imputation

Achieving improved accuracy for imputation of ancient DNA

This paper introduces an imputation method for ancient DNA that improves accuracy at lower coverages compared to existing tools.

Inverted genomic regions between reference genome builds in humans impact imputation accuracy and decrease the power of association testing

The paper identifies inverted genomic regions between human reference genome builds that affect imputation accuracy and association testing power, proposing a heuristic to correct these issues.

Single Pixel Reconstruction Imaging: taking confocal imaging to the extreme

This paper introduces SPiRI, a method that improves confocal microscopy resolution by using single-pixel image reconstruction, achieving 330 nm axial resolution and better 3D imaging of cellular structures.

Resolution doubling in light-sheet microscopy via oblique plane structured illumination

This paper demonstrates isotropic resolution doubling in light-sheet microscopy using oblique plane structured illumination, achieving sub-150nm lateral resolution with reduced phototoxicity and faster volumetric imaging.

SMbiot: A Shared Latent Model for Microbiomes and their Hosts

SMbiot identifies low-dimensional latent variables that capture host-microbiome associations and predicts missing metadata or community compositions.

Deep generative modeling and clustering of single cell Hi-C data

This paper introduces scDEC-Hi-C, a deep generative framework for analyzing single cell Hi-C data, showing improved clustering and imputation over existing methods.

SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification

SUMMIT improves transcriptomic data imputation and TWAS power by using large eQTL summary datasets, identifying 11 causal genes for COVID-19 severity.

Fast-exchanging spirocyclic rhodamine probes for aptamer-based super-resolution RNA imaging

This paper introduces RhoBAST:SpyRho, a fluorescent probe for high-resolution RNA imaging, showing improved brightness, fluorogenicity, and performance in super-resolution techniques.

KBeagle: An Adaptive Strategy and Tool for Improvement of Imputation Accuracy and Computing Efficiency

KBeagle improves imputation accuracy and reduces computing time by integrating K-Means clustering with Beagle software for genotype imputation.

MSBooster: Improving Peptide Identification Rates using Deep Learning-Based Features

MSBooster improves peptide identification rates by integrating deep learning-based features into existing workflows with MSFragger and Percolator.

A comparative analysis of current phasing and imputation software

This study benchmarks phasing and imputation software using three datasets, finding Beagle 5.2 most accurate for common markers and IMPUTE5 for low-frequency markers, while also creating an automated pipeline for customized chip design.

Imputation of Low-density Marker Chip Data in Plant Breeding: Evaluation of Methods Based on Sugar Beet

This paper evaluates imputation methods for low-density marker data in sugar beet breeding, finding that AlphaPlantImpute2 performs well with default settings while Beagle benefits from parameter tuning, and combining both tools yields the highest accuracy.

Turn-on Rate Determines the Blinking Propensity of Rhodamine Fluorophores for Super-Resolution Imaging

The paper identifies a turn-on rate parameter that explains why some rhodamines fail in super-resolution imaging despite meeting pKcycling criteria.

Joint Variational Autoencoders for Multi-Modal Imputation and Embedding

JAMIE imputes and embeds multimodal single-cell data with partial modality matches, outperforming existing methods and providing mechanistic insights.

Field dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging

This paper introduces FD-DeepLoc, a deep learning method for high-throughput 3D super-resolution imaging over a large field of view using a sCMOS camera.

FIST-nD: A tool for n-dimensional spatial transcriptomics data imputation via graph-regularized tensor completion

FIST-nD imputes 2D and 3D spatial transcriptomics data using graph-regularized tensor completion, improving accuracy for downstream analyses.

Simultaneous multicolor fluorescence imaging using duplication-based PSF splitting

The paper introduces a method to enhance fluorescence imaging by splitting the PSF into multiple copies, enabling simultaneous multicolor imaging with super-resolution and single-molecule capabilities.

A hybrid reconstruction of the physical model with the deep-learning that improves structured illumination microscopy

This paper introduces a hybrid method combining a physical model with deep learning to improve structured illumination microscopy, achieving better artifact suppression and resolution in low SNR images.

Automated STED nanoscopy for high-throughput imaging of cellular structures

This paper develops fully automated STED nanoscopy to increase data output and efficiency in high-throughput cellular imaging.

DomainRank: Improving Biological Data Sets With Domain Knowledge and Google's PageRank

DomainRank improves biological data quality using domain knowledge and PageRank, enhancing interaction detection and contact prediction in proteomics and cross-linking experiments.

Rapid, Reference-Free Human Genotype Imputation with Denoising Autoencoders

This paper introduces a denoising autoencoder for rapid, reference-free human genotype imputation, achieving higher accuracy and faster runtime than standard methods.

Homologue Series Detection and Management in LC-MS data with homologueDiscoverer

The paper introduces homologueDiscoverer, an R package for detecting and managing homologue series in LC-MS data through interactive plots and local databases.

EagleImp: Fast and Accurate Genome-wide Phasing and Imputation in a Single Tool

EagleImp provides fast and accurate genome-wide phasing and imputation, outperforming existing tools in speed while maintaining or improving accuracy.

HOPE-SIM, a cryo-structured illumination fluorescence microscopy system for accurately targeted cryo-electron tomography

The paper introduces HOPE-SIM, a cryo-CLEM system that improves targeting precision for cryo-ET by integrating 3D SIM and software, achieving 150 nm correlation accuracy.

Optimized fluorescent proteins for 4-color and photoconvertible live-cell imaging in Neurospora crassa

The paper evaluates fluorescent proteins for 4-color and photoconvertible live-cell imaging in Neurospora crassa, introducing genetic tools and promoters for enhanced imaging capabilities.

Miniaturised structured illumination microscopy using two 3-axis MEMS micromirrors

This paper develops a compact structured illumination microscope using MEMS micromirrors to achieve improved lateral resolution in fluorescent samples.

Two-color live-cell STED nanoscopy by click labeling with cell-permeable fluorophores

This paper demonstrates two-color STED nanoscopy using organic fluorophores and click labeling for long-term imaging of living cells.

SOGO-SOFI, light-modulated super-resolution optical fluctuation imaging using only 20 raw frames for high-fidelity reconstruction

This paper introduces SOGO-SOFI, a light-modulated super-resolution imaging technique that uses only 20 frames for high-fidelity reconstruction, achieving higher temporal resolution and reduced artifacts compared to pcSOFI.

Evaluation of Vicinity-based Hidden Markov Models for Genotype Imputation

This paper evaluates local hidden Markov models for genotype imputation, showing they can accurately impute common, uncommon, and rare variants.

Super-resolution vibrational imaging based on photoswitchable Raman probe

This paper introduces RESORT microscopy using photoswitchable Raman probes to achieve super-resolution vibrational imaging of live cells with high chemical specificity and spatial resolution.