-field microscopy: real-time volumetric reconstruction of biological dynamics by deep learning

This paper introduces a deep learning method to improve light-field microscopy, enabling high-speed, artifact-free volumetric imaging of biological processes.

Bfimpute: A Bayesian factorization method to recover single-cell RNA sequencing data

Bfimpute is a Bayesian factorization method for imputing single-cell RNA-seq data, achieving better accuracy than existing methods on simulated and real data.